1,721,118 research outputs found
Analyzing the factors influencing the successful design and uptake of interactive systems to support social networks in urban neighborhoods
No full textIn urban residential environments in Australia and other developed countries, Internet access is on the verge of becoming a ubiquitous utility like gas or electricity. From an urban sociology and community informatics perspective, this article discusses new emerging social formations of urban residents that are based on networked individualism and the potential of Internet-based systems to support them. It proposes that one of the main reasons for the disappearance or nonexistence of urban residential communities is a lack of appropriate opportunities and instruments to encourage and support local interaction in urban neighborhoods. The article challenges the view that a mere reappropriation of applications used to support dispersed virtual communities is adequate to meet the place and proximity-based design requirements that community networks in urban neighborhoods pose. It argues that the key factors influencing the successful design and uptake of interactive systems to support social networks in urban neighborhoods include the swarming social behavior of urban dwellers; the dynamics of their existing communicative ecology; and the serendipitous, voluntary, and place-based quality of interaction between residents on the basis of choice, like-mindedness, mutual interest and support needs. Drawing on an analysis of these factors, the conceptual design framework of a prototype system — the urban tribe incubator — is presented
Investigation of Mobile Games for Cognitive Assessment and Screening with a Focus on Touch-based and Motion Features
Full text linkEarly detection of cognitive decline is important for timely intervention and treatment strategies to prevent further deterioration or development of more severe forms of cognitive dysfunction. Therefore, many tests have been developed for screening and monitoring changes in cognitive status. However, these existing assessment and screening tools are not designed for self-administration without a trained examiner. Moreover, the lack of multiple variations of these paper-based measures and repeated exposure to such tests could reduce their sensitivity to detect cognitive changes due to practice effects. These limitations pose clinical challenges to early identification of cognitive deficits and monitoring of longitudinal changes in cognitive function, especially in resource-limited settings. To this end, a number of studies have adopted mobile technology and gamification to facilitate remote and self-administered cognitive assessment and screening in a less effortful and engaging manner. Despite this, existing literature has so far only examined the feasibility of using gameplay performance as a means for cognitive assessment. There has not been any attempt to explore gameplay behaviours as revealed through patterns of touch interactions and device motions as indicative features for cognitive evaluation. Therefore the aim of this thesis is to investigate the use of touch and motions features in game-based cognitive assessment and screening. This is achieved through two studies.
The first study was carried out to examine the links between cognitive abilities and underlying patterns of user-game interaction with a focus on touch gestures and device motions. 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 casual mobile games in which user-game interaction data were passively collected. The results from bivariate analysis indicated that increases in swipe length and swipe speed, in the game context, were significantly correlated with declines in response inhibition ability but increased performance on attention. However, it remained unclear whether the device motion features alone could be used to identify cognitive ability as the results provide only weak evidence for relationships between cognitive performance and the underlying device motion patterns while playing the games.
In the second study, we evaluated the potential use of these behavioural features and mobile games as a potential screening tool for clinical conditions with cognitive impairment. Alcohol-related brain damage (ARBD) is often found to be associated with deficits in multiple cognitive functions in patients with alcohol dependence, which is the focus of this thesis. Based on findings from the preliminary study, the second experimental study was carried out to investigate the feasibility of using such user-game interaction patterns on mobile games to develop an automated screening tool for alcohol-dependent patients. The classification performance of various supervised learning algorithms was evaluated on data collected from 40 patients and 40 age-matched healthy adults. The results showed that patients with alcohol dependence could 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 findings provide 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 method could be used as a novel strategy to promote self-screening, especially outside of clinical settings. The findings from this thesis were also applied to guidelines to aid researchers in the game interaction design to capitalise on the use of touch and device motion features with regard to cognitive assessment and screening
Investigating the Generalisability of Machine Learning Algorithms for Classifying Mental Illnesses in Low- and Middle-Income Countries Using Multimodal Data from Smartphones and Social Media
Full text linkMental health disorders, particularly neurodevelopmental and behavioral conditions, are a major health concern globally, with high prevalence rates in low- to middle-income countries like India. Access to mental health care is often limited in these countries due to factors such as poor health infrastructure, lack of skilled mental health workers, and social stigma. As a result, many patients fail to receive timely intervention, which can worsen their conditions and increase challenges in managing mental health over time. The widespread use of smartphones and social media presents an opportunity to address these challenges. These digital platforms generate vast amounts of data on daily activity, social interaction, and online behavior, which can provide valuable information about individuals' mental health. The purpose of this study is to investigate how such digital information can be harnessed to classify mental disorders, with a particular focus on ADHD and eating disorders, especially in regions where traditional healthcare services are scarce or difficult to access.
