Enhanced rehabilitation after total joint replacement using a wearable high-density surface electromyography system
Year: 2025
Type: article
Abstract: Introduction: Neuromuscular recovery after total joint arthroplasty remains insufficiently understood, and current tools for assessing muscle function lack the resolution to monitor detailed recovery dynamics. High-Density surface Electromyography (HD-sEMG) enables spatiotemporal analysis of muscle activation and may support individualized rehabilitation. However, its clinical application in orthopedic settings remains limited. Methods: This exploratory study presents a methodological framework for applying wearable 64-channel HD-sEMG system to monitor neuromuscular recovery in patients undergoing total knee or hip arthroplasty. HD-sEMG data were recorded during standardized mobilization exercises at multiple pre- and postoperative time points. A custom signal processing pipeline was developed, encompassing artifact suppression, dimensionality reduction, feature extraction, and the derivation of five functional indices summarizing key aspects of muscle performance. Results: Initial clinical application demonstrated the feasibility of the approach. The functional indices revealed distinct recovery dynamics across patients and showed promising alignment with patient-reported outcome measures. Individual case analyses suggested the potential of HD-sEMG to differentiate between restitution and dysfunctional compensation patterns. Discussion: This study provides a structured, exploratory foundation for longitudinal HD-sEMG research in orthopedic rehabilitation. While not yet suited for clinical decision-making, the proposed framework offers methodological tools for future investigations of neuromuscular recovery trajectories and may contribute to the development of personalized, data-driven rehabilitation strategies.
Institutions: Saarland University, Universitätsklinikum des Saarlandes
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W4415237378