Publications by Dr Chee Siang (Jim) Ang

Printed electronics using flexible substrates are an emerging area, allowing next-generation electronics to conform and flex with different surfaces, from human skin to clothing. In the hybrid integration, or sea-of-rigids, approach, conventional microchips are mounted onto (generally) plastic substrates such as polyethylene naphthalate (PEN), with (typically) printed silver tracks for interconnections between components. An ongoing research direction is to replace plastic substrates with biodegrad- able substrates and to replace silver tracks with non-heavy metal-based tracks. While the substrates and tracks form only part of an overall system, replacing them is a step towards increased sustainability and helps to meet net-zero goals for printed electronic systems. Previously, several papers have inves- tigated printed carbon tracks for low-frequency analog sensing applications. This paper explores the feasibility of using printed carbon tracks on biodegradable substrates for high-frequency applications such as digital signaling over a Serial-Peripheral Interface (SPI). We investigate the printability, thermal stability, and electrical conductivity of carbon ink screen-printed onto six commercially available sustainable and flexible substrates. Our results demonstrate that multi-layer screen printing substantially reduced the electrical resistance of carbon tracks, enabling SPI communication at frequencies up to 16 MHz with three layers of carbon ink. A Natureflex™ substrate provided the best balance of printability, thermal stability, and electrical performance. Substrates such as greaseproof paper and ClearFilm PU showed

Background Family caregivers provide essential care in the home to millions of individuals around the globe annually. However, family caregiving results in considerable burden, financial hardship, stress and psychological morbidity. Identifying and managing stress in caregivers is important as they have a dual role in manging their own health as well as that of the person they care for. If stress becomes overwhelming, a caregiver may no longer be able to perform this essential role. Digital methods of stress monitoring may be one strategy of identifying effective interventions to relieve caregiver burden and stress. Objective To explore perceived acceptability, challenges, and opportunities of using digital and biosensing technologies to measure caregiver stress. Methods We conducted a descriptive qualitative study using semi-structured interviews and reflexive thematic analysis methods. We recruited adult family caregivers (18 years) currently or previously caring for an adult in the home with significant health issues. Interview questions focused on stress monitoring more generally and on ecological momentary assessment, remote monitoring technologies such as smartwatches, and fluid biosensors. Results We recruited 27 family caregivers of whom 70% were currently in a caregiving role, the remainder were previously in a caregiving role. We identified three themes with ten subthemes. Themes comprised 'Providing meaningful data' with subthemes of 'Monitoring without action is pointless'; 'Monitoring that enables self-management' and 'Seeing the bigger picture'; 'Low burden monitoring' with subthemes of 'Low effort', 'Practical alongside daily routines' and 'Retaining control over monitoring'; and 'Inadvertent harms of stress monitoring' with subthemes of 'Stigma of stress', 'Need for discretion', 'Contributing to stress', and 'Trust'. Conclusion In this descriptive qualitative study examining the perspectives of a diverse sample of family caregivers on methods of stress monitoring we identified three themes. These provide useful considerations for use of stress monitoring and implementation of interventions to ameliorate family caregiver stress of relevance to social care and community teams, researchers, and policy makers. These include providing meaningful situationally specific data resulting in action, that does not contribute to caregiver burden, or in inadvertent harm to either the caregiver or the care recipient.

One factor leading to compromised Quality of Life (QoL) for people with dementia in long-term care settings is the significant barriers they face in accessing experiences beyond their physical premises. Although, in recent years, research within HCI has investigated the use of Virtual Reality (VR) in providing enriched experiences for people with dementia, few studies have looked into the practical issues relating to integrating and deploying VR into care settings and how in-depth understanding of such issues can inspire VR design for dementia care. Considering the perspective of key stakeholders, we demonstrate VR's potential to create a rich conversation space with family members, preserve the identity and personhood of people with dementia through VR, and consider organisational issues of VR deployment in care settings. As such, this paper contributes to the HCI research community with future design directions to enhance the deployment and adoption of VR in dementia care settings.

Background and Objectives: Virtual reality (VR) interventions provide immersive, interactive computer-simulated virtual environments. There is interest in their use for people with dementia as they may provide stimulating experiences and improve dementia symptoms and quality of life. However, as more insight is needed about carers' and clinical professionals' perspectives to understand how VR may be implemented successfully, we elicited their views on the benefits of, and challenges to, using VR in dementia care. Methods: We conducted five qualitative focus groups involving 25 healthcare professionals and informal carers with experience of dementia care. Participants received a demonstration of a VR headset and content and were then questioned following a topic guide asking for views on benefits of, and challenges to, using VR for dementia care. Findings: The main findings addressed the benefits of, and concerns about, the impact and implications of VR on wellbeing, ethics, implementation, caregivers and services. Overall, participants had a positive attitude toward VR and made several suggestions for its future use to enable enjoyable and immersive experiences. Examples included suggestions to personalise VR content to accommodate heterogenous profiles and stages of dementia, co-developing protocols to address health risks and side effects and further investigating shared experiences of VR with caregivers. Conclusion: Healthcare professionals and informal carers thought that VR had potential to enhance a holistic and personalised approach to dementia care. They suggested changes which could guide future implementation of VR interventions for dementia patients and their caregivers.

The development of AI to function as communicators (i.e. conversational agents), has opened the opportunity to rethink AI's place within people's social worlds, and the process of sense-making between humans and machines, especially for people with autism who may stand to benefit from such interactions. The current study aims to explore the interactions of six autistic and six non-autistic adults with a conversational virtual human (CVH/conversational agent/chatbot) over 1-4 weeks. Using semi-structured interviews, conversational chatlogs and post-study online questionnaires, we present findings related to human-chatbot interaction, chatbot humanization/dehumanization and chatbot's autistic/non-autistic traits through thematic analysis. Findings suggest that although autistic users are willing to converse with the chatbot, there are no indications of relationship development with the chatbot. Our analysis also highlighted autistic users' expectations of empathy from the chatbot. In the case of the non-autistic users, they tried to stretch the conversational agent's abilities by continuously testing the AI conversational/cognitive skills. Moreover, non-autistic users were content with Kuki's basic conversational skills, while on the contrary, autistic participants expected more in-depth conversations, as they trusted Kuki more. The findings offer insights to a new human-chatbot interaction model specifically for users with autism with a view to supporting them via companionship and social connectedness.

Mental illness has recently become a global health issue, causing significant suffering in people's lives and having a negative impact on productivity. In this study, we analyzed the generalization capacity of machine learning to classify various mental illnesses across multiple social media platforms (Twitter and Reddit). Language samples were gathered from Reddit and Twitter postings in discussion forums devoted to various forms of mental illness (anxiety, autism, schizophrenia, depression, bipolar disorder, and BPD). Following this process, information from 606,208 posts (Reddit) created by a total of 248,537 people and from 23,102,773 tweets was used for the analysis. We initially trained and tested machine learning models (CNN and Word2vec) using labeled Twitter datasets, and then we utilized the dataset from Reddit to assess the effectiveness of our trained models and vice versa. According to the experimental findings, the suggested method successfully classified mental illness in social media texts even when training datasets did not include keywords or when unrelated datasets were utilized for testing.

It is estimated that 55 million people are living with dementia worldwide in 2021, and the numbers are expected to rise to 78 million in 2030 and 139 million in 2050 (Siriaraya et al., 2022; World Health Organisation, 2022). Dementia is an umbrella term that describes neurodegenerative disorders that impact memory, cognition, language, and behaviour (Beck et al., 1998; Cohen-Mansfield, 2001; Kane, 2001). Along with symptoms of dementia such as forgetfulness, disorientation and communication, People with Dementia (PwD) often lose their sense of autonomy and capacity to make decisions in various or all aspects of their life (Garcia-Palacios et al., 2002; Jones et al., 2015). Currently, there is no cure for dementia. Thus, promoting well-being in PwD or Quality of Life (QoL) is considered a quintessential measure of effective dementia care (Van Nieuwenhuizen and Nijman, 2009). QoL for dementia care is multifaceted, which includes measures related to i. physical comfort, hygiene, and wellbeing, ii. safety, security, and order, iii. maintaining a sense of autonomy, dignity, and privacy, as well as iv. living a meaningful life, individuality, maintaining relationships, and enjoyment (Kane, 2001). However, such measures of QoL can be challenging to achieve due to the complexity of dementia symptoms (i.e. cognitive decline, losing the ability to communicate, behaviour that challenges, etc.) (Hennelly et al., 2021) and families' burden of caring for PwD against other competing priorities (Sury et al., 2013). In the case of institutionalised care, care settings suffer from understaffing and a low retention rate (Brown Wilson, 2009; Bunn et al., 2020), which leads care settings to focus on delivering everyday care (i.e. physical safety, assistance in eating and bathing) over other psychosocial QoL measures (Hicks et al., 2022). As such, there is an immense need to develop tools, interventions, and solutions to preserve and promote PwD's QoL and overall physical, emotional and mental well-being. We discuss key areas of digital technologies which are relevant to dementia care. We then conclude by summarising the six papers of this special issue.

With one-person households being increasingly common and Covid-19 lockdown policies forcing people to stay home, remote dining has become common practice for many, who take it as an opportunity to connect with others in times of loneliness. Sharing meals online, also known as digital commensality, is a rich form of interaction, where people leverage technology to achieve a sense of connectedness and belonging while eating. In this paper, we look at digital commensality and we explore its inherent playful potential with the aim to inspire the design of engaging technologies that can support, enhance and augment this form of interaction. For this, we used a situated play design approach to document and analyze the behavior of 36 people (including pairs of friends and strangers) sharing meals online. Our analysis surfaced a set of play potentials of remote dining -- i.e., playful things people already do and enjoy spontaneously while sharing meals online. We present those play potentials as inspirational material: they can motivate and enrich the design of future digital commensality technologies by responding to people's desire for playful and social interaction with, through, and around food.

