Application of biofeedback loop in rehabilitation optimization after robot-assisted total knee replacement

Objective:Robot-assisted total knee replacement (TKA) faces technical gaps including lack of real-time quantitative feedback and insufficient individualization in postoperative rehabilitation. This study aims to explore the application value of a multimodal biofeedback loop system—integrating joint pressure sensing, surface electromyography (sEMG) monitoring, and kinematic tracking—in optimizing postoperative rehabilitation, thereby improving functional recovery efficiency and prosthesis long-term survival rate. Methods: A single-center randomized controlled trial was conducted at Jiujiang First People's Hospital from January 2022 to October 2025, enrolling 160 robot-assisted TKA patients. They were randomly assigned to the observation group (biofeedback loop-assisted rehabilitation, n=80) and the control group (traditional rehabilitation, n=80). The observation group adopted a closed-loop system with 16-channel sEMG array, piezoresistive pressure sensors, and inertial measurement units (IMU), combined with a lightweight convolutional neural network (CNN) for real-time data analysis (<=200 ms delay) and dynamic feedback (vibration/visual/auditory). The control group received conventional rehabilitation. Outcomes were compared at 12 weeks, 6 months, and 1 year postoperatively using Knee Association Scoring (KSS), gait analysis, imaging, and cost accounting. Results: Preliminary data showed that the observation group had significantly higher KSS scores at 12 weeks postoperatively than the control group (P<0.05), with 30% shorter recovery time, 35% reduced abnormal prosthesis stress, and 20%-25% lower overall treatment cost. At 6 months, the observation group exhibited better gait symmetry and muscle activation efficiency (P<0.05). The biofeedback system achieved high data synchronization accuracy (<5 ms error) and algorithmic reliability (RMSE=0.03±0.01 for muscle activation calculation). Conclusion: The multimodal biofeedback loop system optimizes robot-assisted TKA postoperative rehabilitation through real-time multimodal data fusion and dynamic feedback. It not only improves functional recovery quality and economic efficiency but also fills the technical gap between robotic surgical precision and postoperative rehabilitation. With strong reproducibility and clinical promotability, this system provides an effective solution for precise rehabilitation, warranting clinical application.