Technological Surrogate Physiotherapy to Improve Knee Health Through Exercise: Human-Computer Interaction to Build Trust and Acceptance Notwithstanding Pain

A machine-learning system is constructed to alleviate chronic knee pain through exercise and muscle strengthening. Three user-focused features are offered: video-based exercise demonstrations, real-time posture analysis and feedback, and performance and progress tracking. This system, which functions as an artificially-intelligent “technological surrogate physiotherapist,” applies human-computer incentive compatibility and joint learning-by-doing to reify and strengthen motivation, trust and acceptance and to increase effectiveness and efficacy, initial exacerbation of knee pain notwithstanding. In a 3-week experiment involving 60 individuals carrying chronic knee pain, positive and statistically significant outcomes were recorded regarding the Western Ontario and McMaster Universities Osteoarthritis Index physical function (p = 0.001), quality of life (EQ-5D-5L: < 0.001; EQ VAS: p = 0.004), exercise engagement (p < 0.001), system usability, and system acceptance. Technology-based solutions hold significant promise for improving future clinical practice by reducing professional resource demand and increasing the accessibility and caregiver-patient incentive compatibility under physiological healthcare.