Mindless eating, or the lack of awareness of the food we are consuming, has been linked to health problems attributed to unhealthy eating behaviour, including obesity. Traditional approaches used to moderate eating behaviour often rely on inaccurate self-logging, manual observations or bulky equipment. Overall, there is a clear unmet clinical need to develop an intelligent and lightweight system which can automatically monitor eating behaviour and provide feedback. In this paper, we investigate: i) the development of an automated system for detecting eating behaviour using wearable Electromyography (EMG) sensors, and ii) the application of the proposed system combined with real-time wristband haptic feedback to facilitate mindful eating. For this, the collected data from 16 participants were used to develop an algorithm for detecting chewing and swallowing. We extracted 18 features from EMG which were presented to different classifiers, to develop a system enabling participants to self-moderate their chewing behaviour using haptic feedback. An additional experimental study was conducted with 20 further participants to evaluate the effectiveness of eating monitoring and haptic interface in promoting mindful eating. We used a standard validation scheme with a leave-one-participant-out to assess model performance using standard metrics (F1-score). The proposed algorithm automatically assessed eating behaviour accurately using the EMG-extracted features and a Support Vector Machine (SVM): F1-Score=0.95 for chewing classification, and F1-Score=0.87 for swallowing classification. The experimental study showed that participants exhibited a lower rate of chewing when haptic feedback was delivered in the form of wristband vibration, compared to a baseline and non-haptic condition (F (2,38) = 58.243, p <.001). These findings may have major implications for research in eating behaviour, providing key insights into the impact of automatic chewing detection and haptic feedback systems on moderating eating behaviour towards improving health outcomes.

Losing a loved one through death is known to be one of the most challenging life events. To help the bereaved and their therapists monitor and better understand the factors that contribute to Prolonged Grief Disorder (PGD), we co-designed and studied a web-based explainable AI screening system named "Grief Inquiries Following Tragedy (GIFT)." We used an initial iteration of the system to collect PGD- related data from 611 participants. Using this data, we developed a model that could be used to screen and explain the different factors contributing to PGD. Our results showed that a Random Forest model using Bereavement risk and outcome features performed best in detecting PGD (AUC=0.772), with features such as a negative intepretation of grief and the ability to integrate stressful life events contributing strongly to the model. Afterwards, five grief experts were asked to provide feedback on a mock-up of the results generated by the GIFT model, and discuss the potential value of the explanatory AI model in real-world PGD care. Overall, the grief experts were generally receptive towards using such a tool in a clinical setting and acknowledged the benefit of offering a personalized result to the users based on the explainable AI model. Our results also showed that, in addition to the explainability of the model, the grief experts also preferred a more "empathetic" and "actionable" AI system, especially, when designing for patient end-users.

Background : Repetitive transcranial magnetic stimulation (rTMS) is effective in treating depression; however, the effect on physical activity, sleep and recovery is unclear. This study investigated rTMS effect on physical activity and sleep through providing patients with a Fitbit and software apps; and reports the impact of rTMS on depression, anxiety and mental health recovery. Methods : Study design was a pre and post data collection without a control, with twenty-four participants with treatment-resistant depression (TRD). Measures used were Fitbit activity and sleep data, and patient-rated Recovering Quality of Life (ReQoL-20), Patient Health Questionnaire (PHQ-9) and Generalised Anxiety Disorder (GAD-7). Results : Response and remission rates were, respectively: 34.8% and 39% for PHQ-9; 34.8% and 47.8% for GAD-7. ReQoL-20 response and reliable improvement were 29.4% and 53%. PHQ-9, GAD-7 and ReQol-20 scores significantly improved, with large effect sizes. Analysis of Fitbit activity and sleep data yielded non-significant results. The Fitbit data machine learning model classified two levels of depression to 82% accuracy. Limitations : rTMS treatment was open-label and adjunct to existing antidepressant medication. No control group. Female patients were overrepresented. Conclusions : Improvements on the ReQoL-20 and aspects of sleep and activity indicate the positive impact of rTMS on the individual's real world functioning and quality of life. A wearable activity tracker can provide feedback to patients and clinicians on sleep, physical activity and depression levels. Further research could be undertaken through a sufficiently powered RCT comparing rTMS versus rTMS with use of a Fitbit, its software applications, and sleep and physical activity advice.

The paper introduces a multimodal affective dataset named VREED (VR Eyes: Emotions Dataset) in which emotions were triggered using immersive 360° Video-Based Virtual Environments (360-VEs) delivered via Virtual Reality (VR) headset. Behavioural (eye tracking) and physiological signals (Electrocardiogram (ECG) and Galvanic Skin Response (GSR)) were captured, together with self-reported responses, from healthy participants (n=34) experiencing 360-VEs (n=12, 1-3 min each) selected through focus groups and a pilot trial. Statistical analysis confirmed the validity of the selected 360-VEs in eliciting the desired emotions. Preliminary machine learning analysis was carried out, demonstrating state-of-the-art performance reported in affective computing literature using non-immersive modalities. VREED is among the first multimodal VR datasets in emotion recognition using behavioural and physiological signals. VREED is made publicly available on Kaggle 1. We hope that this contribution encourages other researchers to utilise VREED further to understand emotional responses in VR and ultimately enhance VR experiences design in applications where emotional elicitation plays a key role, i.e. healthcare, gaming, education, etc.

Motor imagery offers an excellent opportunity as a stimulus-free paradigm for brain-machine interfaces. Conventional electroencephalography (EEG) for motor imagery requires a hair cap with multiple wired electrodes and messy gels, causing motion artifacts. Here, we introduce a wireless scalp electronic system with virtual reality for real-time, continuous classification of motor imagery brain signals. This low-profile, portable system integrates imperceptible microneedle electrodes and soft wireless circuits. Virtual reality addresses subject variance in detectable EEG response to motor imagery by providing clear, consistent visuals and instant biofeedback. The wearable soft system offers advantageous contact surface area and reduced electrode impedance density, resulting in significantly enhanced EEG signals and classification accuracy. The combination with convolutional neural network-machine learning provides a real-time, continuous motor imagery-based brain-machine interface. With four human subjects, the scalp electronic system offers a high classification accuracy (93.22±1.33% for four classes), allowing wireless, real-time control of a virtual reality game.

Momentary photography is enjoyed by many smartphone users, especially with the popularity of apps such as Snapchat and Instagram. Many traditional positive psychology interventions focus on lengthy writing tasks to express positive emotions experienced during past events, acts of kindness and gratuitous situations. In this work we developed SnapAppy, a smartphone application to integrate momentary photography with traditional intervention methodologies to conduct a month-long positive psychology intervention to improve emotional well-being. A study involving 74 participants aimed to assess whether photo-taking, photo viewing and image contents are correlated with improvements in certain aspects of the participant's emotional well-being including their mood, affect and satisfaction with life. The results indicated that features including the number of photos, the variety of categories, the effort applied to annotating photos, the number of photos revisited and photos taken of people were positively correlated with an improvement in the participant's mood and positive and negative affect (PANAS).

Despite the substantial research interest in using Virtual Reality (VR) in healthcare in general and in Psychological, Cognitive, and Behavioral (PC&B) interventions in specific, as well as emerging research supporting the efficacy of VR in healthcare, the design process of translating therapies into VR to meet the needs of critical stakeholders such as users and clinicians is rarely addressed. In this paper, we aim to shed light onto the design needs, opportunities and challenges in designing efficient and effective PC&B-VR interventions. Through analyzing the co-design processes of four user-centered PC&B-VR interventions, we examined how therapies were adapted into VR to meet stakeholders' requirements, explored design elements for meaningful experiences, and investigated how the understanding of healthcare contexts contribute to the VR intervention design. This paper presents the HCI research community with design opportunities and challenges as well as future directions for PC&B-VR intervention design.

Although short tandem repeat (STR) analysis is available as a reliable method for the determination of the genetic origin of cell lines, the occurrence of misauthenticated cell lines remains an important issue. Reasons include the cost, effort and time associated with STR analysis. Moreover, there are currently no methods for the discrimination between isogenic cell lines (cell lines of the same genetic origin, e.g. different cell lines derived from the same organism, clonal sublines, sublines adapted to grow under certain conditions). Hence, additional complementary, ideally low-cost and low-effort methods are required that enable 1) the monitoring of cell line identity as part of the daily laboratory routine and 2) the authentication of isogenic cell lines. In this research, we automate the process of cell line identification by image-based analysis using deep convolutional neural networks. Two different convolutional neural networks models (MobileNet and InceptionResNet V2) were trained to automatically identify four parental cancer cell line (COLO 704, EFO-21, EFO-27 and UKF-NB-3) and their sublines adapted to the anti-cancer drugs cisplatin (COLO-704rCDDP1000, EFO-21rCDDP2000, EFO-27rCDDP2000) or oxaliplatin (UKF-NB-3rOXALI2000), hence resulting in an eight-class problem. Our best performing model, InceptionResNet V2, achieved an average of 0.91 F1-score on 10-fold cross validation with an average area under the curve (AUC) of 0.95, for the 8-class problem. Our best model also achieved an average F1-score of 0.94 and 0.96 on the authentication through a classification process of the four parental cell lines and the respective drug-adapted cells, respectively, on a four-class problem separately. These findings provide the basis for further development of the application of deep learning for the automation of cell line authentication into a readily available easy-to-use methodology that enables routine monitoring of the identity of cell lines including isogenic cell lines. It should be noted that, this is just a proof of principal that, images can also be used as a method for authentication of cancer cell lines and not a replacement for the STR method.

Recent years have seen a growing research interest towards designing computer-assisted health interventions aiming to improve mental health services. Digital technologies are becoming common methods for diagnosis, therapy, and training. With the advent of lower-cost VR head-mounted-displays (HMDs) and high internet data transfer capacity, there is a new opportunity for applying immersive VR tools to augment existing interventions. This study is among the first to explore the use of a Multi-User Virtual Reality (MUVR) system as a therapeutic medium for participants at high-risk for developing Eating Disorders. This paper demonstrates the positive effect of using MUVR remote psychotherapy to enhance traditional therapeutic practices. The study capitalises on the opportunities which are offered by a MUVR remote psychotherapeutic session to enhance the outcome of Acceptance and Commitment Therapy, Play Therapy and Exposure Therapy for sufferers with body shape and weight concerns. Moreover, the study presents the design opportunities and challenges of such technology, while strengths on the feasibility, and the positive user acceptability of introducing MUVR to facilitate remote psychotherapy. Finally, the appeal of using VR for remote psychotherapy and its observed positive impact on both therapists and participants is discussed.

