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 | | | Acoustic Sensing Using Mobile Devices |  | TRAN Ngoc Doan Thu PhD Candidate
School of Computing and Information Systems
Singapore Management University
| Research Area Dissertation Committee Research Advisor Dissertation Committee Member External Member - Fahim KAWSAR, Research Director, Internet of Things Research Bell Laboratories, Nokia (Belgium, Ireland, and UK)
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| | Date 21 November 2024 (Thursday) | Time 4:30pm – 5:30pm | Venue Meeting room 4.4,
Level 4
School of Computing and Information Systems 1,
Singapore Management University,
80 Stamford Road,
Singapore 178902 | Please register by 20 November 2024. We look forward to seeing you at this research seminar. 
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| | ABOUT THE TALK TRAN Ngoc Doan ThuHuman health and performance sensing from physiology to mental health and movement analytics typically rely on invasive and contact sensors or require professional practitioners, limiting their scalability. For example, the gold standard for measuring heart rate is through an electrocardiogram, which requires multiple probes attached to the skin and it to be performed in a hospital setting under the supervision of a trained physiologist. Depression detection often relies on the expertise of psychologists or psychiatrists, while there is a shortage of these professionals in many areas. In the context of swimming, obtaining kinematic feedback from athletes often involves wearing inertial measurement units, which is uncomfortable for the wearers and illegal during a competition. Recent studies have introduced innovative approaches that can sense and analyze human performance on a large scale and in a contactless manner. Nevertheless, each individual approach still faces challenges and trade-offs that need to be addressed. This thesis addresses these challenges through three integrative studies.
The first study introduces a novel approach to contactless heart rate monitoring, overcoming limitations in crowded settings to enable precise tracking of multiple individuals simultaneously. The second study evaluates an app-based system designed for detecting depression in elderly populations, pinpointing key factors linked to geriatric depressive symptoms. Lastly, a proposed drone-based system for non-contact swimming analysis offers real-time feedback on stroke rate and speed via video analysis, potentially revolutionizing training and performance assessment in aquatic sports. | | | ABOUT THE SPEAKER TRAN Ngoc Doan Thu is a PhD candidate at the School of Computing and Information Systems, Singapore Management University. Under the supervision of Professor Rajesh Krishna Balan, her research focuses on scalable and contactless sensing. She is currently working on improving swimmers' performance through a drone-based system and studying the factors influencing the lifestyle of older adults. |
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