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

NCT ID: NCT05173064

Last Updated: 2025-10-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

264 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-10-30

Study Completion Date

2027-03-31

Brief Summary

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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

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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

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Pain Knee Osteoarthritis

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

TREATMENT

Blinding Strategy

TRIPLE

Participants Investigators Outcome Assessors

Study Groups

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The AI-powered Technological Surrogate Physiotherapist

Participants will be required to perform three 30-minute exercise sessions per week for 12 weeks, with six exercises at any one time. During the exercise sessions, participants will receiveTechnological Surrogate Physiotherapist (TSP) support which will in particular leverage AI to offer innovative features and modules dedicated to enhancing exercise monitoring and supervision, real-time performance feedback, and self-assessment.

Group Type EXPERIMENTAL

The AI-powered Technological Surrogate Physiotherapist

Intervention Type DEVICE

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.

Face-to-face physiotherapist-supervised exercise program

Participants will be required to visit a physiotherapist for usual face-to-face exercise therapy. Also, they will be required to perform three 30-minute home exercise sessions per week for 12 weeks. However, TSP will not be involved in this group.

Group Type ACTIVE_COMPARATOR

Face-to-face physiotherapist-supervised exercise program

Intervention Type BEHAVIORAL

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.

The AI-powered Technological Surrogate Physiotherapist Plus Face-to-face physiotherapist-supervised

Participants will receive an integrated intervention combining conventional physiotherapist-supervised sessions and TSP-supported home exercises (three 30-minute exercise sessions per week for 12 weeks).

Group Type EXPERIMENTAL

The AI-powered Technological Surrogate Physiotherapist Plus Face-to-face physiotherapist-supervised exercise program

Intervention Type COMBINATION_PRODUCT

This group will attend in-person group therapy sessions, while additionally completing weekly home exercise sessions using the TSP system.

Interventions

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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.

Intervention Type DEVICE

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.

Intervention Type BEHAVIORAL

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.

Intervention Type COMBINATION_PRODUCT

Eligibility Criteria

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Inclusion Criteria

Participants will be recruited if they

* age ≥ 50 years,
* report having pain in or around the knee for more than 12 weeks and on most days of the previous month,
* report being diagnosed with knee OA by a physician, have physician-diagnosed knee OA in the medical record, or have radiographic evidence of grade 2 to 3 knee OA on the Kellgren-Lawrence scale in the posteroanterior and/or skyline view or the presence of lateral/posterior osteophytes (the X-rays will be read and classified by our orthopaedic surgeons collaborators to decide on each patient's eligibility to be included in the study),
* are willing and physically and cognitively able to perform (technology-supported) exercises required in the study protocol
* have normal or corrected to normal vision,
* are able to speak and read Chinese,
* are able to provide written informed consent.

Exclusion Criteria

Individuals will be excluded if they have

* history of knee or hip replacement surgery,
* non-ambulatory status,
* systemic inflammatory arthritis (e.g., gout),
* history of trauma (e.g., fractures around the knee, dislocation, and sprains or tears of soft tissues, like ligaments) or surgical arthroscopy of either knee within the past 6 months,
* intra-articular injection to the knee within the past 6 months,
* cognitive impairment,
* involvement in a similar study in the past 6 months,
* recent or imminent surgery (within 12 weeks),
* medical co-morbidities that preclude participation in exercise.
Minimum Eligible Age

50 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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The University of Hong Kong

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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826, Haking Wong Building, Pokfulam, The University of Hong Kong, Hong Kong

Hong Kong, , Hong Kong

Site Status

Countries

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Hong Kong

Central Contacts

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Calvin Kalun Or, PhD

Role: CONTACT

(852) 3917-2587

Facility Contacts

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Kalun Or, Doctoral degree

Role: primary

(852) 3917-2587

References

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Other Identifiers

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Feedback System

Identifier Type: -

Identifier Source: org_study_id

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