Abstract In an era dominated by technology and sedentary lifestyles, posture-related dysfunctions have become increasingly prevalent, particularly among digitally engaged populations. Traditional physiotherapy, although effective, often struggles with compliance, personalization, and continuity in remote settings. This paper introduces a novel artificial intelligence (AI)-driven rehabilitation framework that redefines physiotherapy delivery by integrating real-time posture monitoring, machine learning-based corrective algorithms, and adaptive feedback systems.We propose an ethically-grounded and clinically scalable system called the Neuro-AI Physio brace—an intelligent wearable supported by AI algorithms that detects postural deviations, evaluates neuromuscular patterns, and delivers personalized interventions through guided physiotherapeutic cues. The AI framework is trained on diverse datasets involving postural markers, functional mobility scores, and individual rehabilitation profiles. The system is designed not only to correct biomechanical inefficiencies but also to promote long-term neuromuscular adaptation via predictive learning and behaviour reinforcement loops.Beyond functionality, this model emphasizes patient autonomy, data privacy, and ethical compliance in AI-assisted care. We discuss the potential of this approach in reducing musculoskeletal strain, improving adherence, and redefining physiotherapy in both clinical and home-based environments. The article also explores its implications for future AI regulation in physical medicine and rehabilitation. This paper serves as both a conceptual prototype and a call to action for integrating ethical, intelligent technologies in physiotherapy—shaping the future of patient-centric, AI-augmented rehabilitation.
Muthukrishnan et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: