Understanding and mitigating the impact of Internet demand in everyday life

Digital devices and online services are increasingly embedded within our everyday lives. The growth in usage of these technologies has implications for environmental sustainability due to the energy demand from the underlying Internet infrastructure (e.g. communication networks, data centres). Energy efficiencies in the infrastructure are important, but they are made inconsequential by the sheer growth in the demand for data. We need to transition users’ Internet-connected practices and adapt HumanComputer Interaction (HCI) design in less demanding and more sustainable directions. Yet it’s not clear what the most data demanding devices and online activities are in users’ lives, and how this demand can be intervened with most effectively through HCI design. In this thesis, the issue of Internet demand is explored—uncovering how it is embedded into digital devices, online services and users’ everyday practices. Specifically, I conduct a series of experiments to understand Internet demand on mobile devices and in the home, involving: a large-scale quantitative analysis of 398 mobile devices; and a mixed-methods study involving month-long home router logging and interviews with 20 participants (nine households). Through these studies, I provide an in-depth understanding of how digital activities in users’ lives augment Internet demand (particularly through the practice of watching), and outline the roles for the HCI community and broader stakeholders (policy makers, businesses) in curtailing this demand. I then juxtapose these formative studies with design workshops involving 13 participants; these discover how we can reduce Internet demand in ways that users may accept or even want. From this, I provide specific design recommendations for the HCI community aiming to alleviate the issue of Internet growth for concerns of sustainability, as well as holistically mitigate the negative impacts that digital devices and online services can create in users’ lives

An audience perspective on the second screen phenomenon

Second screen applications are among the latest of the TV industry’s innovations to retain the TV viewer’s attention in a challenging multi-screen environment. These applications can be regarded as an extension of TV content consumed on a TV set towards lightweight portable devices such as tablets. While numerous commercial instances are available internationally and the existing literature on the topic from a technical perspective is extensive, the audience side of this phenomenon has been paid far less attention to. Moreover, in the case of Flanders, the successful commercial implementation of second screen applications remains limited. In this research, we aim to elicit what TV viewers’ expectations and preferences are regarding second screen functionalities. By applying means-end theory and a laddering approach we were able to discern how these preferences subsequently relate to the TV show itself, the consequences for the viewing experience, as well as how second screen applications and usages are expected to fit in the viewer’s everyday life

Coping with Digital Wellbeing in a Multi-Device World

While Digital Self-Control Tools (DSCTs) mainly target smartphones, more effort should be put into evaluating multi-device ecosystems to enhance digital wellbeing as users typically use multiple devices at a time. In this paper, we first review more than 300 DSCTs by demonstrating that the majority of them implements a single-device conceptualization that poorly adapts to multi-device settings. Then, we report on the results from an interview and a sketching exercise (N=20) exploring how users make sense of their multi-device digital wellbeing. Findings show that digital wellbeing issues extend beyond smartphones, with the most problematic behaviors deriving from the simultaneous usage of different devices to perform uncorrelated tasks. While this suggests the need of DSCTs that can adapt to different and multiple devices, our work also highlights the importance of learning how to properly behave with technology, e.g., through educational courses, which may be more effective than any lock-out mechanism

Human Computer Interaction and Emerging Technologies

The INTERACT Conferences are an important platform for researchers and practitioners in the field of human-computer interaction (HCI) to showcase their work. They are organised biennially by the International Federation for Information Processing (IFIP) Technical Committee on Human–Computer Interaction (IFIP TC13), an international committee of 30 member national societies and nine Working Groups. INTERACT is truly international in its spirit and has attracted researchers from several countries and cultures. With an emphasis on inclusiveness, it works to lower the barriers that prevent people in developing countries from participating in conferences. As a multidisciplinary field, HCI requires interaction and discussion among diverse people with different interests and backgrounds. The 17th IFIP TC13 International Conference on Human-Computer Interaction (INTERACT 2019) took place during 2-6 September 2019 in Paphos, Cyprus. The conference was held at the Coral Beach Hotel Resort, and was co-sponsored by the Cyprus University of Technology and Tallinn University, in cooperation with ACM and ACM SIGCHI. This volume contains the Adjunct Proceedings to the 17th INTERACT Conference, comprising a series of selected papers from workshops, the Student Design Consortium and the Doctoral Consortium. The volume follows the INTERACT conference tradition of submitting adjunct papers after the main publication deadline, to be published by a University Press with a connection to the conference itself. In this case, both the Adjunct Proceedings Chair of the conference, Dr Usashi Chatterjee, and the lead Editor of this volume, Dr Fernando Loizides, work at Cardiff University which is the home of Cardiff University Press

Logging Stress and Anxiety Using a Gamified Mobile-based EMA Application, and Emotion Recognition Using a Personalized Machine Learning Approach