This PhD study investigates methodologies to analyze and detect patterns associated with a range of mental and neurodevelopmental disorders using both social media and smartphone sensor data. The first study uses machine learning algorithms like CNN and Word2Vec to classify mental health conditions including anxiety, autism, schizophrenia, depression, bipolar disorder, and borderline personality disorder based on information gathered from social media platforms such as Twitter and Reddit. Large datasets were collected from Reddit and Twitter and analyzed to develop models capable of identifying patterns associated with these disorders. The results showed consistent model performance across platforms, with positive evaluation scores such as precision, recall, and F1-score validating the effectiveness of the classification methods.
The second study addresses the shortcomings of lab-based research in assessing neurodevelopmental disorders like ADHD by using smartphone sensor data for a more objective assessment. Accelerometer, location tracking, application usage, and smartphone interaction data (e.g., keyboard and touch gestures) were collected from 43 participants, 21 with ADHD and 22 without. Analysis revealed significant differences in attention-related activity patterns between the groups, with variations in attentiveness and interaction patterns serving as strong indicators of ADHD. These findings suggest that smartphone sensor data can effectively classify ADHD-related behaviors and provide insights into attentiveness patterns. The third study focuses on the assessing patterns associated with of eating disorders using smartphone sensor data. Accelerometer and location information, along with application use, keyboard interactions, and touch movements, were collected from 45 participants: those without eating disorders, those with moderate disorders, and those with severe disorders. Statistical analysis revealed unique behavioral patterns, particularly during meal sessions, such as longer periods of screen inactivity and abnormal touch movements in individuals with severe eating disorders. Machine learning models were able to detect these patterns, accurately classifying eating disorders by severity. This study also explored practical and methodological challenges in smartphone-based mental health research in low- and middle-income countries, including participant recruitment amid limited smartphone availability, variability in device performance and connectivity, and cultural and geographic differences in digital behavior and expression of mental health. Strategies such as adaptive data collection methods and culturally sensitive study designs were discussed to improve the reliability, accessibility, and impact of smartphone-based mental health research in resource-scarce environments.
This PhD study demonstrates that digital data from social media and smartphones can aid in the classification of neurodevelopmental and mental disorders, with particular emphasis on ADHD and eating disorders. These methodologies offer non-invasive, affordable, and scalable means of detecting health-related patterns. The findings indicate that digital data can play a key role in improving early identification and supporting interventions, especially in resource-limited settings where access to mental health professionals and clinical resources is constrained
Emotional Spaces in Virtual Reality: Applications for Healthcare & Wellbeing
Full text linkDespite the abundance of research that supports the efficacy of Virtual Reality (VR) in applications for healthcare and wellbeing, the process of designing VR as an emotional space that fosters the appropriate therapeutic milieu is rarely discussed. Furthermore, current approaches for VR design tend to be lone one-off controlled experiments, rather than extensions to advance knowledge of best practices that considers the real-world deployment contexts. In this research thesis, a series of studies were carried out to investigate the effects of emotional experiences in VR within healthcare contexts, and how to design emotional spaces in VR, in a way that meets the needs of key stakeholders such as clinicians, patients and the deployment setting. First, the psychological and physiological effects of VR was explored. This study investigated the emotional effects of engaging in 360-degree video-based experiences in VR and the use of eye-tracking in VR to predict emotional elicitation. The study also explored the potential of eye-tracking in VR as a tool for emotional assessment in healthcare and wellbeing. The second study investigated the use of VR as an emotional space in a healthcare setting by presenting VR as a non-pharmacological intervention for people living with moderate to severe dementia residing in a locked psychiatric hospital. The study concluded that by "bringing the outside in" VR was cognitively stimulating, sustained attention, promoted wellbeing among the patients, reduced behaviour that challenges, and offered a unique medium for caregivers and patients to build therapeutic rapport. Finally, the last study analysed the co-design, iterative prototyping and evaluation of four user-centred psychological, cognitive and behavioural VR interventions. This study aimed to understand the design elements of effective, meaningful and enriched VR interventions. The findings are drawn in this thesis, and the implications of these findings extend the theoretical and practical knowledge in designing emotional spaces within VR in a way that fosters the appropriate therapeutic medium for healthcare and wellbeing contexts
Physiological Sensing for Measurement of Eating Function, and Detection of Food and Characteristics of Eating
Full text linkThe Design of Virtual Reality Applications for Psychological Interventions
