This paper is in the following e-collection/theme issue:

Technology in Physiotherapy (131) Machine Learning (1434) Innovations in Exercise Rehabilitation (211) Wearable Devices and Sensors (874) Emerging Technologies for Rehabilitation (256) Assistive Technologies (112)

Published on in Vol 9, No 3 (2022): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38689, first published .
Detection of Low Back Physiotherapy Exercises With Inertial Sensors and Machine Learning: Algorithm Development and Validation

Detection of Low Back Physiotherapy Exercises With Inertial Sensors and Machine Learning: Algorithm Development and Validation

Detection of Low Back Physiotherapy Exercises With Inertial Sensors and Machine Learning: Algorithm Development and Validation

Authors of this article:

Abdalrahman Alfakir1, 2 Author Orcid Image ;   Colin Arrowsmith1, 3 Author Orcid Image ;   David Burns1, 3, 4 Author Orcid Image ;   Helen Razmjou1 Author Orcid Image ;   Michael Hardisty1, 4 Author Orcid Image ;   Cari Whyne1, 2, 4 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. Arrowsmith C, Burns D, Mak T, Hardisty M, Whyne C. Physiotherapy Exercise Classification with Single-Camera Pose Detection and Machine Learning. Sensors 2022;23(1):363 View
  2. Ratnaparkhi A, Beckett J. Digital Phenotyping, Wearables, and Outcomes. Neurosurgery Clinics of North America 2023 View
  3. Phan V, Song K, Silva R, Silbernagel K, Baxter J, Halilaj E. Seven Things to Know About Exercise Classification With Inertial Sensing Wearables. IEEE Journal of Biomedical and Health Informatics 2024;28(6):3411 View
  4. Reis F, Carvalho M, Neves G, Nogueira L, Meziat-Filho N. Machine learning methods in physical therapy: A scoping review of applications in clinical context. Musculoskeletal Science and Practice 2024;74:103184 View