Abstract
We propose a novel dual-channel electromyography (EMG) spatio-temporal differential (DESTD) method that can estimate volitional electromyography (vEMG) signals during time-varying functional electrical stimulation (FES). The proposed method uses two pairs of EMG signals from the same stimulated muscle to calculate the spatio-temporal difference between the signals. We performed an experimental study with five healthy participants to evaluate the vEMG signal estimation performance of the DESTD method and compare it with that of the conventional comb filter and Gram–Schmidt methods. The normalized root mean square error (NRMSE) values between the semi-simulated raw vEMG signal and vEMG signals which were estimated using the DESTD method and conventional methods, and the two-tailed -test and analysis of variance were conducted. The results showed that under the stimulation of the gastrocnemius muscle with rapid and dynamically modulated stimulation intensity, the DESTD method had a lower NRMSE compared to the conventional methods (p < 0.01) for all stimulation intensities (maximum 5, 10, 15, and 20 mA). We demonstrated that the DESTD method could be applied to wearable EMG-controlled FES systems because it estimated vEMG signals more effectively compared to the conventional methods under dynamic FES conditions and removed unnecessary FES-induced EMG signals.
Highlights
Functional electrical stimulation (FES) induces the action potential of muscles by stimulating muscle motor nerves with electric current pulses
functional electrical stimulation (FES) systems typically require the assistance of physical therapists for controlling the systems or applying predetermined stimulation patterns
FES system that can be operated in response to the motion intention of a patient has been studied using wearable motion sensors [6,7,8], gait phase detection sensors for lower limbs, and muscle activity measurement sensors (e.g., electromyography (EMG) [10], and mechanomyography [11])
Summary
Functional electrical stimulation (FES) induces the action potential of muscles by stimulating muscle motor nerves with electric current pulses. It has been widely utilized in various areas of rehabilitation, e.g., hand mobility rehabilitation for stroke patients [1], dorsiflexion rehabilitation for foot drop patients [2], and rehabilitation for spinal cord injury patients [3,4,5]. Surface EMG sensors are one of the representative muscle activity measurement sensors They have been mainly utilized to identify the motion intention in patient-active FES systems on the basis of the characteristics of muscle contraction biosignals that can be achieved prior to performing the motion
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