Muscle synergy-guided optimization of FES based on real-time vEMG feedback for personalized neuromodulation
Source abstract
Abstract
Emerging evidence underscores the role of muscle synergies in neural control, presenting a promising path for advancing neuromodulation strategies. Functional electrical stimulation (FES) directly activates and regulates the peripheral neuromuscular system, making it particularly advantageous for synergy-guided neuromodulation. However, a comprehensive framework integrating volitional feedback for synergy-guided FES parameter optimization is currently lacking. This study introduced a novel synergy-guided framework to optimize FES parameters based on volitional EMG (vEMG) feedback. Leveraged by multi-channel FES with synchronized vEMG acquisition, real-time muscle synergy patterns were identified, guiding FES to assist the subject in achieving the target synergy pattern. Bayesian optimization was employed to refine FES parameters, ensuring personalized and adaptive neuromodulation. Additionally, an intensity decay strategy promoted the transition from FES-assisted to independent volitional control. Experiments were conducted on healthy individuals to evaluate the efficacy of the synergy-guided neuromodulation framework. A total of 14 participants performed upper-limb isometric exercises in the horizontal plane, from which the average synergy pattern was extracted as the target synergy. Subsequently, 5 individuals exhibiting large deviations from the target synergy were selected for the synergy modulation experiment. Results demonstrated that the synergies of all 5 participants were successfully modulated towards the target synergy, as indicated by meaningful improvements in synergy variance accounted for (VAF) and similarity to the target pattern (Cliff’s Delta ⩾ 0.6). These findings suggest that the proposed synergy-guided neuromodulation framework has strong potential as an effective therapeutic approach for individuals with neurologically impaired motor function, offering substantial improvements in neurorehabilitation outcomes.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Muscle activation and electromyography studies · Stroke Rehabilitation and Recovery · Motor Control and Adaptation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (37)
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