According to American Psychological Association (APA) more than 9 in 10 (94 percent) adults believe that stress can contribute to the development of major health problems, such as heart disease, depression, and obesity. Due to the subjective nature of stress, and anxiety, it has been demanding to measure these psychological issues accurately by only relying on objective means. In recent years, researchers have increasingly utilized computer vision techniques and machine learning algorithms to develop scalable and accessible solutions for remote mental health monitoring via web and mobile applications. To further enhance accuracy in the field of digital health and precision diagnostics, there is a need for personalized machine-learning approaches that focus on recognizing mental states based on individual characteristics, rather than relying solely on general-purpose solutions. This thesis focuses on conducting experiments aimed at recognizing and assessing levels of stress and anxiety in participants. In the initial phase of the study, a mobile application with broad applicability (compatible with both Android and iPhone platforms) is introduced (we called it STAND). This application serves the purpose of Ecological Momentary Assessment (EMA). Participants receive daily notifications through this smartphone-based app, which redirects them to a screen consisting of three components. These components include a question that prompts participants to indicate their current levels of stress and anxiety, a rating scale ranging from 1 to 10 for quantifying their response, and the ability to capture a selfie. The responses to the stress and anxiety questions, along with the corresponding selfie photographs, are then analyzed on an individual basis. This analysis focuses on exploring the relationships between self-reported stress and anxiety levels and potential facial expressions indicative of stress and anxiety, eye features such as pupil size variation and eye closure, and specific action units (AUs) observed in the frames over time. In addition to its primary functions, the mobile app also gathers sensor data, including accelerometer and gyroscope readings, on a daily basis. This data holds potential for further analysis related to stress and anxiety. Furthermore, apart from capturing selfie photographs, participants have the option to upload video recordings of themselves while engaging in two neuropsychological games. These recorded videos are then subjected to analysis in order to extract pertinent features that can be utilized for binary classification of stress and anxiety (i.e., stress and anxiety recognition). The participants that will be selected for this phase are students aged between 18 and 38, who have received recent clinical diagnoses indicating specific stress and anxiety levels. In order to enhance user engagement in the intervention, gamified elements - an emerging trend to influence user behavior and lifestyle - has been utilized. Incorporating gamified elements into non-game contexts (e.g., health-related) has gained overwhelming popularity during the last few years which has made the interventions more delightful, engaging, and motivating. In the subsequent phase of this research, we conducted an AI experiment employing a personalized machine learning approach to perform emotion recognition on an established dataset called Emognition. This experiment served as a simulation of the future analysis that will be conducted as part of a more comprehensive study focusing on stress and anxiety recognition. The outcomes of the emotion recognition experiment in this study highlight the effectiveness of personalized machine learning techniques and bear significance for the development of future diagnostic endeavors. For training purposes, we selected three models, namely KNN, Random Forest, and MLP. The preliminary performance accuracy results for the experiment were 93%, 95%, and 87% respectively for these models

Establishing Design Principles for Augmented Reality for Older Adults

Augmented Reality (AR) is growing rapidly and becoming a more mature and robust technology, which combines virtual information with the real environment in real-time. This becomes significant in ensuring the acceptance and success of Augmented Reality systems. With the growing number of older mobile phone users, evidence shows the possible trends associated with using AR systems to support older adults in terms of transportation, home activities, rehabilitation training and entertainment. However, there is a lack of research on a theoretical framework or AR design principles that could support designers when developing suitable AR applications for specific groups (e.g. older adults). This PhD research mainly focuses on the possibility of developing and applying AR design principles to provide various possible design alternatives in order to address the relevant AR-related issues focusing on older adults. This research firstly identified the architecture of Augmented Reality to understand the definition of AR using a range of previous AR examples. Secondly, AR design principles (version 1) were identified after describing the AR features and analysing the AR design recommendations. Thirdly, this research refined the AR design principles (version 2) by conducting two half-day focus groups with AR prototypes and related scenarios for older adults. The final version of the AR design principles (version 3) for older adults was established. These are: Instantaneous Augmentation, Layer-focus Augmentation, Modality-focus Augmentation, Accurate Augmentation and Hidden Reality. Ultimately, all of these design principles were applied to AR applications and examined in practice using two focus groups. Additionally, as part of the process of AR principle development, a number of AR issues were identified and categorised in terms of User, Device, Augmentation, Real Content, Interaction and Physical World, based on the pre-established AR architecture. These AR issues and design principles may help AR designers to explore quality design alternatives, which could potentially benefit older adults

CreaTable Content and Tangible Interaction in Aphasia

Multimedia digital content (combining pictures, text and music) is ubiquitous. The process of creating such content using existing tools typically requires complex, language-laden interactions which pose a challenge for users with aphasia (a language impairment following brain injury). Tangible interactions offer a potential means to address this challenge, however, there has been little work exploring their potential for this purpose. In this paper, we present CreaTable – a platform that enables us to explore tangible interaction as a means of supporting digital content creation for people with aphasia. We report details of the co-design of CreaTable and findings from a digital creativity workshop. Workshop findings indicated that CreaTable enabled people with aphasia to create something they would not otherwise have been able to. We report how users’ aphasia profiles affected their experience, describe tensions in collaborative content creation and provide insight into more accessible content creation using tangibles

Exploitation of multiplayer interaction and development of virtual puppetry storytelling using gesture control and stereoscopic devices

With the rapid development of human-computer interaction technologies, the new media generation demands novel learning experiences with natural interaction and immersive experience. Considering that digital storytelling is a powerful pedagogical tool for young children, in this paper, we design an immersive storytelling environment that allows multiple players to use naturally interactive hand gestures to manipulate virtual puppetry for assisting narration. A set of multimodal interaction techniques is presented for a hybrid user interface that integrates existing 3D visualization and interaction devices including head-mounted displays and depth motion sensor. In this system, the young players could intuitively use hand gestures to manipulate virtual puppets to perform a story and interact with props in a virtual stereoscopic environment. We have conducted a user experiment with four young children for pedagogical evaluation, as well as system acceptability and interactivity evaluation by postgraduate students. The results show that our framework has great potential to stimulate learning abilities of young children through collaboration tasks. The stereoscopic head-mounted display outperformed the traditional monoscopic display in a comparison between the two