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

Theme Issue: Participatory Methods in Rehab Interventions and Assistive Technologies (29) Mobile Health (mhealth) (5314) Focus Groups and Qualitative Research for Human Factors Research (1605) Wearable Devices and Sensors (1662) Technology in Physiotherapy (307)

Published on in Vol 12 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67440, first published .
Anatomical illustration of a runner's musculature and vascular system glowing with neon blue and pink light.

Assessing Physical Therapists’ Expectations and Experiences With an Automated Rehabilitation System Using Technology Acceptance Model: Multiple Methods Pilot Study

Assessing Physical Therapists’ Expectations and Experiences With an Automated Rehabilitation System Using Technology Acceptance Model: Multiple Methods Pilot Study

Authors of this article:

Cynthia Williams1 Author Orcid Image ;   Lindsay Toth2 Author Orcid Image ;   Raine Osborne3 Author Orcid Image ;   Chloe E Bailey4 Author Orcid Image ;   Aishwarya Joshi1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Funayama T, Uchida Y, Asano Y, Soma D. MediaPipe-Based Activity Analysis by Healthcare Professionals: Method Development and Technology Acceptance—A Pilot Study. Sensors 2026;26(17):5681 View
  2. Sequeira J. Low-cost robotics and AI technologies for rehabilitation and health monitoring. Frontiers in Robotics and AI 2026;13 View
  3. Mikko S, Cronström A, Sandlund M, Häger C. “It’s a black box”: Physiotherapists’ perspectives on sensorimotor control and the use of technology in this context to improve rehabilitation following ACL injury. BMC Musculoskeletal Disorders 2026;27(1) View