Volitional EMG Estimation Method during Functional Electrical Stimulation by Dual-Channel Surface EMGs.

Area of Science:

• Biomedical Engineering
• Neuroscience
• Rehabilitation Technology

Background:

• Functional Electrical Stimulation (FES) systems require accurate volitional electromyography (vEMG) signal detection for effective control.
• Conventional methods struggle to isolate vEMG signals from FES-induced artifacts, especially under dynamic stimulation conditions.

Purpose of the Study:

• To introduce and evaluate a novel Dual-channel Electromyography Spatio-Temporal Differential (DESTD) method for estimating vEMG signals during time-varying FES.
• To compare the performance of the DESTD method against conventional comb filter and Gram-Schmidt methods.

Main Methods:

• The DESTD method utilizes two pairs of EMG signals from the same stimulated muscle to compute spatio-temporal differences.
• Experimental evaluation involved five healthy participants performing isometric plantarflexion with FES applied to the gastrocnemius muscle.
• Performance was assessed using Normalized Root Mean Square Error (NRMSE) between semi-simulated and estimated vEMG signals, with statistical analysis via t-tests and ANOVA.

Main Results:

• The DESTD method demonstrated significantly lower NRMSE compared to conventional methods (p < 0.01) across various FES intensities (5-20 mA).
• This improved performance was observed under rapid and dynamically modulated stimulation intensity conditions.
• The DESTD method effectively removed FES-induced EMG artifacts, preserving the integrity of the vEMG signal.

Conclusions:

• The DESTD method offers a superior approach for estimating vEMG signals in the presence of dynamic FES.
• Its effectiveness and artifact removal capabilities make it suitable for advanced wearable EMG-controlled FES applications.
• This advancement holds potential for improving the functionality and user experience of FES-based neurorehabilitation and assistive devices.