Traditional methods for screening and diagnosis of alcohol dependence are typically administered by trained clinicians in medical settings and often rely on interview responses. These self-reports can be unintentionally or deliberately false, and misleading answers can, in turn, lead to inaccurate assessment and diagnosis. In this study, we examine the use of user-game interaction patterns on mobile games to develop an automated diagnostic and screening tool for alcohol-dependent patients. Our approach relies on the capture of interaction patterns during gameplay, while potential patients engage with popular mobile games on smartphones. The captured signals include gameplay performance, touch gestures, and device motion, with the intention of identifying patients with alcohol dependence. We evaluate the classification performance of various supervised learning algorithms on data collected from 40 patients and 40 age-matched healthy adults. The results show that patients with alcohol dependence can be automatically identified accurately using the ensemble of touch, device motion, and gameplay performance features on 3-minute samples (accuracy=0.95, sensitivity=0.95, and specificity=0.95). The present findings provide strong evidence suggesting the potential use of user-game interaction metrics on existing mobile games as discriminant features for developing an implicit measure to identify alcohol dependence conditions. In addition to supporting healthcare professionals in clinical decision-making, the game-based self-screening method could be used as a novel strategy to promote alcohol dependence screening, especially outside of clinical settings.

Ocular disorders are currently affecting the developed world, causing loss of productivity in adults and children. While the cause of such disorders is not clear, neurological issues are often considered as the biggest possibility. Treatment of strabismus and vergence requires an invasive surgery or clinic-based vision therapy that has been used for decades due to the lack of alternatives such as portable therapeutic tools. Recent advancement in electronic packaging and image processing techniques have opened the possibility for optics-based portable eye tracking approaches, but several technical and safety hurdles limit the implementation of the technology in wearable applications. Here, we introduce a fully wearable, wireless soft electronic system that offers a portable, highly sensitive tracking of eye movements (vergence) via the combination of skin-conformal sensors and a virtual reality system. Advancement of material processing and printing technologies based on aerosol jet printing enables reliable manufacturing of skin-like sensors, while a flexible electronic circuit is prepared by the integration of chip components onto a soft elastomeric membrane. Analytical and computational study of a data classification algorithm provides a highly accurate tool for real-time detection and classification of ocular motions. In vivo demonstration with 14 human subjects captures the potential of the wearable electronics as a portable therapy system, which can be easily synchronized with a virtual reality headset.

Variation in human brains creates difficulty in implementing electroencephalography (EEG) into universal brain-machine interfaces (BMI). Conventional EEG systems typically suffer from motion artifacts, extensive preparation time, and bulky equipment, while existing EEG classification methods require training on a per-subject or per-session basis. Here, we introduce a fully portable, wireless, flexible scalp electronic system, incorporating a set of dry electrodes and flexible membrane circuit. Time domain analysis using convolutional neural networks allows for an accurate, real-time classification of steady-state visually evoked potentials on the occipital lobe. Simultaneous comparison of EEG signals with two commercial systems captures the improved performance of the flexible electronics with significant reduction of noise and electromagnetic interference. The two-channel scalp electronic system achieves a high information transfer rate (122.1 ± 3.53 bits per minute) with six human subjects, allowing for a wireless, real-time, universal EEG classification for an electronic wheelchair, motorized vehicle, and keyboard-less presentation.

Background and objectives: Emerging research supports virtual reality use with people with dementia in the community, but is limited to this area, warranting further investigation in different care settings. The feasibility of virtual reality within an inpatient psychiatric care setting was therefore explored. Research design and methods: Eight people with dementia and 16 caregivers were recruited in January and February 2018 from a UK hospital specialising in progressive neurological conditions. A mixed methods design measured affect and behaviour using the Observed Emotion Rating Scale, Overt Aggression Scale-Modified for Neurorehabilitation and St Andrew's Sexual Behaviour Assessment. Thematic analysis was conducted following semi-structured interviews. Caregivers who worked at the hospital supported people with dementia throughout the process and were interviewed for their views on Head Mounted Display-Virtual Reality (HMD-VR) use with people with dementia. Results: HMD-VR was tried and accepted by people with dementia. Participants viewed HMD-VR positively as a 'change in environment' and would use it again. People with dementia experienced more pleasure during and after HMD-VR compared to before exposure, as well as increased alertness after. Three core themes emerged: 'Virtual Reality Experiences', 'Impact of Virtual Reality' and 'Experiences within the Virtual Environment'. Caregivers discussed preconceptions about virtual reality use and how these changed. Discussion and implications: This is the first study to explore the feasibility of HMD-VR with people with mild to moderately severe dementia in hospital and found that overall HMD-VR is viable. Findings evidence the clinical feasibility of HMD-VR implementation in this environment and inform future research.

Early detection of cognitive decline is important for timely intervention and treatment strategies to prevent further dete- rioration or development of more severe cognitive impairment, as well as identify at risk individuals for research. In this paper, we explore the feasibility of using data collected from built-in sensors of mobile phone and gameplay performance in mobile-game-based cognitive assessments. Twenty-two healthy participants took part in the two-session experiment where they were asked to take a series of standard cognitive assessments followed by playing three popular mobile games in which user-game interaction data were passively collected. The results from bivariate analysis reveal correlations between our proposed features and scores obtained from paper-based cognitive assessments. Our results show that touch gestural interaction and device motion patterns can be used as supplementary features on mobile game-based cognitive measurement. This study provides initial evidence that game related metrics on existing off-the-shelf games have potential to be used as proxies for conventional cognitive measures, specifically for visuospatial function, visual search capability, mental flexibility, memory and attention.

Scholarly efforts to understand conspiracy theories have grown significantly in recent years, and there is now a broad and interdisciplinary literature that we review in this article. We ask three specific questions. First, what are the factors that are associated with conspiracy theorizing? Our review of the literature shows that conspiracy beliefs result from a range of psychological, political and social factors. Next, how are conspiracy theories communicated? Here, we explain how conspiracy theories are shared among individuals and spread through traditional and social media platforms. Next, what are the risks and rewards associated with conspiracy theories? By focusing on politics and science, we argue that conspiracy theories do more harm than good. Finally, because this is a growing literature and many open questions remain, we conclude by suggesting several promising avenues for future research.

Background: Cognitive Bias Modification of Interpretations (CBM-I) is a computerized intervention designed to change negatively biased interpretations of ambiguous information, which underlie and reinforce anxiety. The repetitive and monotonous features of CBM-I can negatively impact training adherence and learning processes. Objective: This proof-of-concept study aimed to examine whether performing a CBM-I training using mobile virtual reality technology (virtual reality Cognitive Bias Modification of Interpretations [VR-CBM-I]) improves training experience and effectiveness. Methods: A total of 42 students high in trait anxiety completed 1 session of either VR-CBM-I or standard CBM-I training for performance anxiety. Participants' feelings of immersion and presence, emotional reactivity to a stressor, and changes in interpretation bias and state anxiety, were assessed. Results: The VR-CBM-I resulted in greater feelings of presence (P<.001, d=1.47) and immersion (P<.001, ηp2=0.74) in the training scenarios and outperformed the standard training in effects on state anxiety (P<.001, ηp2=0.3) and emotional reactivity to a stressor (P=.03, ηp2=0.12). Both training varieties successfully increased the endorsement of positive interpretations (P<.001, drepeated measures [drm]=0.79) and decreased negative ones. (P<.001, drm=0.72). In addition, changes in the emotional outcomes were correlated with greater feelings of immersion and presence. Conclusions: This study provided first evidence that (1) the putative working principles underlying CBM-I trainings can be translated into a virtual environment and (2) virtual reality holds promise as a tool to boost the effects of CMB-I training for highly anxious individuals while increasing users' experience with the training application.

Objectives: Past research has shown that Virtual Reality (VR) is an effective method for reducing the perception of pain and effort associated with exercise. As pain and effort are subjective feelings, they are influenced by a variety of psychological factors, including one's awareness of internal body sensations, known as Private Body Consciousness (PBC). The goal of the present study was to investigate whether the effectiveness of VR in reducing the feeling of exercise pain and effort is moderated by PBC. Design and Methods: Eighty participants were recruited to this study and were randomly assigned to a VR or a non-VR control group. All participants were required to maintain a 20% 1RM isometric bicep curl, whilst reporting ratings of pain intensity and perception of effort. Participants in the VR group completed the isometric bicep curl task whilst wearing a VR device which simulated an exercising environment. Participants in the non-VR group completed a conventional isometric bicep curl exercise without VR. Participants' heart rate was continuously monitored along with time to exhaustion. A questionnaire was used to assess PBC. Results: Participants in the VR group reported significantly lower pain and effort and exhibited longer time to exhaustion compared to the non-VR group. Notably, PBC had no effect on these measures and did not interact with the VR manipulation. Conclusions: Results verified that VR during exercise could reduce negative sensations associated with exercise regardless of the levels of PBC.

The detection and monitoring of emotions are important in various applications, e.g. to enable naturalistic and personalised human-robot interaction. Emotion detection often require modelling of various data inputs from multiple modalities, including physiological signals (e.g.EEG and GSR), environmental data (e.g. audio and weather), videos (e.g. for capturing facial expressions and gestures) and more recently motion and location data. Many traditional machine learning algorithms have been utilised to capture the diversity of multimodal data at the sensors and features levels for human emotion classification. While the feature engineering processes often embedded in these algorithms are beneficial for emotion modelling, they inherit some critical limitations which may hinder the development of reliable and accurate models. In this work, we adopt a deep learning approach for emotion classification through an iterative process by adding and removing large number of sensor signals from different modalities. Our dataset was collected in a real-world study from smart-phones and wearable devices. It merges local interaction of three sensor modalities: on-body, environmental and location into global model that represents signal dynamics along with the temporal relationships of each modality. Our approach employs a series of learning algorithms including a hybrid approach using Convolutional Neural Network and Long Short-term Memory Recurrent Neural Network (CNN-LSTM) on the raw sensor data, eliminating the needs for manual feature extraction and engineering. The results show that the adoption of deep-learning approaches is effective in human emotion classification when large number of sensors input is utilised (average accuracy 95% and F-Measure=%95) and the hybrid models outperform traditional fully connected deep neural network (average accuracy 73% and F-Measure=73%). Furthermore, the hybrid models outperform previously developed Ensemble algorithms that utilise feature engineering to train the model average accuracy 83% and F-Measure=82%)

Many advocate for artificial agents to be empathic. Crowdsourc- ing could help, by facilitating human-in-the-loop approaches and dataset crea- tion for visual emotion recognition algorithms. Although crowdsourcing has been employed successfully for a range of tasks, it is not clear how effective crowdsourcing is when the task involves subjective rating of emotions. We ex- amined relationships between demographics, empathy and ethnic identity in pain emotion recognition tasks. Amazon MTurkers viewed images of strangers in painful settings, and tagged subjects' emotions. They rated their level of pain arousal and confidence in their responses, and completed tests to gauge trait empathy and ethnic identity. We found that Caucasian participants were less confident than others, even when viewing other Caucasians in pain. Gender cor- related to word choices for describing images, though not to pain arousal or confidence. The results underscore the need for verified information on crowdworkers, to harness diversity effectively for metadata generation tasks.

