ORCID Profile
0000-0001-5310-0943
Current Organisation
Deakin University
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Publisher: IEEE
Date: 05-2018
Publisher: JMIR Publications Inc.
Date: 29-11-2022
DOI: 10.2196/33952
Abstract: In 2022, an estimated 1.105 billion people used smart wearables and 31 million used Fitbit devices worldwide. Although there is growing evidence for the use of smart wearables to benefit physical health, more research is required on the feasibility of using these devices for mental health and well-being. In studies focusing on emotion recognition, emotions are often inferred and dependent on external cues, which may not be representative of true emotional states. The aim of this study was to evaluate the feasibility and acceptability of using consumer-grade activity trackers for apps in the remote mental health monitoring of older aged people. Older adults were recruited using criterion s ling. Participants were provided an activity tracker (Fitbit Alta HR) and completed weekly online questionnaires, including the Geriatric Depression Scale, for 4 weeks. Before and after the study period, semistructured qualitative interviews were conducted to provide insight into the acceptance and feasibility of performing the protocol over a 4-week period. Interview transcripts were analyzed using a hybrid inductive-deductive thematic analysis. In total, 12 participants enrolled in the study, and 9 returned for interviews after the study period. Participants had positive attitudes toward being remotely monitored, with 78% (7/9) of participants experiencing no inconvenience throughout the study period. Moreover, 67% (6/9) were interested in trialing our prototype when it is implemented. Participants stated they would feel more comfortable if mental well-being was being monitored by carers remotely. Fitbit-like devices were an unobtrusive and convenient tool to collect physiological user data. Future research should integrate physiological user inputs to differentiate and predict depressive tendencies in users.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
Publisher: Atlantis Press
Date: 2020
Publisher: ACM
Date: 29-11-2018
Publisher: IEEE
Date: 08-2015
Publisher: ACM
Date: 02-12-2020
Publisher: IEEE
Date: 08-2020
Publisher: IEEE
Date: 06-2012
Publisher: IEEE
Date: 08-2015
Publisher: ACM
Date: 05-10-2015
Publisher: IEEE
Date: 04-08-2021
Publisher: Association for Computing Machinery (ACM)
Date: 08-2014
Abstract: In digital games, the map (sometimes referred to as the level ) is the virtual environment that outlines the boundaries of play, aids in establishing rule systems, and supports the narrative. It also directly influences the challenges that a player will experience and the pace of gameplay, a property that has previously been linked to a player's enjoyment of a game [1]. In most industry leading games, creating maps is a lengthy manual process conducted by highly trained teams of designers. However, for many decades procedural content generation (PCG) techniques have posed as an alternative to provide players with a larger range of experiences than would normally be possible. In recent years, PCG has even been proposed as a means of tailoring game content to meet the preferences and skills of a specific player, in what has been termed Experience-driven PCG (EDPCG) [2].
Publisher: ACM
Date: 17-10-2019
Publisher: IEEE
Date: 06-2010
Publisher: ACM
Date: 15-10-2016
Publisher: IEEE
Date: 28-06-2021
Publisher: JMIR Publications Inc.
Date: 30-09-2021
Abstract: orldwide, in 2021, 929 million people use smart wearables and 31 million use Fitbit devices. While there is growing research on using smart wearables to benefit physical health, more research is required on the application and feasibility of using these devices for mental health and wellbeing. In studies focusing on emotion recognition, inference is often dependent on external cues, which may not always be representative of genuine inner emotion. he aim of this study was to identify the facilitators and barriers of utilizing consumer-grade activity trackers for applications in remote mental health monitoring of older aged persons. articipants, aged ≥65, were recruited using criterion s ling. Participants were provided an activity tracker (Fitbit Alta HR) and completed weekly online questionnaires (Geriatric Depression Scale), and self-report mood questionnaires. We conducted semi-structured pre-post qualitative interviews with participants to gain insight on the facilitators and barriers of the procedure. Interview transcripts were analyzed using a hybrid inductive-deductive thematic analysis. welve participants enrolled in the study, with 9 returning for the post-procedure interviews. Participants were positive about the procedure with 77.78% (7/9) participants finding it feasible, having experienced no inconvenience through the 4-week procedure period. 66.67% (6/9) participants were interested in the full implementation of our prototype, stating that they would feel more at ease knowing that their mental wellbeing was being monitored by their carers remotely. itbit-like devices are an unobtrusive tool to collect user data without being disruptive or inconvenient to the user. Future research should integrate physiological user inputs to differentiate and predict depressive tendencies in users.
