Knee Osteoarthritis, Pain
Conditions
Keywords
knee pain, physical therapy, exercise
Brief 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 two groups: (1) the conventional PT group receiving the exercise program delivered through in-person sessions; or (2) the AI-guided group following the program through the TSP after an initial PT session. 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 compare the effects of the AI-powered Technological Surrogate Physiotherapist with those of in-person physiotherapy sessions.
Interventions
DEVICEThe 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.
BEHAVIORALFace-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.
Sponsors
The University of Hong Kong
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
TRIPLE (Subject, Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
50 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. At least 50 years of age; 2. Report having knee pain most days of the week; 3. Has radiographic evidence of grade 2, 3, or 4 knee OA on the K-L scale in the posteroanterior and/or skyline view in at least 1 knee; 4. Willing and able, both physically and cognitively, to perform the exercises required in the study protocol; 5. Has normal or corrected-to-normal vision; 6. Able to speak Cantonese and read Chinese, AND 7. Able to provide written informed consent.
Exclusion criteria
1. Having a history of knee or hip replacement surgery; 2. Being nonambulatory; 3. Having systemic inflammatory arthritis (e.g., gout); 4. Having a history of trauma (e.g., fractures around the knee, dislocation, sprains or tears of soft tissues like ligaments) or surgical arthroscopy of either knee within the past 6 months; 5. Having intra-articular injection to the knee within the past 6 months; 6. Having cognitive impairment; 7. Involvement in a similar study (i.e., involving physical exercise or physical therapies for knee pain) within the past 6 months; 8. Undergoing recent or imminent surgery (within 3 months) , OR 9. Having medical co-morbidities that preclude participation in exercise.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Changes in knee pain as assessed by a 11-point numerical pain rating scale as recommended by the OARSI | From baseline to 12 weeks | 0 represents no pain and 10 represents the worst possible pain. |
| Changes in physical function as assessed by the Knee Injury and Osteoarthritis Outcome Score (KOOS) physical function sub-scale | From baseline to 12 weeks | The scale regards the degree of difficulty in performing usual daily activities and higher level activities that involve physical function of the knee. Each item will be rated on a 5-point Likert scale ranging from 'None' (i.e., no difficulty) to 'Extreme' (i.e., extreme difficulty), based on which a normalized total score will be calculated (0 indicating extreme symptoms and 100 indicating no symptoms). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Changes in physical function as assessed by 30-second chair-stand test | From baseline to 12 weeks | 30-second chair stand test (30CST), which measures the number of stands the participant can complete in 30 sec, will be used to assess the general leg strength and functional performance. |
| Changes in physical function as assessed by timed up-and-go test | From baseline to 12 weeks | Timed up and go (TUG) test, which measures the time it takes the participant to standup from the chair, walk 3 meters, walk back to the chair, and sit down, will be used to assess functional mobility. |
| Changes in physical function as assessed by maximal isometric strength of the quadriceps and hamstrings | From baseline to 12 weeks | The participant will be instructed to maximally extend/flex each knee for 3 trials, 3 sec each, with a 1-minute rest in between. Verbal encouragement will be given in each trial to ensure the participant makes the maximum effort. The highest force of each muscle in the three trials will be used for data analysis. After each test trial, the severity of pain experienced by the participant during the trial will be assessed using the 11-point numerical pain rating scale. |
| Exercise adherence | From baseline to 12 weeks | Exercise adherence will be indicated by the proportion of sessions and proportion of exercises performed which will be recorded by the TSP system (only for intervention group) and by participants and researchers using a log book. |
| Satisfaction with the therapeutic exercise training | From baseline to 12 weeks | It will be rated by participants using a 7-point Likert scale with anchors of 'Extremely unsatisfied' and 'Extremely satisfied'. |
| Convenience in terms of location and time for accessing the exercise therapy | From baseline to 12 weeks | It will be assessed on an 11-point numerical rating scale, with 0 representing 'Extremely inconvenient' and 10 representing 'Extremely convenient'. |
Countries
Hong Kong
Contacts
CONTACTCalvin Kalun Or, PhD
Outcome results
None listed