A novel sensor-based Internet of Educational Things (IoET) platform named OBSY was iteratively designed, developed and evaluated to support education in rural regions in Thailand. To assess the effectiveness of this platform, a study was carried out at four primary schools located near the Thai northern border with 244 students and 8 teachers. Participants were asked to carry out three science-based learning activities and were measured for improvements in learning outcome and learning engagement. Overall, the results showed that students in the IoET group who had used OBSY to learn showed significantly higher learning outcome and had better learning engagement than those in the control condition. In addition, for those in the IoET group, there was no significant effect regarding gender, home location (Urban or Rural), age, prior experience with technology and ethnicity on learning outcome. For learning engagement, only age was found to influence interest/enjoyment. The study demonstrated the potential of IoET technologies in underprivileged area, through a co-design approach with teachers and students, taking into account the local contexts.

Today's mobile phone users are faced with large numbers of notifications on social media, ranging from new followers on Twitter and emails to messages received from WhatsApp and Facebook. These digital alerts continuously disrupt activities through instant calls for attention. This paper examines closely the way everyday users interact with notifications and their impact on users' emotion. Fifty users were recruited to download our application NotiMind and use it over a five-week period. Users' phones collected thousands of social and system notifications along with affect data collected via self-reported PANAS tests three times a day. Results showed a noticeable correlation between positive affective measures and keyboard activities. When large numbers of Post and Remove notifications occur, a corresponding increase in negative affective measures is detected. Our predictive model has achieved a good accuracy level using three different "in the wild" classifiers (F-measure 74-78% within- subject model, 72-76% global model). Our findings show that it is possible to automatically predict when people are experiencing positive, neutral or negative affective states based on interactions with notifications. We also show how our findings open the door to a wide range of applications in relation to emotion awareness on social and mobile communication.

Abstract: The perception of three-dimensional sculptural forms is quite different from two-dimensional art works such as painting and drawing. Though both are considered forms of artistic production, the distinction is the tactual and kinesthetic sensations of the three-dimensional sculptural forms. The understanding of the perception of sculptural forms adds another dimension to cognitive and emotive qualities embedded in art. The emotions evoked while observing, knowing, touching, and feeling a sculpture, as well as the experiences of working, creating, and producing one, affect an individual's perception. People with dementia who develop visual and perceptual difficulties may gradually have a different experience of sculpture. The materiality of a sculpture and its tactile engagement have the capacity to influence their perception. With spatial errors, changes in colour, and misperceptions, there is a possibility that they see, appreciate, and experience, in a different way, both physical sculptural forms and those that are mediated through digital technology.

We introduce a skin-friendly electronic system that enables human-computer interaction (HCI) for swallowing training in dysphagia rehabilitation. For an ergonomic HCI, we utilize a soft, highly compliant ("skin-like") electrode, which addresses critical issues of an existing rigid and planar electrode combined with a problematic conductive electrolyte and adhesive pad. The skin-like electrode offers a highly conformal, user-comfortable interaction with the skin for long-term wearable, high-fidelity recording of swallowing electromyograms on the chin. Mechanics modeling and experimental quantification captures the ultra-elastic mechanical characteristics of an open mesh microstructured sensor, conjugated with an elastomeric membrane. Systematic in vivo studies investigate the functionality of the soft electronics for HCI-enabled swallowing training, which includes the application of a biofeedback system to detect swallowing behavior. The collection of results demonstrates clinical feasibility of the ergonomic electronics in HCI-driven rehabilitation for patients with swallowing disorders.

Background: This report details the development of the Men's Safer Sex website and the results of a feasibility randomised controlled trial (RCT), health economic assessment and qualitative evaluation. Objectives: (1) Develop the Men's Safer Sex website to address barriers to condom use; (2) determine the best design for an online RCT; (3) inform the methods for collecting and analysing health economic data; (4) assess the Sexual Quality of Life (SQoL) questionnaire and European Quality of Life-5 Dimensions, three-level version (EQ-5D-3L) to calculate quality-adjusted life-years (QALYs); and (5) explore clinic staff and men's views of online research methodology. Methods: (1) Website development: we combined evidence from research literature and the views of experts (n = 18) and male clinic users (n = 43); (2) feasibility RCT: 159 heterosexually active men were recruited from three sexual health clinics and were randomised by computer to the Men's Safer Sex website plus usual care (n = 84) or usual clinic care only (n = 75). Men were invited to complete online questionnaires at 3, 6, 9 and 12 months, and sexually transmitted infection (STI) diagnoses were recorded from clinic notes at 12 months; (3) health economic evaluation: we investigated the impact of using different questionnaires to calculate utilities and QALYs (the EQ-5D-3L and SQoL questionnaire), and compared different methods to collect resource use; and (4) qualitative evaluation: thematic analysis of interviews with 11 male trial participants and nine clinic staff, as well as free-text comments from online outcome questionnaires. Results: (1) Software errors and clinic Wi-Fi access presented significant challenges. Response rates for online questionnaires were poor but improved with larger vouchers (from 36% with £10 to 50% with £30). Clinical records were located for 94% of participants for STI diagnoses. There were no group differences in condomless sex with female partners [incidence rate ratio (IRR) 1.01, 95% confidence interval (CI) 0.52 to 1.96]. New STI diagnoses were recorded for 8.8% (7/80) of the intervention group and 13.0% (9/69) of the control group (IRR 0.75, 95% CI 0.29 to 1.89). (2) Health-care resource data were more complete using patient files than questionnaires. The probability that the intervention is cost-effective is sensitive to the source of data used and whether or not data on intended pregnancies are included. (3) The pilot RCT fitted well around clinical activities but 37% of the intervention group did not see the Men's Safer Sex website and technical problems were frustrating. Men's views of the Men's Safer Sex website and research procedures were largely positive. Conclusions: It would be feasible to conduct a large-scale RCT using clinic STI diagnoses as a primary outcome; however, technical errors and a poor response rate limited the collection of online self-reported outcomes. The next steps are (1) to optimise software for online trials, (2) to find the best ways to integrate digital health promotion with clinical services, (3) to develop more precise methods for collecting resource use data and (4) to work out how to overcome barriers to digital intervention testing and implementation in the NHS. Trial registration: Current Controlled Trials ISRCTN18649610. Funding: This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 91. See the NIHR Journals Library website for further project information.

Linguistic mimicry, the adoption of another's language patterns, is a subconscious behavior with pro-social benefits. However, some professions advocate its conscious use in empathic communication. This involves mutual mimicry; effective communicators mimic their interlocutors, who also mimic them back. Since mimicry has often been studied in face-to-face contexts, we ask whether individuals with empathic dis- positions have unique communication styles and/or elicit mimicry in mediated communication on Facebook. Participants completed Davis' Interpersonal Reactivity Index and provided access to Facebook activity. We confirm that dispositional empathy is correlated to the use of particular stylistic features. In addition, we identify four empathy profiles and find correlations to writing style. When a linguistic feature is used, this often "triggers" use by friends. However, the presence of particular features, rather than participant dispo- sition, best predicts mimicry. This suggests that machine-human communications could be enhanced based on recently used features, without extensive user profiling.

With the increasing incidence and prevalence of chronic brain injury patients and the current financial constraints in healthcare budgets, there is a need for a more intelligent way to realise the current practice of neuro-rehabilitation service provision. Brain-computer Interface (BCI) systems have the potential to address this issue to a certain extent only if carefully designed research can demonstrate that these systems are accurate, safe, cost-effective, are able to increase patient/carer satisfaction and enhance their quality of life. Therefore, one of the objectives of the proposed study was to examine whether participants (patients with brain injury and a sample of reference population) were able to use a low cost BCI system (Emotiv EPOC) to interact with a computer and to communicate via spelling words. Patients participated in the study did not have prior experience in using BCI headsets so as to measure the user experience in the first-exposure to BCI training. To measure emotional arousal of participants we used an ElectroDermal Activity Sensor (Qsensor by Affectiva). For the signal processing and feature extraction of imagery controls the Cognitive Suite of Emotiv's Control Panel was used. Our study reports the key findings based on data obtained from a group of patients and a sample reference population and presents the implications for the design and development of a BCI system for communication and control. The study also evaluates the performance of the system when used practically in context of an acute clinical environment.

The availability of advanced software and less expensive hardware allows museums to preserve and share artefacts digitally. As a result, museums are frequently making their collections accessible online as interactive, 3D models. This could lead to the unique situation of viewing the digital artefact before the physical artefact. Experiencing artefacts digitally outside of the museum on personal devices may affect the user's ability to emotionally connect to the artefacts. This study examines how two target populations of young adults (18–21 years) and the elderly (65 years and older) responded to seeing cultural heritage artefacts in three different modalities: augmented reality on a tablet, 3D models on a laptop, and then physical artefacts. Specifically, the time spent, enjoyment, and emotional responses were analysed. Results revealed that regardless of age, the digital modalities were enjoyable and encouraged emotional responses. Seeing the physical artefacts after the digital ones did not lessen their enjoyment or emotions felt. These findings aim to provide an insight into the effectiveness of 3D artefacts viewed on personal devices and artefacts shown outside of the museum for encouraging emotional responses from older and younger people.

Computer-mediated communication has become a popular platform for identity construction and experimentation as well as social interaction for those who identify as lesbian, gay, bisexual or transgender (LGBT). The creation of user-generated videos has allowed content creators to share experiences on LGBT topics. With bullying becoming more common amongst LGBT youth, it is important to obtain a greater understanding of this phenomenon. In our study, we report on the analysis of 151 YouTube videos which were identified as having LGBT- and bullying-related content. The analysis reveals how content creators openly disclose personal information about themselves and their experiences in a non-anonymous rhetoric with an unknown public. These disclosures could indicate a desire to seek friendship, support and provide empathy.

