AI Micro Motion Sensors for Screening Sarcopenia-prone Elderly Subjects
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
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| Title of host publication | Proceedings of the 3rd IEEE International Conference on Micro/Nano Sensors for AI, Healthcare and Robotics |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. |
| Pages | 107-111 |
| ISBN (electronic) | 9798350375213 |
| ISBN (print) | 979-8-3503-7522-0 |
| Publication status | Published - 2024 |
Publication series
| Name | Proceedings of the IEEE International Conference on Micro/Nano Sensors for AI, Healthcare and Robotics, NSENS |
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Conference
| Title | 3rd IEEE International Conference on Micro/Nano Sensors for AI, Healthcare and Robotics (IEEE-NSENS 2024) |
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| Location | Shenzhen Convention and Exhibition Center |
| Place | China |
| City | Shenzhen |
| Period | 2 - 3 March 2024 |
Link(s)
Abstract
Sarcopenia, a condition characterized by age-related muscle mass and function decline, poses significant risks including falls, fractures, gait disorders, and even mortality. This study aimed to develop an AI motion sensor system utilizing micro inertial measurement units (μIMUs) to screen sarcopeniaprone elderly subjects. Subjects within the age range of 65-84 years performed single sit-To-stand and 5-Time chair stand while wearing two μIMUs. K-Nearest-Neighbours (KNN) algorithms were employed to collect and analyze motion data from the tests. The 53 subjects were categorized as either healthy or sarcopeniaprone, with the sarcopenia-prone group further classified into three levels based on their condition severity. The highest classification accuracy achieved was 94.64% for distinguishing between healthy and sarcopenia-prone subjects, and 90.44% for differentiating various sarcopenia-prone risk levels. This AI motion sensor system demonstrates potential as a cost-effective and accessible approach for large-scale sarcopenia screening. Further refinement of this method could enable remote health monitoring and telerehabilitation programs catering to older adults. © 2024 IEEE.
Citation Format(s)
AI Micro Motion Sensors for Screening Sarcopenia-prone Elderly Subjects. / Wang, Keer; Zhang, Hongyu; Cheng, Clio Yuen Man et al.
Proceedings of the 3rd IEEE International Conference on Micro/Nano Sensors for AI, Healthcare and Robotics. Institute of Electrical and Electronics Engineers, Inc., 2024. p. 107-111 (Proceedings of the IEEE International Conference on Micro/Nano Sensors for AI, Healthcare and Robotics, NSENS).
Proceedings of the 3rd IEEE International Conference on Micro/Nano Sensors for AI, Healthcare and Robotics. Institute of Electrical and Electronics Engineers, Inc., 2024. p. 107-111 (Proceedings of the IEEE International Conference on Micro/Nano Sensors for AI, Healthcare and Robotics, NSENS).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
