Diz Osteoartriti Egzersiz Yönetimi İçin Derin Öğrenme Tabanlı Exergame Sistemi

Özet (abstract)

Home-based exercise management for people with knee osteoarthritis (KOA) is often limited by insufficient movement supervision, individualization, and progression support. This study described the development and preliminary evaluation of a KOA-specific 3D exergame exercise management system. The system combined markerless motion analysis using a conventional RGB camera with biomechanical analysis, concurrent avatar-based guidance, task-specific feedback, adaptive difficulty adjustment, pain monitoring, therapist override, and training records. Exercise tasks addressed lower-limb strength, balance, range of motion, and toe-in or toe-out gait retraining. Five physiotherapists conducted a preliminary evaluation of the prototype through technology-acceptance and usability questionnaires and semi-structured interviews. They reported generally favorable perceptions and identified clinically relevant exercise content, low sensing burden, comprehensive feedback, and training-progress monitoring as potential strengths. Concerns included fall risk during demanding tasks, limited individualization of some parameters, and insufficient safeguards for unsupervised use. Selected TDPT-derived kinematic measures were also compared with synchronized marker-based motion capture using a public dataset comprising 18 squat cycles from six participants. Agreement varied by measure: waveform associations were strong for functional hip flexion, knee flexion, trunk inclination, and frontal-plane hip abduction/adduction, whereas absolute errors ranged from 6.59° to 20.00° and the foot-orientation proxy showed negligible correlation. These findings provide preliminary clinician-informed and task-specific technical evidence for the prototype but do not establish patient usability or clinical effectiveness. Further technical validation, safety refinement, and supervised evaluation with people with KOA are required before routine or independent home use can be considered.

Yazarların özeti; kaynağından alınmıştır. Sensors, 2026 · DOI ↗