It seems self-evident that smell profoundly shapes emotion, but less clear is the nature of this interaction. Here we sought to determine whether the ability to identify odors co-varies with self-reported feelings of empathy and emotional expression recognition, as predicted if the two capacities draw on common resource. Thirty six neurotypical volunteers were administered the Alberta Smell Test, The Interpersonal Reactivity Index and an emotional expression recognition task. Statistical analyses indicated that feelings of emotional empathy positively correlated with odor discrimination in right nostril, while the recognition of happy and fearful facial expressions positively correlated with odor discrimination in left nostril. These results uncover new links between olfactory discrimination and emotion which, given the ipsilateral configuration of the olfactory projections, point towards intra- rather than inter-hemispheric interaction. The results also provide novel support for the proposed lateralisation of emotional empathy and the recognition of facial expression, and give reason to further explore the diagnostic sensitivity of smell tests because reduced sensitivity to others' emotions can mark the onset of certain neurological diseases.

The need to provide low-cost learning technologies such as laptops or tablet computers in developing countries with the aim to bridge the digital divide as well as addressing the uneven standards of education quality has been widely recognised by previous studies. With this aim in mind, the Thai Government has launched the "One Tablet PC Per Child" (OTPC) policy and distributed 800,000 tablet computers to grade-one students nationwide in 2012. However, there is limited empirical evidence on the effectiveness of tablet computer use in the classroom. Our study examined students' learning styles, attitudes towards tablet computer use and how these are linked to their academic performance. The study has investigated 213 grade two students in economically underprivileged regions of North Thailand. Data collection was based on questionnaires filled in by the students with the help of their teachers. Our results overall suggested that there were some key significant differences in relation to students' gender and home locations (urban vs. rural). In contrast to existing studies, both genders at this stage had similar technology experience and positive attitudes towards tablet computer use. However, we found girls had higher visual learning style (M = 4.23, p < .032) than boys (M = 3.96). Where home location was concerned, rural students had higher learning competitiveness and higher levels of anxiety towards tablet use (M = 1.71, p < .028) than urban students (M = 1.33). Additionally, we also found technology experiences, collaborative learning style and anxiety affected students' academic performance.

This paper presents the results of energy conservation strategies implemented in the University residential halls to address energy consumption issues, using IPTED (Integration of Persuasive Technology and Energy Delegate) in the student residential halls. The results show that real time energy feedback from a visual interface, when combined with energy delegate can provide significant energy savings. Therefore, applying IPTED reveals a significant conservation and carbon emission reduction as a result from the intervention conducted in student hall of residents comprising of 16 halls with 112 students. Overall, the intervention revealed that, the use of real time feedback system reduced energy consumption significantly when compared to baseline readings. Interestingly, we found that the combination of real time feedback system with a human energy delegate in 8 halls resulted in higher reduction of 37% in energy consumptions when compared to the baseline amounting to savings of 1360.49 kWh, and 713.71 kg of CO2 in the experimental halls. On the contrary, the 8 non-experimental halls, which were exposed to the real time feedback and weekly email alert, resulted in only 3.5% reduction in energy consumption when compared to the baseline, amounting to savings of only 165.00 kWh, and 86.56 kg of CO2.

There is a need for energy conservation mechanisms, especially in university campuses, as students do not have any direct feedback on their energy consumptions, which leads to excess usages. There are few existing approaches aiming to reduce electricity usages in higher education institutions through real-time feedback applications. These approaches mainly apply student experimental studies with incentives (gift reward). Their feedback systems present data only in near real time using data loggers and Modbus data collector, which are characterised with a slow and unstable data transfer rate. Furthermore, they are not designed for long-term deployment in a wider campus energy management environment. Thus, the challenges for reducing energy consumption and carbon emissions in the higher education sector still remain. To address these challenges, we have designed, configured and implemented a robust persuasive feedback support system (PFSS) to facilitate energy conservation and carbon emission reduction. This paper presents the complete architecture of the proposed PFSS, its system interface and the real time measurement output strategies. To demonstrate the applicability of the proposed system and to assess its performance in comparison with the previous

Massively Multi-player Online Role-playing Games (MMORPGs) have become a popular leisure activity. It has been suggested that the reason for their popularity is that they offer a new 'third-place' for people to socialise. However, designing for sociability in these games has been shown to be a challenge. In this article, we discuss the results of an online survey that was directed towards game design researchers and professionals. We then present a subsequent discussion on the results of the survey at a Special Interest Group (SIG) held at CHI 2011. Through analysis of the findings of the survey and the discussion, we propose six requirements that facilitate the design of MMORPGs: In-game Communication, Off-game Communication, Empathy, Grouping and Rewards, World Design, and Designed Relationships. We state that it is not necessary to add all the proposed requirements in the design of such games, but we also caution that a game that does not include any of the requirements presented here cannot belong to this genre. We discuss limitations of this work, and offer future research directions that result from this work.

There is an increasing need to find innovative activities to help the older population maintain a healthy life. Virtual worlds, which can provide social engagement, entertainment and creativity as well as useful information and services for older people might offer a solution to this issue. Although emerging studies have begun to look into the benefits of virtual worlds in healthcare, little has been done in the context of older people. Based on semi-structured interviews and previous research on healthy aging, we identified and described in depth four areas in which virtual worlds could be useful to support older people. In general, it was found that virtual worlds could help empower older people to manage their disabilities, facilitate social engagement, provide mental stimulation and productive activities.

3D virtual worlds are becoming increasingly popular as tool for social interaction, with the potential of augmenting the user's perception of physical and social presence. Thus, this technology could be of great benefit to older people, providing home-bound older users with access to social, educational and recreational resources. However, so far there have been few studies looking into how older people engage with virtual worlds, as most research in this area focuses on younger users. In this study, an online experiment was conducted with 30 older and 30 younger users to investigate age differences in the perception of presence in the use of virtual worlds for social interaction. Overall, we found that factors such as navigation and prior experience with text messaging tools played a key role in older people's perception of presence. Both physical and social presence was found to be linked to the quality of social interaction for users of both age groups. In addition, older people displayed proxemic behavior which was more similar to proxemic behavior in the physical world when compared to younger users.

3D online multi-user virtual environments (MUVEs) have a lot of potential in supporting older people in their daily lives, yet little research has been conducted to explore how older people engage with this type of technology. This paper aims to investigate the characteristics, user groups and activity patterns (particularly social networks and gift giving behaviour) of older users within a 3D online multi-user virtual environment. Data from approximately 5000 online user profiles of older and younger users from a 3D MUVE, namely IMVU, was collected for analysis. Overall, we identified several distinct patterns of use (e.g. size of social ties, level of reciprocity, etc.) among older users when compared with younger users. We also found that despite the capabilities of 3D MUVEs to provide the users immersion in alternative realities, a feature well embraced by younger users in this study, older users seemed more interested in activities which serve as an extension to their physical life.

The impact of energy consumption and carbon emission in the UK poses a grave challenge. This challenge is particularly high amongst residents of university campuses, where usage of electricity and carbon emission remain invisible to the students. In student residential accommodation, personal choices and social influences affect electricity consumption and ultimately the resultant reduction in carbon emissions. Therefore, innovative solutions are required to change students' energy consumption behavior, and one promising part of the solution is to present real-time electricity consumption data to students in real-time via a dedicated web platform, while, at the same time, appointing an energy delegate in each hall to induce motivation among the students. The results of some interventions show that immediate energy feedback from smart meters or display devices can provide savings of 5%–15%. However, the situation is different; with the complexity in behavior of our target groups "the students who are living in the halls of residence", there are economical and environmental aspects to be addressed in these issues, in the campus halls of residence. Therefore, we propose a system to address this issue, by applying smart sensors (real-time electricity data capture), integration of dedicated visual web interface (real-time electricity feedback display) and an appointed energy delegate in each hall (a motivator). It is expected that this will motivate students living in the halls of residence to reduce their electricity wastage and, therefore, control the energy cost and also reduce the carbon emissions released into the environment. In the present research, we focus on the University of Kent, Canterbury campus to study energy conservation and carbon emission reduction strategies.

In this study, we adopted the social network analysis (SNA) approach and applied it to massively multiplayer online games studies. Virtual participant observation was carried out through which we identified seven types of interaction (grouped into task and social orientated interaction categories) using thematic analysis and recorded "who-talk-to-whom" relationships for each of these seven interaction types. The first part of the study was conducted to explore descriptively the patterns of user interaction. It was followed by a detailed study to look into these issues using SNA statistical techniques known as P* modeling. We found that task interactions were more unequal and expansive while social interactions were more densely knitted, resulting in horizontal and cohesive group formation. The studies also demonstrated the benefits of combining SNA and qualitative methods.

Online social network services (SNS) provide an unprecedented rich source of information about millions of users worldwide. However, most existing studies of this emerging phenomenon are limited to relatively small data samples, with an emphasis on mostly "western" online communities (such as Facebook and MySpace users in Western countries). To understand the cultural characteristics of users of online social networks, this paper explores the behavioral patterns of more than 16 million users of a popular social network in the Russian segment of the Internet, namely, My.Mail.Ru (also known as "My World" or "Moj Mir" in Russian). Our main goal is to study the self-disclosure patterns of the site users as a function of their age and gender.We compare the findings of our analysis to the previous studies on Western users of SNS and discuss the culturally distinctive aspects. Our study highlights some important cultural differences in usage patterns among Russian users, which call for further studies in SNS in various cultural contexts.

Brain computer interfaces (BCI) enable users to transform their thoughts into actions without involving voluntary motor movement. This relatively new user interface technology not only offers those with severe neuromotor disabilities a new means to interact with the environment, but can also provides effective and engaging rehabilitation to restore motor or cognitive functions that have been impaired due to disease or trauma. This article summarizes the use of BCI in neurorehabilitation settings based on a review of relevant literature. It also identifies the challenges of BCI and provides recommendations for practical use and future directions for research. BCI could be a promising tool to assist patients undergoing neurological rehabilitation by providing access to environmental control and communication, as well as neurofeedback rehabilitation.

