Published on in Vol 23, No 10 (2021): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29884, first published .
Accuracy and Diversity of Wearable Device–Based Gait Speed Measurement Among Older Men: Observational Study

Accuracy and Diversity of Wearable Device–Based Gait Speed Measurement Among Older Men: Observational Study

Accuracy and Diversity of Wearable Device–Based Gait Speed Measurement Among Older Men: Observational Study

Journals

  1. Dlima S, Shevade S, Menezes S, Ganju A. Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review. JMIR Bioinformatics and Biotechnology 2022;3(1):e39618 View
  2. Biswas N, Chakrabarti S, Jones L, Ashili S. Smart wearables addressing gait disorders: A review. Materials Today Communications 2023;35:106250 View
  3. Turimov Mustapoevich D, Kim W. Machine Learning Applications in Sarcopenia Detection and Management: A Comprehensive Survey. Healthcare 2023;11(18):2483 View
  4. Shin J, Kweon H, Choi J. Assessment of Gait Parameters Using Wearable Sensors and Their Association With Muscle Mass, Strength, and Physical Performance in Korean Older Adults: Cross-Sectional Study. JMIR Formative Research 2025;9:e63928 View
  5. Chang C, Wei C, Lien W, Yang T, Liu B, Lin Y, Tan P, Lin Y. The Usability and Effect of a Novel Intelligent Rehabilitation Exergame System on Quality of Life in Frail Older Adults: Prospective Cohort Study. JMIR Serious Games 2025;13:e50669 View