Muscle synergy analysis during badminton forehand overhead smash: integrating electromyography and musculoskeletal modeling

Raheleh Tajik; Wissem Dhahbi; Hamed Fadaei; Raghad Mimar

doi:10.3389/fspor.2025.1596670

Muscle synergy analysis during badminton forehand overhead smash: integrating electromyography and musculoskeletal modeling

Front Sports Act Living. 2025 Jun 3:7:1596670. doi: 10.3389/fspor.2025.1596670. eCollection 2025.

Authors

Raheleh Tajik^#¹, Wissem Dhahbi^#^{2

3}, Hamed Fadaei¹, Raghad Mimar¹

Affiliations

¹ Department of Biomechanics and Sports Injuries, Faculty of Physical Education and Sports Sciences, Kharazmi University, Tehran, Iran.
² Research Unit "Sport Sciences, Health and Movement", Higher Institute of Sports and Physical Education of Kef, University of Jendouba, Kef, Tunisia.
³ Training Department, Police College, Police Academy, Doha, Qatar.

^# Contributed equally.

Abstract

Introduction: This study aimed to quantify shoulder muscle synergies during badminton forehand overhead smash (BFOS) via non-negative matrix factorization (NMF), validate musculoskeletal (MSK) models for high-speed movements by comparing electromyography (EMG)-derived synergies with simulation results, and explore the potential of NMF-based MSK models in advancing sports science.

Methods: Twenty elite badminton players (age: 24 ± 4 years; experience: 15 ± 4 years) performed maximal-effort BFOS while EMG signals from fifteen shoulder muscles were recorded. Three-dimensional motion analysis with a ten-camera Vicon system captured kinematic data at 100 Hz. A validated OpenSim upper extremity model was implemented to simulate muscle activations via static optimization. NMF extracted synergy vectors and activation coefficients from both experimental EMG and MSK modeling data.

Results: Three muscle synergies accounted for >90% variance in both analyses with no significant differences in global VAF (p = 0.12). The first synergy (trapezius-dominant) showed 95% EMG and 97% MSK variance; the second synergy (pectoralis/anterior deltoid) exhibited 97% EMG and 94% MSK variance; the third synergy (posterior muscles) demonstrated 95% EMG and 98% MSK variance. Strong agreement between approaches was observed for both weight vectors (W1:0.81 ± 0.04, W2:0.87 ± 0.01, W3:0.88 ± 0.03) and activation coefficients (C1:0.95 ± 0.02, C2:0.98 ± 0.01, C3:0.98 ± 0.01), with differences primarily in lower trapezius activation (similarity: 0.77 ± 0.05), likely due to challenges in recording deep muscle activity through surface electromyography. These findings validate the combined experimental-computational approach for analyzing complex, high-velocity movements.

Conclusion: The strong correspondence between experimental and computational synergies validates MSK modeling for analyzing neuromuscular control during high-velocity overhead movements. The identified synergies provide a framework for understanding muscle coordination during BFOS, with potential applications in targeted training program optimization and injury prevention strategies in overhead sports.

Keywords: biomechanical phenomena; elite athletes; joint instability; motor control; movement disorders; neuromuscular coordination; rotator cuff.