This article reports a study that investigated the occurrences of empathy in online support communities for teenagers. Qualitative content analysis with 400 messages from a discussion board about depression was used to identify how empathy was expressed in the specific online communication. Emphasis was also placed on the comparison of this age group to older people, by comparing the results with those from a previous study on empathy in an online support community about depression for older people. Specifically, the analysis focused on the frequencies of the categories of the code scheme, linguistic characteristics of the communication content, the occurring components of empathy, and the roles as well as activities of the members. From our analysis, we concluded that young people exchanged a substantial amount of empathic emotional communication when participating in an online support community, and they communicated on a more personal level compared to older people, who tended to engage in a more formal communication. In addition, teenagers also showed a high level of understanding but lower level of concern compared to older persons when expressing empathy online.

In this article, an online support community for older people is studied, with the aim of developing a taxonomy of social roles based on content analysis and social network analysis. Four hundred messages (posted between August 9, 2007, and February 5, 2008) in an online support community for older people (http://www.seniornet.org) were investigated. The data were analyzed to identify and shed light on patterns of the online functional behavior as well as the social structure of active members. Drawing on the findings, a set of six social roles were identified, defined, and described in depth. The findings showed that the structural positions of online community members were associated with the kind of content these members tended to post. For example, it was found that central members were very likely to give support, whereas members not very well connected were more inclined to post self-disclosing messages.

To provide an overview on social media for consumers and patients in areas of health behaviours and outcomes.

In this study, we investigated the social roles that emerged from the users' behaviour and intereaction (as opposed to pre-defined formal roles) within a virtual community of massively multiplaer online role playing game. Adopting the social network analysis perspective, we identified and analysed three major social roles with distinct interaction stuyles and network properties. It was found that core members of the community were players who contributed to the community expansion by provciding help and fostering group cohesiveness through friendly social interaction. On the other hand, some perphery members were freeloaders whose sole purpose of joining the guild was only to utilize the guild resource.

Various forms of play emerge around computer games. These types of play, known as out-of-game play or extrinsic play, take place beyond the original game context. Despite their significant contribution to the overall play experience, they are often neglected by the game research community. Conventional game theories such as ludology and narratology do not provide an insightful account of the socio-cultural aspects of game play. Therefore, in this article, we report our observations and investigations into different forms of extrinsic play activities in an online virtual setting. Founded on Activity Theory, we articulate theoretical models that explicate game play in a socio-cultural context. Our findings reveal that extrinsic play constitutes reflective play and expansive play, which transform the play activity and transport the players beyond the original boundary of play.

This article investigates how activity theory can help research a constructionist community. We present a constructionist activity model called Constructionism Through Activity Theory (CONTACT) model and explain how it can be used to analyse the constructionist activity in knowledge building communities. We then illustrate the model through its application to analysing the Wiki-supported community associated with a computer game. Our analysis focuses mainly on two perspectives: individual and collective actions, as well as individual and collective mediations. Experiences and challenges from the analysis are reported to demonstrate how CONTACT is helpful in analysing such communities.

We aimed to study the characteristics and usage patterns of 3D virtual worlds in the context of teaching and learning. To achieve this, we organised a full?day workshop to explore, discuss and investigate the educational use of 3D virtual worlds. Thirty participants took part in the workshop. All conversations were recorded and transcribed for analysis. Thematic analysis was carried out to identify prominent issues and topics. We found that to fully utilise 3D virtual worlds for teaching and learning, students, tutors and educational institutions face a number of socio?psychological, pedagogical and technological challenges. The paper highlights and discusses the issues that emerged from the workshop, supporting them with real life experiences and case studies provided by the workshop participants.

This article reviews a range of literature of computer games and learning theories and attempts to establish a link between them by proposing a typology of games which we use as a new usability measure for the development of guidelines for game-based learning. First, we examine game literature in order to understand the key elements that constitute games. This is then followed by the theoretical discussion of the relationship between the game components and the learning theories, namely behaviourism, cognitive constructivism, and social constructivism. Ten games are analysed using the learning theories and a typology of game is proposed that classifies games into four major categories. Then based on these findings we developed a set of guidelines for game-based learning using Human Computer Interaction (HCI) methods.

Purpose – Recently, researchers have begun investigating the learning process that occurs within computer games (learning to play), as opposed to studying games that support explicit learning for educational purposes (playing to learn). With the increasing popularity of massively multiplayer online games (MMOGs), some research has begun to look beyond individual play and is now focusing on social play. By conducting a 30 day virtual participant observation in an MMOG, namely World of Warcraft (WoW) this paper aims to identify and provide a theoretical explanation of the process of learning that takes place in such an open-ended virtual world. Design/methodology/approach – Through the lens of activity theory, the paper focuses its analysis on the tool, the goal, the activity of game playing and contradictions. Findings – It was found that social learning could occur through intrinsic and extrinsic play. Intrinsic play is play oriented toward goal completion while extrinsic play is directed toward reflection and expansion of intrinsic play. WoW is designed with tools that facilitate these types of play, and therefore learning that emerges from them. Furthermore, learning involves not only the process of acquiring knowledge and skills to accomplish certain goals, but also the process of defining the goal, thus shaping the learning process. Originality/value – The results could be used to inform game design either for social play or for social learning.

In conventional teaching there are three major goal structures: competitive learning, cooperative learning and individualistic learning. There has been much research into the effectiveness of these goal structures in conventional teaching. In regards to computer-aided learning, cooperative learning has been researched in game-based e-learning (GBEL), but competitive learning has mostly been overlooked. This research investigates the impact that competition has on the effectiveness of GBEL. The results of the experiment showed that when the e-learning game was played in a competitive context there was a lower learning improvement than if the game was played in a non-competitive, individualistic context.

Being one of the most commercially successful entertainment software applications, massively multiplayer online role playing games (MMORPGs) continue to expand in term of the revenue they generate as well as the involvement of users who congregate in their virtual space and form communities around them to support each other. Unlike conventional offline computer games, or networked games with limited numbers of players, MMORPGs are not merely software applications as they are usually seen as a space with complicated dynamics of social interactions. Hence, it is believed that playing these games might cause cognitive overload problems among the players as they have to constantly interact with the game world as well as with other users. We conducted an exploratory study using qualitative methods to explore cognitive overloads in Maple Story, a typical MMORPG. Our results reveal that several types of cognitive overloads emerge during the game playing. While some of these overloads pose serious problems even to expert players, players seem to develop strategies to overcome them. It is found that some forms of cognitive load are actually desirable in order to make the game challenging. We have also created a set of recommendations that can help game developers handle cognitive load problems in MMORPGs

The mid 20th century witnessed some serious attempts in studies of play and games with an emphasis on their importance within culture. Most prominently, Huizinga (1944) maintained in his book Homo Ludens that the earliest stage of culture is in the form of play and that culture proceeds in the shape and the mood of play. He also claimed that some elements of play crystallised as knowledge such as folklore, poetry and philosophy as culture advanced. A more contemporary play scholar, Crawford (1982), in his seminal book. The Art of Computer Game Design scrutinised play within computer games and maintained in line with Huizinga that play is the sources of knowledge and that the most fundamental motivation of play is, in fact, to learn. As cultures move forwards, the notion of play seems to receive more positive recognition among the society. In the society where youthfulness is regarded as a desirable state of human life (where cosmetic surgery is popular especially for women, and both sexes alter their hair colour with chemical dyes to hide the natural greying that occurs with age), playful behaviour might be one of the ways by which their members can present themselves as youthful (Kücklich, 2004). In addition, as human civilisation advances toward the post-industrialism era, people have more leisure time and disposable income to engage in play activities. As more emphasis is put on creative forms of labour, the boundaries between work and leisure time become blurred. Offe (as cited in Bills, 2003) for example, identified a trend away from work and toward leisure as the means by which people establish their identities in contemporary society.

This article explores the relationship between national culture and computer-mediated communication (CMC) in Wikipedia. The articles on the topic game from the French, German, Japanese, and Dutch Wikipedia websites were studied using content analysis methods. Correlations were investigated between patterns of contributions and the four dimensions of cultural influences proposed by Hofstede (Power Distance, Collectivism versus Individualism, Femininity versus Masculinity, and Uncertainty Avoidance). The analysis revealed cultural differences in the style of contributions across the cultures investigated, some of which are correlated with the dimensions identified by Hofstede. These findings suggest that cultural differences that are observed in the physical world also exist in the virtual world.

An explanatorystudy is conductedto examine the different kinds of rules in video games. Two layers of game, the abstract and the narrative layer, are explored to unify the study of gameplay and narratives. Derivatives of paidea rules and ludus rules are analyzed in relation to gameplay and narratives. A model is presented to show the relation between rules, gameplay, and narratives. Video games are seen as having two layers, an abstract layer and a narrative layer, which are linked by game rules. It is hence maintained that gameplay and narratives should not be antagonistic; they should be complementary when studying video games.

The computer game is about the player experience and enjoyment. It includes graphics, sounds, stories, user interfaces and most importantly gameplay. Setting player experiences aside, the game is governed by a set of rules that define how the game is played. Game design should focus more on the gameplay: the interaction between players and games. This paper attempts to study the core element of computer game that constitutes the gameplay. Other elements that contribute to the whole experience of game are also explored. The utilisation of Unified Modelling Language (UML) in designing interactivity in computer games is studied by performing reverse engineering on two games using use case diagrams and class diagrams. that all games can be decomposed into players and tokens, the interaction of which can be described by interaction matrices and finite state machine diagrams.

Virtual worlds offer much potential in supporting social interaction for older adults, particularly as a platform which can provide an interactive and immersive social experience. Yet, there has not been much work carried out to study the use, interaction and behavior of older people in 3D virtual world systems, especially studies which investigate their interactions in a fully functional virtual world. Most focus on issues related to usability such as cognitive difficulties when navigation in a 3D space and we know little about their perceptions and preferences when socializing in a virtual space. In this chapter, we report an experimental study examining the various factors which affected the social experience of older users in virtual worlds. The study involved 38 older participants engaging with a 3D and non-3D virtual grocery store. A mixed method of questionnaire and contextual interview was used for data collection and analysis. Overall, we found that physical presence was a significant predictor of many measures defining the quality of social interaction, yet participants often reported a sense of artificiality in their virtual experience. Interestingly, avatars were not considered directly important for social interaction and instead were only seen as a "place holder" to complete the tasks. Two factors contributed to this, the lack of non-verbal communication and the perceived difficulty in embodying physical people with virtual avatars.

