Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77140, first published .
Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study

Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study

Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study

Xiaoping Zheng   1 * , PhD ;   Ziwei Zeng   1 * , MSc ;   Kimberley S van Schooten   2, 3 , PhD ;   Yijian Yang   1, 4 , MD, PhD

1 Department of Sports Science and Physical Education, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong)

2 Neuroscience Research Australia, University of New South Wales, Sydney, Australia

3 School of Population Health, University of New South Wales, Sydney, Australia

4 CUHK Jockey Club Institute of Ageing, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong)

*these authors contributed equally

Corresponding Author:

  • Yijian Yang, MD, PhD
  • Department of Sports Science and Physical Education
  • The Chinese University of Hong Kong
  • G07 Kwok Sports Building. University Ave. The Chinese University of Hong Kong. N.T.
  • Hong Kong
  • China (Hong Kong)
  • Phone: 852 39434001
  • Fax: 852 26035781
  • Email: yyang@cuhk.edu.hk