期刊
ACS NANO
卷 15, 期 12, 页码 18633-18646出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsnano.1c10676
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类别
资金
- 2021 Hellman Fellow Research Grant
The increasing elderly and disabled population pose challenges to the healthcare system. Assistive physical therapy devices, utilizing self-powered sensors and optimized machine-learning algorithms, play a crucial role in promoting well-being and independence. Technological advancements in this field offer innovative solutions to meet global needs.
An expanding elderly population and people with disabilities pose considerable challenges to the current healthcare system. As a practical technology that integrates systems and services, assistive physical therapy devices are essential to maintain or to improve an individual's functioning and independence, thus promoting their well-being. Given technological advancements, core components of self-powered sensors and optimized machine-learning algorithms will play innovative roles in providing assistive services for unmet global needs. In this Perspective, we provide an overview of the latest developments in machine-learning-aided assistive physical therapy devices based on emerging self-powered sensing systems and a discussion of the challenges and opportunities in this field.
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