A growing body of research exploits social media behaviors to gauge psychological character- istics, though trait empathy has received little attention. Because of its intimate link to the abil- ity to relate to others, our research aims to predict participants' levels of empathy, given their textual and friending behaviors on Facebook. Using Poisson regression, we compared the vari- ance explained in Davis' Interpersonal Reactivity Index (IRI) scores on four constructs (em- pathic concern, personal distress, fantasy, perspective taking), by two classes of variables: 1) post content and 2) linguistic style. Our study lays the groundwork for a greater understanding of empathy's role in facilitating interactions on social media.

The chapter discusses and examines the educational potential of computer games in language learning. The commercial success of games has recently attracted the scholarly study from various fields. However little has been done in term of learning theories despite the increasing interest in educational games. Thus, in this chapter, theoretical issues and practical challenges in game-based language learning are raised to provide an overview on the potential of gaming technologies for such purposes. Some prominent learning theories in relation to computer aided language learning are detailed. This is followed by a discussion of what computer games are before some case studies of game-based language learning are presented. Some implications on the language uses of computer games are derived and discussed.

Computer games have for years been the focus of Human Computer Interaction (HCI)-oriented research. For example, researchers have looked at playability and have developed heuristics for evaluating fun as well as usability of computer games (Desurvire, et al. 2004; Fabricatore, et al. 2002; Federoff 2002). Although much of this research has revolved around enhancing engagement by improving player-game interaction, some (Ducheneaut, et al. 204; Ducheneaut, et al. 2006; Kolo and Baur 2004) have begun to look into the social aspects of gaming as most computer game play is social. Surveys have shown that almost 60 percent of game players play with friends; 33 percent play with siblings and 25 percent play with spouses or parents (Jenkins 2006). Similarly, within the area of game-based learning, the focus is moving from treating games as a standalone tool that delivers knowledge to learners in an enjoyable way, to utilising games as a medium for social interaction and collaboration.

This chapter attempts to examine computer game theories — ludology and narratology— that explain computer games as play activities and storytelling media. Founded onthis theoretical explanation, a game model that incorporates gameplay and narrativesis presented. From the model, two aspects of learning in the game environment areidentified: gameplay-oriented and narrative-oriented. It is believed that playingcomputer games involves at least one of these types of learning; thus, this game's naturecan be used in designing engaging educational software. In addition, based onMalone's theoretical framework on motivational heuristics, there are two methods ofapplying computer games in language learning: extrinsic and intrinsic, depending onthe integration of game designs and learning materials. Then, two cases of language-learning games are scrutinized, using the game model, in order to demonstrate the useof computer games in language learning.

People living with dementia are at risk of social isolation, and conversational AI agents can potentially support such individuals by reducing their loneliness. In our study, a conversational AI agent, called MindTalker, co-designed with therapists and utilizing the GPT-4 Large Language Model (LLM), was developed to support people with early-stage dementia, allowing them to experience a new type of "social relationship" that could be extended to real life. Eight PwD engaged with MindTalker for one month or even longer, and data was collected from interviews. Our findings emphasized that participants valued the novelty of AI, but sought more consistent, deeper interactions. They desired a personal touch from AI, while stressing the irreplaceable value of human interactions. The findings underscore the complexities of AI engagement dynamics, where participants commented on the artificial nature of AI, highlighting important insights into the future design of conversational AI for this population.

Human behaviour and habits co-evolve with technology, and the metaverse is poised to become a key player in reshaping how we live our everyday life. Given the importance of food in our daily lives, we ask: how will our relationships with food be transformed by the metaverse, and what are the promises and pitfalls of this technology? To answer this, we propose a co-design study that reveals the important elements people value in their daily interactions with food. We then present a speculative catalogue of novel metaverse food experiences, and insights from discussing these ideas with food designers, anthropologists and metaverse experts. Our work aims to provide designers with inspirations for building a metaverse that: provides inclusive opportunities for the future of food; helps re-discover the forgotten or lost knowledge about food; facilitates the exploration, excitement and joy of eating; and reinvigorates the ways that food can soothe and heal.

The acoustic and visual experiences of musicians in the spaces they perform in are complex and organic in nature, entailing a continuous interaction with the environment. With this project, we leverage the power of Virtual Reality (VR) to support musicians in their creative practice by transporting them to novel sonic and visual worlds. For this, we developed a musician-centred VR system, featuring various acoustic and visual virtual environments, VR Rehearse & Perform, based on design requirements gathered with musicians and performance experts. To investigate how VR can be designed to support music-makers in their creative musical practice, we performed iterative tests with 19 musicians followed by semi-structured interviews. Our findings suggest that VR has the potential to support different aspects of the creative musical practice, such as rehearsing, performing and improvising. Our research provides insights and inspirations toward designing musician-centred VR experiences for various musical activities.

The loss of autonomy that comes with being in the care of others has a significant impact on the emotional well-being of people with dementia (PwD). Our research aims to investigate key design factors when creating Virtual Reality (VR) non-pharmacological interventions to improve their emotional wellbeing and enhance their interactions with caregivers. This paper, presents the iterative design and initial evaluation of a VR system aiming to enhance the procedure of admitting VR interventions.

In this paper, we propose VR Rehearse & Perform - a Virtual Reality application for enhancing the rehearsal efforts of performers by providing them access to accurate recreations - both visual and acoustical - of iconic concert venues.

Prolong Grief Disorder (PGD) is a condition in which mourners are stuck in the grief process for a prolonged period and continue to suffer from an intense, mal-adaptive level of grief. Despite the increased popularity of virtual mourning practices, and subsequently the emergence of HCI research in this area, there is little research looking into how continuing bonds maintained digitally promote or impede bereavement adjustment. Through a one-month diary study and in-depth interviews with 17 participants who recently lost their loved ones, we identified four broad mechanisms of how grievers engage in what we called "backstage" grieving (as opposed to bereavement through digital public space like social media). We further discuss how this personal and private grieving is important in maintaining emotional well-being hence avoiding developing PGD, as well as possible design opportunities and challenges for future digital tools to support grieving.

For many disabled people, brain computer interface (BCI) may be the only way to communicate with others and to control things around them. Using motor imagery paradigm, one can decode an individual's intention by using their brainwaves to help them interact with their environment without having to make any physical movement. For decades, machine learning models, trained on features extracted from acquired electroencephalogram (EEG) signals have been used to decode motor imagery activities. This method has several limitations and constraints especially during feature extraction. Large number of channels on the current EEG devices make them hard to use in real-life as they are bulky, uncomfortable to wear, and takes lot of time in preparation. In this paper, we introduce a technique to perform channel selection using convolutional neural network (CNN) and to decode multiple classes of motor imagery intentions from four participants who are amputees. A CNN model trained on EEG data of 64 channels achieved a mean classification accuracy of 99.7% with five classes. Channel selection based on weights extracted from the trained model has been performed with subsequent models trained on eight selected channels achieved a reasonable accuracy of 91.5%. Training the model in time domain and frequency domain was also compared, different window sizes were experimented to test the possibilities of realtime application. Our method of channel selection was then evaluated on a publicly available motor imagery EEG dataset.

Many people with dementia (PWD) residing in long-term care may face barriers in accessing experiences beyond their physical premises; this may be due to location, mobility constraints, legal mental health act restrictions, or offence-related restrictions. In recent years, there have been research interests towards designing non-pharmacological interventions aiming to improve the Quality of Life (QoL) for PWD within long-term care. We explored the use of Virtual Reality (VR) as a tool to provide 360°-video based experiences for individuals with moderate to severe dementia residing in a locked psychiatric hospital. We discuss at depth the appeal of using VR for PWD, and the observed impact of such interaction. We also present the design opportunities, pitfalls, and recommendations for future deployment in healthcare services. This paper demonstrates the potential of VR as a virtual alternative to experiences that may be difficult to reach for PWD residing within locked setting.

The existing evidence base in relation to the feasibility of using Virtual Reality technology systems with individuals living with a dementia appeared limited and was therefore explored. The research was collected and reviewed in terms of the different types of Virtual Reality systems (equipment and levels of immersion) and feasibility of the technology within different stages of demen- tia as well as the methodological limitations. A systematic search of the literature was conducted using the healthcare databases advanced search (Medline, PsychINFO, and EMBASE) and snowballing methods. The participants had a dementia diagnosis and the feasibility of Virtual Reality in terms of its acceptability and practicality was discussed. Only five articles met the eligibility criteria. Four included semi-immersive Virtual Reality with participants in the early stages of dementia. One included fully- immersive Virtual Reality where dementia stage ranged from 'mild' to 'severe'. Based on available demographic information, study participants resided in residential care homes, alone in the community or with their spouse. The existing literature sug- gests that both semi and fully-immersive Virtual Reality technology use can be feasible amongst individuals living within the ear- lier stages of dementia outside of a hospital environment, with it being viewed as a welcomed distraction that increased alert- ness and pleasure. However, Virtual Reality was also found to increase fear and anxiety in one study, raising important ethical implications around the safety of the user. The current evidence-base leaves a predominant gap in Virtual Reality technology system use for people within the moderate to later stages of dementia and those living in a hospital environment.

Brain Computer Interface (BCI) may be the only way to communicate and control for disabled people. Someone's intention can be decoded from their brainwaves during motor imagery action. This can be used to help them control their environment without making any physical movement. To decode someone's intention from brainwaves during motor imagery activities, machine learning models trained on features extracted from the acquired EEG signals have been used. Although the technique has been successful, it has encountered several limitations and difficulties especially during feature extraction. Moreover, many current BCI systems rely on a large number of channels (e.g. 64) to capture spatial information which are necessary during training a machine learning model. In this study, Convolutional Neural Network (CNN) is used to decode five motor imagery intentions from EEG signals obtained from four subjects using 64 channels EEG device. A CNN model trained on raw EEG data managed to achieve a mean classification accuracy of 99.7%. Channel selection based on learned weights extracted from a trained CNN model has been performed with subsequent models trained on only two selected channels with higher weights attained a high accuracy (average of 98%) among three participants out of four.

