Computing and Information Systems - Research Publications

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Author: Kostakos, Vassilis × Author: Tag, Benjamin × End date: 2022 × Start date: 2020 × Type: Journal Article ×

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    Emotion trajectories in smartphone use: Towards recognizing emotion regulation in-the-wild
    Tag, B ; Sarsenbayeva, Z ; Cox, AL ; Wadley, G ; Goncalves, J ; Kostakos, V (ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2022-10)
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    Impact of the global pandemic upon young people's use of technology for emotion regulation
    Tag, B ; van Berkel, N ; Vargo, AW ; Sarsenbayeva, Z ; Colasante, T ; Wadley, G ; Webber, S ; Smith, W ; Koval, P ; Hollenstein, T ; Goncalves, J ; Kostakos, V (ELSEVIER, 2022-05)
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    A System for Computational Assessment of Hand Hygiene Techniques
    Wang, C ; Jiang, W ; Yang, K ; Sarsenbayeva, Z ; Tag, B ; Dingler, T ; Goncalves, J ; Kostakos, V (SPRINGER, 2022-05-06)
    The World Health Organization (WHO) recommends a six-step hand hygiene technique. Although multiple studies have reported that this technique yields inadequate skin coverage outcomes, they have relied on manual labeling that provided low-resolution estimations of skin coverage outcomes. We have developed a computational system to precisely quantify hand hygiene outcomes and provide high-resolution skin coverage visualizations, thereby improving hygiene techniques. We identified frequently untreated areas located at the dorsal side of the hands around the abductor digiti minimi and the first dorsal interosseous. We also estimated that excluding Steps 3, 6R, and 6L from the six-step hand hygiene technique leads to cumulative coverage loss of less than 1%, indicating the potential redundancy of these steps. Our study demonstrates that the six-step hand hygiene technique could be improved to reduce the untreated areas and remove potentially redundant steps. Furthermore, our system can be used to computationally validate new proposed techniques, and help optimise hand hygiene procedures.
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    Inferring Circadian Rhythms of Cognitive Performance in Everyday Life
    Tag, B ; Dingler, T ; Vargo, AW ; Kostakos, V (Institute of Electrical and Electronics Engineers, 2020-01-01)
    Physical, mental, and behavioral processes of most living beings underlie cyclic changes, mainly governed by the day-night cycle. Investigations of these circadian rhythms have traditionally required constrained settings and invasive methods, such as repetitive blood testing and testing in sleep laboratories. Recent developments in pervasive technology, e.g., the proliferation of smartphones in our everyday lives, allow us to develop less intrusive ways to infer circadian rhythmicity in everyday settings. In this article, we present an overview of the current state of research, describe a mobile toolkit for collecting ground truth data on cognitive state fluctuations, and detail the implementation of a wearable system to unobtrusively detect alertness changes in the wild. Understanding and monitoring circadian rhythms will lead to the development of interventions to support mental health, physical health, and will ease the negative consequences of time shifts inflicted by jet lag or shift-work.
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    Measuring Mobility and Room Occupancy in Clinical Settings: System Development and Implementation
    Marini, G ; Tag, B ; Goncalves, J ; Velloso, E ; Jurdak, R ; Capurro, D ; McCarthy, C ; Shearer, W ; Kostakos, V (JMIR PUBLICATIONS, INC, 2020-10-27)
    BACKGROUND: The use of location-based data in clinical settings is often limited to real-time monitoring. In this study, we aim to develop a proximity-based localization system and show how its longitudinal deployment can provide operational insights related to staff and patients' mobility and room occupancy in clinical settings. Such a streamlined data-driven approach can help in increasing the uptime of operating rooms and more broadly provide an improved understanding of facility utilization. OBJECTIVE: The aim of this study is to measure the accuracy of the system and algorithmically calculate measures of mobility and occupancy. METHODS: We developed a Bluetooth low energy, proximity-based localization system and deployed it in a hospital for 30 days. The system recorded the position of 75 people (17 patients and 55 staff) during this period. In addition, we collected ground-truth data and used them to validate system performance and accuracy. A number of analyses were conducted to estimate how people move in the hospital and where they spend their time. RESULTS: Using ground-truth data, we estimated the accuracy of our system to be 96%. Using mobility trace analysis, we generated occupancy rates for different rooms in the hospital occupied by both staff and patients. We were also able to measure how much time, on average, patients spend in different rooms of the hospital. Finally, using unsupervised hierarchical clustering, we showed that the system could differentiate between staff and patients without training. CONCLUSIONS: Analysis of longitudinal, location-based data can offer rich operational insights into hospital efficiency. In particular, they allow quick and consistent assessment of new strategies and protocols and provide a quantitative way to measure their effectiveness.