NCT05173064

Effects of a Machine Learning-based Lower Limb Exercise Training System for Knee Pain

Development and Randomized Controlled Trial of an AI-powered Technological Surrogate Physiotherapist (TSP) Dedicated to Quality Enhancement and Cost Reduction in Knee Osteoarthritis Exercise Rehabilitation

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 264 (estimated)
• Sponsor: The University of Hong Kong · Academic / Other
• Sex: All
• Age: 50 Years
• Healthy volunteers: Not accepted

Summary

The goal of the study is to confirm the idea of AI-powered Technological Surrogate Physiotherapist (TSP), by demonstrating its effectiveness and value as a new technology-based contribution to OA healthcare. Participants will be randomized to one of three groups: (1) the conventional PT group receiving the exercise program delivered through in-person sessions; (2) the AI-guided group following the program through the TSP after an initial PT session; or (3) the combined group receiving both in-person PT sessions and AI-guided home exercise. All individuals will take part in the study for 12 weeks, and data will be collected at baseline and 12 weeks after randomization.

Detailed description

Knee pain, often caused by osteoarthritis, is a prevalent musculoskeletal disorder among older adults and significantly reduces physical function and quality of life. Exercise therapy has been shown to be an effective form of treatment for knee pain. However, the traditional delivery of exercise therapy requires that individuals attend clinics to participate in face-to-face exercise sessions, which can be expensive and inconvenient. In recent years, information technologies have been used to support the delivery of exercise programs. The programs have also shown great benefits in improving the management of knee pain. However, it remains a concern that physical therapists are not able to provide the patients with direct and immediate supervision when exercises are taken place remotely at home or in community centers, which can be detrimental to exercise performance and the management of knee pain. Thus, the research team has developed a machine learning-based exercise training system to provide evidence-based lower limb exercise videos, real-time movement feedback, and tracking of exercise progress for older adults with knee pain. In this study, a 12-week randomized controlled non-inferiority trial will be conducted to examine the effects of AI-powered Technological Surrogate Physiotherapist, comparing with the effects of the group receiving in-person sessions and effects of the combined group receiving both.

Conditions

• Pain
• Knee Osteoarthritis

Interventions

Type	Name	Description
DEVICE	The AI-powered Technological Surrogate Physiotherapist	The AI-powered Technological Surrogate Physiotherapist will have three key features: 1. Evidence-based exercise videos instructed by physical therapists 2. Real-time movement feedback and performance score 3. Exercise records.
BEHAVIORAL	Face-to-face physiotherapist-supervised exercise program	Physiotherapists will give usual face-to-face therapy. The assessment of participants' exercise movements will only be achieved in the traditional manner during face-to-face exercise sessions - by physiotherapists' visual inspection of and professional judgement on postural alignment and effectiveness, with verbal instructions for posture correction. The features of real-time movement feedback and tracking of exercise progress will not be provided.
COMBINATION_PRODUCT	The AI-powered Technological Surrogate Physiotherapist Plus Face-to-face physiotherapist-supervised exercise program	This group will attend in-person group therapy sessions, while additionally completing weekly home exercise sessions using the TSP system.

Timeline

• Start date: 2025-10-30
• Primary completion: 2027-01-31
• Completion: 2027-03-31
• First posted: 2021-12-29
• Last updated: 2025-10-07

Locations

1 site across 1 country: Hong Kong