As a consequence of prolonged muscle contraction, acute pain arises during exercise due to a build-up of noxious biochemicals in and around the muscle. Specific visual cues, e.g., the size of the object in weight lifting exercises, may reduce acute pain experienced during exercise. In this study, we examined how Virtual Reality (VR) can facilitate this "material-weight illusion", influencing perception of task difficulty, which may reduce perceived pain. We found that when vision understated the real weight, the time to exhaustion was 2 minutes longer. Furthermore, participants' heart rate was significantly lower by 5-7 bpm in the understated session. We concluded that visual-proprioceptive information modulated the individual's willingness to continue to exercise for longer, primarily by reducing the intensity of negative perceptions of pain and effort associated with exercise. This result could inform the design of VR aimed at increasing the level of physical activity and thus a healthier lifestyle.

Education plays an important role in helping developing nations reduce poverty and improving quality of life. Ubiquitous and mobile technologies could greatly enhance education in such regions by providing augmented access to learning. This paper presents a three-year iterative study where a ubiquitous sensor based learning platform was designed, developed and tested to support science learning among primary school students in underprivileged Northern Thailand. The platform is built upon the school's existing mobile devices and was expanded to include sensor-based technology. Throughout the iterative design process, observations, interviews and group discussions were carried out with stakeholders. This lead to key reflections and design concepts such as the value of injecting anthropomorphic qualities into the learning device and providing personally and culturally relevant learning experiences through technology. Overall, the results outlined in this paper help contribute to knowledge regarding the design, development and implementation of ubiquitous sensor-based technology to support learning.

In this paper, we explore the feasibility of developing a sensor-driven rehabilitation game for people suffering from dysphagia. This study utilizes the skin-like electronics for unobtrusive, comfortable, continuous recording of surface electromyograms (EMG) during swallowing and use them for driving game-based, user-controlled feedback. The experimental study includes the development and evaluation of a real-time swallow detection algorithm using skin-like sensors and a game-based human-computer interaction. The user evaluations support the ease of use of the skin-like electronics as a motivational tool for people with dysphagia.

Interrelationship between ethnicity, motivation and technology usage is an interesting scope of study as it offers various dimensions to be explored, polished and refined. One of the most interest areas is on the motivational factors for technology usage among the indigenous people from the viewpoints of socio-structural, socioeconomic and socio cultural. This paper present the findings on the motivational factors of technology usage based on the socioeconomic and socio cultural situational study of Orang Asli in Peninsular Malaysia. The study analysis was performed against the theoretical lens of need-based theory of technology use to uncover constructs of needs that can be identified as motivational factors for technology use. From the study, it is found that Orang Asli has a tendency toward holding on to perceived idea of enjoyment and the preservation of culture and benefits delivery as a motivation for them to use the technology. We propose the affect based needs and cultural needs as new constructs for technology use by the indigenous people.

Wristbands have been traditionally designed to track the activities of a single person. However there is an opportunity to utilize the sensing capabilities of wristbands to offer activity tracking services within the domain of team-based sports games. In this paper we demonstrate the design of an activity tracking system capable of detecting the players' activities within a one-to-one basketball game. Relying on the inertial sensors of wristbands and smartphones, the system can capture the shooting attempts of each player and provide statistics about their performance. The system is based on a two- level classification architecture, combining data from both players in the game. We employ a technique for semi-automatic labelling of the ground truth that requires minimum manual input during a training game. Using a single game as a training dataset, and applying the classifier on future games we demonstrate that the system can achieve a good level of accuracy detecting the shooting attempts of both players in the game (precision 91.34%, recall 94.31%).

Diary studies require participants to record entries at the moment of events, but the process often distracts the participants and disrupts the flow of the events. In this work, we explore the notion of delayed reflection for diary studies. Users quickly denote cues of diary events and only reflect on the cues later when they are not busy. To minimize disruptions, we employed a squeeze gesture that is swift and discreet for denoting cues. We investigated the feasibility of delayed reflection and compared it against a conventional digital diary that requires users to reflect immediately at the time of entry. In a weeklong field study, we asked participants to record their daily experiences with both types of diaries. Our results show that users' preference is context-dependent. Delayed reflection is favored for use in contexts when interruptions are deemed inappropriate (e.g. in meetings or lectures) or when the users are mobile (e.g. walking). In contrast, the users prefer immediate reflection when they are alone, such as during leisure and downtime.

In some countries, it is revealed that the ICT usage by indigenous people is possible to be accomplished and utilized to deliver benefits. For the purpose of development and advancement of Orang Asli (one of the indigenous groups in Malaysia) and in support of the national aspirations in Vision 2020, ICT exposure to Orang Asli requires holistic implementation. Therefore, the predominant issue to be discovered comprehensively is about Orang Asli and it is imperative to understand their needs and requirements in terms of ICT acceptance, appropriation, barriers, as well as infrastructure and infostructure issues. In conclusion, we found four main aspects to be considered in research involving Orang Asli's use of ICT and benefit ICT: (i) the influential people, (ii) infrastructure barriers (iii) social development issues, and (iv) motivational factors.

The research reviews the basic elements of sculptures ascertaining the perception of people with dementia and the patterns of their interaction and visual understanding along with tactile engagement.

To provide better education to children from different socio-economic backgrounds, the Thai Government launched the "One Tablet PC Per Child" (OTPC) policy and distributed 800,000 tablet computers to first grade students across the country in 2012. This initiative is an opportunity to study how mobile learning and Internet of Things (IoT) technology can be designed for students in underprivileged areas of northern Thailand. In this position paper, we present a prototype, called OBSY (Observation Learning System) which targets primary science education. OBSY consists of i) a sensor device, developed with low-cost open source singled-board computer Raspberry Pi, housed in a 3D printed case, ii) a mobile device friendly graphical interface displaying visualisations of the sensor data, iii) a self-contained DIY Wi-Fi network which allows the system to operate in an environment with inadequate ICT infrastructure.

The diary method has been adopted for recording participants' behaviours. However, recording diary entries can be difficult or deemed inappropriate in certain situations, like in a social group or in a meeting. In this demo we present SqueezeDiary, a tool that adopts squeeze gestures for users to denote triggers of diary events, and the users reflect on the triggers later when they are not busy (e.g. during lunch). Our application enables delayed reaction, where users can react on their recorded event instances retrospectively during their downtime.

In this demonstration, we showcase SqueezeDiary, a novel mobile diary application that uses squeeze gestures for denoting instances of events. SqueezeDiary consists of a mobile phone and a small squeeze sensor that communicate over a Bluetooth connection. To record an event instance, the user simply squeezes the sensor, and the phone records memory cues for review later. SqueezeDiary provides features for users to swiftly record instances as they continue to live through the experience, and only reflect on the instances during their downtime.

This paper describes a study aimed to understand the use of 3D virtual world (VW) technology to support life engagement for people with dementia in long-term care. Three versions of VW prototypes (reminiscence room, virtual tour and gardening) utilising gestured-base interaction were developed iteratively. These prototypes were tested with older residents (80+) with dementia in care homes and their caregivers. Data collection was based on observations of how the residents and care staff interacted collaboratively with the VW. We discussed in depth the use of VWs in stimulating past memories and how this technology could help enhance their sense of self through various means. We also highlighted key approaches in designing VWs to sustain attention, create ludic experiences and facilitate interaction for older people with dementia.

The museum provides the perfect setting for the convergence of culture, reflection, personal connections, and communication, and many museums supplement these visitor experiences through the use of Human-Computer Interaction (HCI) systems. While there has been past HCI research on various combinations of these four areas, the overall goal of this study is to explore the emotional links museum visitors make while encompassing all four areas through the use of engaging HCI technologies. This paper reports on the results of a study carried out at the Powell-Cotton Museum, a local ethnographic museum located in south-east Kent, UK. Using structured interviews and thematic analysis, visitors' emotional responses to museum artefacts were analysed. Findings suggest that when given the task of providing emotional responses to artefacts, visitors are motivated to find meaningful and personal connections.

The emergence of MMOGs has led to new ways of socializing with friends. Nowadays a good online game is also associated with the pleasure of socializing and interacting with other players. One cannot play a game solitarily in a meaningful sense without interacting with the other players. However, there are still no integrated ways of designing and evaluating the inherent sociability of MMOGs, nor are there methods or guidelines for evaluating social user experiences. Designers of MMOGs are often left to use their intuition and experience, many times leading to design failures. This SIG aims to further the understanding of the challenges relating to the design of the social interactions that users experience, and the way these manifest and are supported in Massively Multi-player Online Games (MMOGs). The goal is to examine the ways that sociability manifests in MMOGs and the way that design affects these manifestations.

The paper looks at how Wiki technologies can be used to facilitate language learning among the youth through game playing as a social activity. Constructionism as related to computer games and language learning are examined. Constructionist theory creates a context of learning in which learners become engaged in collaborative construction of sharable and meaningful artefacts. A case study of narrative construction is investigated further by identifying collaborative activities around game communities that might be able to facilitate language education. A scenario of an educational game community is presented and challenges in the use of such technologies in a game based setting are discussed.

The article presents the academic views of narrative in the interactive environment particularly in computer games. The relationship between stories and games is examined from the perspective of ludology and narratology in order to understand how computer games work as a medium for storytelling. E-Learning software is thus analyzed as computer games and several issues pertaining to the lethargic stage of educational software development are raised. Then, two versions of e-Learning prototypes are demonstrated and discussed.

Computer games provide a good environment for learning. Players learn to play the game without being taught didactically as the learning process takes place naturally in the virtual world. Learning is no longer a process of knowledge transfer from the expert to the novice. Learners need to construct the knowledge themselves by interacting with the environment. It is beneficial to study the theory underpinning computer games: how players learn and respond in the game environment. We elucidate the theories of learning, i.e. behavioural learning theory, cognitive learning theory and motivation theory in the context of computer games. Psychology provides a way to understand the learning that occurs naturally in games and also helps in developing an environment in which the player can learn a particular domain of knowledge extrinsically. By studying the psychology and its relation to computer games, we can understand players more comprehensively, and thus predict their responses. The understanding of psychology offers a framework to developing an educational game that promotes learning while maintaining high player motivation. We also attempt to shed some light on how players learn in computer games based on the theory, and thus infer better techniques in supporting game-based learning.