Full text linkVirtual Reality is an emerging technology with a variety of potential benefits in research, assessment and treatment. The ability to create and control the dynamic 3-dimensional environments within which behavioural responses can be measured and recorded, allows this technology to offer ways of psychological assessment that traditional methods may not be capable of providing. Although plenty of research has been carried out to explore the use of VR in psychology, little was done to further the understanding of the processes of VR design. Considering the potential possibilities of VR in the area of psychological treatments, it is necessary to investigate how VR applications can be designed to meet the needs of psychologists, researchers and end-users. To achieve this, the use of co-design approach is recommended. It is also important to provide stakeholders with the co-design pipeline and technical guidelines on how to create these applications.In the first stage of the research, a series of case studies for pain management and anxiety disorders were carried out to investigate the design opportunities and challenges in the development of mobile VR psychotherapy applications. This includes the description of the development and design process of VR applications, as well as the tools and techniques used for it. Specifically, a mobile VR application for pain management research, where I took part as a designer/developer, and another mobile VR application for anxiety disorders were developed. A study was conducted to examine the innovative use of mobile VR technology to deliver a form of cognitive bias training for anxiety disorder. Forty-two students high in trait anxiety completed one session of either virtual reality cognitive bias modification of interpretations training (VR-CBM-I) or standard CBM-I training for performance anxiety. Overall, the results showed that based on post-training,the VR-CMB-I training reduced perceived anxiety significantly more than the standard CBM-I training. Moreover, the increase in anxiety response in the VRCMB-I training condition after the stressor task was also significantly less when compared to the standard training. Thus, there was a significant increase in positive interpretations and a significant decrease in negative interpretations in both conditions after the training. The results from this stage allowed to identify some key co-design phases as well as techniques and components needed for a successful mobile VR application development. In the second stage of the research, the more advanced system was developed. The use of Multi-User Virtual Reality (MUVR) as a tool to offer effective intervention for representative users at high-risk of eating disorder (ED) was explored. Fourteen females deemed at high risk of ED completed one session of either MUVR intervention based on Acceptance and Commitment Therapy (ACT) or MUVR intervention based on Play Therapy (PT). The use of VR for remote psychotherapy was explored, and the impact of such intervention on both therapists and participants was observed. In addition, the design opportunities, pitfalls, and recommendations for future deployment in psychological interventions were presented. The findings from this thesis help extend the knowledge regarding the design, development and implementation of VR applications in psychotherapy. Contributions within the study can help psychologists, developers and researchers in identifying how these VR applications can be best designed and applied for psychological treatments. Additionally, these findings were formed into a set of3 guidelines to aid developers and psychologists in creating better VR applications to facilitate psychological interventions
Investigating a sensor-based educational platform to facilitate science-based learning activities for children in an underprivileged context
No full textEducation plays an important role in helping developing countries reduce poverty and improve the quality of life. Ubiquitous and mobile technologies could greatly enhance education in such regions by providing enhanced access to learning. However, there is limited empirical evidence on the effectiveness of mobile technologies use by younger learners in the developing nations.
This research presents a long-term 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. Firstly, a user context study was carried out to examine how the students and teachers currently use tablet computers in the classroom and to determine how well this tool supports learning. Observations, interviews and questionnaires were carried out to identify how a tablet-based learning platform can be best designed to facilitate education for school children in underdeveloped areas. Based on the findings from the preliminary study, a sensor-based Internet of Educational Things (IoET) platform named OBSY was developed which functions as a learning hub where students can access sensor data through a wireless connection by using their mobile tablet computers. In order to assess the effectiveness of the platform, a final evaluation study was carried out through observations and interviews. Students' learning engagement and knowledge outcome were measured in an experimental study.
The findings helped to extend our knowledge regarding the design, development and implementation throughout the thesis. Contributions within the study can help educators, developers and researchers in identifying how such a technology can be best designed and applied for young students in underprivileged regions. For instance, adding the value of playfulness qualities into the learning device and providing personally and culturally relevant learning experiences through technology
ENHANCING USERS’ EXPERIENCE WITH SMART MOBILE TECHNOLOGY
Full text linkThe aim of this thesis is to investigate mobile guides for use with smartphones. Mobile guides have been successfully used to provide information, personalisation and navigation for the user. The researcher also wanted to ascertain how and in what ways mobile guides can enhance users' experience.
This research involved designing and developing web based applications to run on smartphones. Four studies were conducted, two of which involved testing of the particular application. The applications tested were a museum mobile guide application and a university mobile guide mapping application. Initial testing examined the prototype work for the ‘Chronology of His Majesty Sultan Haji Hassanal Bolkiah’ application. The results were used to assess the potential of using similar mobile guides in Brunei Darussalam’s museums. The second study involved testing of the ‘Kent LiveMap’ application for use at the University of Kent. Students at the university tested this mapping application, which uses crowdsourcing of information to provide live data. The results were promising and indicate that users' experience was enhanced when using the application.
Overall results from testing and using the two applications that were developed as part of this thesis show that mobile guides have the potential to be implemented in Brunei Darussalam’s museums and on campus at the University of Kent. However, modifications to both applications are required to fulfil their potential and take them beyond the prototype stage in order to be fully functioning and commercially viable
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