Pac-many: Movement behavior when playing collaborative and competitive games on large displays

Peer reviewe

Quantifying the Effects of Situationally-Induced Impairments and Disabilities on Mobile Interaction

© 2020 Zhanna SarsenbayevaSituationally-Induced Impairments and Disabilities (SIIDs), also known as situational impairments, have been shown to negatively affect mobile interaction. This is a consequence of the fact that smartphones have become an indispensable part of our everyday life, and are used under various situations, contexts, and environments. While some situational impairments have received more attention from the research community (e.g., walking-, encumbrance-based SIIDs), some remain underexplored. In addition, research conducted on SIIDs has typically followed an ad-hoc approach, with studies aimed at investigating the impact of a particular SIID on a particular task. Conversely, this thesis systematically quantifies the effects of a range of SIIDs: ambient noise, stress, and dim ambient light on mobile interaction. These findings then enable us to draw baseline comparisons between the effects of these SIIDs on mobile interaction. Furthermore, in a case study this thesis focuses on cold-induced SIIDs, and proposes a sensing mechanism to detect and respond to the onset of such effects. Our contribution to Human-Computer Interaction (HCI) and UbiComp research is to enhance our understanding of the impact of SIIDs on mobile interaction. This knowledge is crucial to enable the development of smarter ubiquitous technology that can detect SIIDs and adapt mobile device interfaces accordingly with the purpose of improving the user experience for people of all abilities

The Methodology of Studying Fairness Perceptions in Artificial Intelligence: Contrasting CHI and FAccT

Supplementary files for the paper 'The Methodology of Studying Fairness Perceptions in Artificial Intelligence: Contrasting CHI and FAccT', to appear in the International Journal of Human-Computer Studies

Impact of Mood Changes on Application Selection

Users of quantified self applications habitually log and track personal information, such as mood. Attempts to automate the procedure of logging mood have been made, but applications themselves rarely provide insights into the user’s mental well-being. In this paper we explore data from two small scale studies related to mobile device usage and mood tracking. We analyse associations between user’s mood throughout the day and the use of smartphone applications from different categories. Our analysis provides insights into the user’s behaviour based on their device usage. Theseinsights mean that QS applications can independently use simple analysis tools to provide similar insights for the user

Application of miniaturized near-infrared spectroscopy in pharmaceutical identification

NIRS is a spectroscopic method that propagates near-infrared waves through objects and measures the absorbance by diffuse reflection, users could analyze the composition information of objects based on that. The technology has fast speed and non-destructive analysis features with relatively simple requirements for operators, making it very friendly to non-expert users. Traditional NIRS scanners used in research laboratories are large and expensive, while recently more and more affordable smaller NIRS scanners are appearing, which attract more end-users to buy and use. Besides, pairing the technology with mobile devices (smartphones, tablets, etc.) could get rid of other professional operation problems, and bring much more possibilities to non-expert users in realistic scenarios. We will explore one such use case in this paper with the extension of work by (Klakegg et al., 2018), namely Smart Pillbox for elderly care. We develop a prototype solution consisting of a hardware-software assistance to support non-expert users

A Review on Mood Assessment Using Smartphones

Due to their abundance of sensors, today’s smartphones can act as a scientific tool to collect contextual information on users’ emotional, social, and physical behaviour. With the continuously growing amount of data that can be unobtrusively extracted from smartphones, mood-tracking and inference methods have become more feasible. However, this does raise critical implications for end-users, including accessibility and privacy. Following a structured selection process, we reviewed 32 papers from the ACM Digital Library on mood inference and tracking using smartphones. We conducted an in-depth analysis of used sensors, platform and accessibility, study designs, privacy, self-reporting methods, and accuracy. Based on our analysis, we provide a detailed discussion of the opportunities for research and practice that arise from our findings and outline recommendations for future research within the area of smartphone-based mood tracking and inference.</p

Electronic Monitoring Systems for Hand Hygiene:Systematic Review of Technology

Background: Hand hygiene is one of the most effective ways of preventing health care–associated infections and reducing their transmission. Owing to recent advances in sensing technologies, electronic hand hygiene monitoring systems have been integrated into the daily routines of health care workers to measure their hand hygiene compliance and quality. Objective: This review aims to summarize the latest technologies adopted in electronic hand hygiene monitoring systems and discuss the capabilities and limitations of these systems. Methods: A systematic search of PubMed, ACM Digital Library, and IEEE Xplore Digital Library was performed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were initially screened and assessed independently by the 2 authors, and disagreements between them were further summarized and resolved by discussion with the senior author. Results: In total, 1035 publications were retrieved by the search queries; of the 1035 papers, 89 (8.60%) fulfilled the eligibility criteria and were retained for review. In summary, 73 studies used electronic monitoring systems to monitor hand hygiene compliance, including application-assisted direct observation (5/73, 7%), camera-assisted observation (10/73, 14%), sensor-assisted observation (29/73, 40%), and real-time locating system (32/73, 44%). A total of 21 studies evaluated hand hygiene quality, consisting of compliance with the World Health Organization 6-step hand hygiene techniques (14/21, 67%) and surface coverage or illumination reduction of fluorescent substances (7/21, 33%). Conclusions: Electronic hand hygiene monitoring systems face issues of accuracy, data integration, privacy and confidentiality, usability, associated costs, and infrastructure improvements. Moreover, this review found that standardized measurement tools to evaluate system performance are lacking; thus, future research is needed to establish standardized metrics to measure system performance differences among electronic hand hygiene monitoring systems. Furthermore, with sensing technologies and algorithms continually advancing, more research is needed on their implementation to improve system performance and address other hand hygiene–related issues