Publisher: IEEE
Date: 08-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2020
Publisher: IEEE
Date: 08-2020
Publisher: IEEE
Date: 08-2017
Publisher: IEEE
Date: 08-2019
Publisher: IEEE
Date: 06-2013
Publisher: Elsevier BV
Date: 12-2020
Publisher: ACM
Date: 29-01-2018
Publisher: Association for Computing Machinery (ACM)
Date: 22-01-2020
DOI: 10.1145/3361524
Abstract: Theme parks visits can be very playful events for families, however, waiting in the ride’s queues can often be the cause of great frustration. We developed a novel augmented reality game to be played in the theme park’s queue, and an in-the-wild study with X participants using log data and interviews demonstrated that every minute playing was perceived to the same extent of about 5 minutes of not playing the game. We articulate a design space for researchers and strategies for game designers aiming to reduce perceived waiting time in queues. With our work, we hope to extend how we use games in everyday life to make our lives more playful.
Publisher: F1000 Research Ltd
Date: 24-01-2022
DOI: 10.12688/WELLCOMEOPENRES.17441.1
Abstract: Background: Adolescence is a sensitive period for the onset of mental health disorders. Effective, easy-to-disseminate, scalable prevention and early interventions are urgently needed. Affective control has been proposed as a potential target mechanism. Training affective control has been shown to reduce mental health symptoms and improve emotion regulation. However, uptake and adherence to such training by adolescents has been low. Thus, the current study aims to receive end user (i.e., adolescents) feedback on a prototype of a novel app-based gamified affective control training program, the Social Brain Train. Methods: The proposed study aims to recruit participants aged 13-16 years old ( N = 20) to provide user feedback on the Social Brain Train app. The first group of participants ( n = 5) will complete an online questionnaire assessing demographics, symptoms of depression and anxiety, social rejection sensitivity and attitudes toward the malleability of cognition and mental health. They will complete two tasks assessing cognitive capacity and interpretation bias. Participants will be then be invited to an online group workshop, where they will be introduced to the app. They will train on the app for three days, and following app usage, participants will complete the aforementioned measures again, as well as provide ratings on app content, and complete a semi-structured interview to obtain in-depth user feedback, which will be used to inform modifications to the app. Following these modifications, a second group of participants ( n = 15) will follow the same procedure, except they will train on the app for 14 days. Feedback from both groups of participants will be used to inform the final design. Conclusions: By including young people in the design of the Social Brain Train app, the proposed study will help us to develop a novel mental health intervention that young people find engaging, acceptable, and easy-to-use
Publisher: ACM
Date: 29-01-2018
Publisher: ACM
Date: 12-07-2011
Publisher: IEEE
Date: 09-2016
Publisher: Frontiers Media SA
Date: 06-08-2021
DOI: 10.3389/FRVIR.2021.630731
Abstract: A cluster of research in Affective Computing suggests that it is possible to infer some characteristics of users’ affective states by analyzing their electrophysiological activity in real-time. However, it is not clear how to use the information extracted from electrophysiological signals to create visual representations of the affective states of Virtual Reality (VR) users. Visualization of users’ affective states in VR can lead to biofeedback therapies for mental health care. Understanding how to visualize affective states in VR requires an interdisciplinary approach that integrates psychology, electrophysiology, and audio-visual design. Therefore, this review aims to integrate previous studies from these fields to understand how to develop virtual environments that can automatically create visual representations of users’ affective states. The manuscript addresses this challenge in four sections: First, theories related to emotion and affect are summarized. Second, evidence suggesting that visual and sound cues tend to be associated with affective states are discussed. Third, some of the available methods for assessing affect are described. The fourth and final section contains five practical considerations for the development of virtual reality environments for affect visualization.
Start Date: 2020
End Date: 2023
Funder: National Health and Medical Research Council
View Funded ActivityStart Date: 2022
End Date: 2023
Funder: University of Technology Sydney
View Funded Activity