Knee4Life: Empowering Knee Recovery After Total Knee Replacement Through Digital Health Protocol

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Computer Vision in Healthcare

Background:

• Total knee replacement (TKR) surgery often results in persistent pain and stiffness, leading to patient dissatisfaction in 10-20% of cases.
• Current post-operative monitoring methods may not adequately capture knee range of motion (ROM) in a patient's home environment.
• Timely intervention is crucial for improving TKR outcomes, but requires effective remote monitoring solutions.

Purpose of the Study:

• To validate a computer vision-based software for measuring knee range of motion in TKR patients.
• To assess the feasibility of integrating this remote monitoring technology into clinical practice for enhanced post-operative care.
• To compare home-recorded ROM data with lab-based measurements.

Main Methods:

• A mixed-methods approach including focus groups with patients and healthcare professionals.
• Validation phase involving 60 participants (30 TKR patients, 30 controls) performing standardized tasks.
• Knee ROM measured using computer vision, marker-based motion capture, and physiotherapy assessments, with a focus on the sit-to-stand test.

Main Results:

• The study protocol aims to establish proof of concept and validate the accuracy and reliability of the computer vision software against established methods.
• Home-based testing will allow comparison of remote versus in-lab ROM data.
• Focus groups will explore the practical integration of the technology into clinical workflows.

Conclusions:

• A validated computer vision-based system offers potential for accurate, remote monitoring of knee ROM post-TKR.
• This technology could enable early detection of stiffness and facilitate timely, non-surgical interventions.
• Improved post-operative care through continuous monitoring may reduce patient dissatisfaction and the need for further invasive procedures.