TY - JOUR
T1 - StimEMG
T2 - An Electromyogram Recording System With Real-Time Removal of Time-Varying Electrical Stimulation Artifacts
AU - Zhao, Jiashun
AU - Yuan, Rui
AU - Shin, Henry
AU - Ji, Run
AU - Zheng, Yang
N1 - Publisher Copyright:
© 2025 The Authors.
PY - 2025
Y1 - 2025
N2 - A closed-loop Functional Electrical Stimulation (FES) system that incorporates electromyogram (EMG) signal feedback provides more effective assistance to paralytic patients in maintaining and recovering their motor abilities. However, the closed-loop FES system with real-time adjustment of stimulation parameters tends to introduce time-varying stimulation artifacts in EMG signals, challenging the removal of stimulation artifacts that aims at more accurate monitoring of muscle contraction status. Therefore, an EMG acquisition system that embeds a stimulation artifact generation (SAG) circuit and the Recursive Least Squares (RLS) adaptive filter was developed in this study and named StimEMG. The SAG-RLS strategy was tested using the simulated contaminated EMG signals and the StimEMG system was tested in an experimental study with 8 subjects. Both the simulation and the experimental study showed that the SAG-RLS method obtained a higher correlation (R{}^{{2}})} between the denoised EMG and the corresponding clean EMG or EMG segments compared with the current Gram-Schmidt-based (GSB) method (simulation study, 0.98± 0.0044 v.s. 0.65± 0.3217 ; experimental study, 0.99± 0.0024 v.s. 0.52± 0.2105 ). Meanwhile, the SAG-RLS method can suppress stimulation artifact more effectively, resulting a higher signal-to-noise ratio (simulation study: 12.83± 2.1745 v.s. 1.54± 1.3106 ) and higher noise rejection ratio (experimental study:2.32± 0.7046 v.s. 1.92± 0.8014 ). The significantly improved performance is speculated to result from the ability of the SAG unit to precisely and timely capture the variation of the stimulation artifacts caused by the change of stimulation parameters, unlike previous methods relying on the stability of the characteristic of stimulation artifacts in the contaminated EMG signals. The developed StimEMG system provides a robust EMG acquisition module for the closed-loop FES system.
AB - A closed-loop Functional Electrical Stimulation (FES) system that incorporates electromyogram (EMG) signal feedback provides more effective assistance to paralytic patients in maintaining and recovering their motor abilities. However, the closed-loop FES system with real-time adjustment of stimulation parameters tends to introduce time-varying stimulation artifacts in EMG signals, challenging the removal of stimulation artifacts that aims at more accurate monitoring of muscle contraction status. Therefore, an EMG acquisition system that embeds a stimulation artifact generation (SAG) circuit and the Recursive Least Squares (RLS) adaptive filter was developed in this study and named StimEMG. The SAG-RLS strategy was tested using the simulated contaminated EMG signals and the StimEMG system was tested in an experimental study with 8 subjects. Both the simulation and the experimental study showed that the SAG-RLS method obtained a higher correlation (R{}^{{2}})} between the denoised EMG and the corresponding clean EMG or EMG segments compared with the current Gram-Schmidt-based (GSB) method (simulation study, 0.98± 0.0044 v.s. 0.65± 0.3217 ; experimental study, 0.99± 0.0024 v.s. 0.52± 0.2105 ). Meanwhile, the SAG-RLS method can suppress stimulation artifact more effectively, resulting a higher signal-to-noise ratio (simulation study: 12.83± 2.1745 v.s. 1.54± 1.3106 ) and higher noise rejection ratio (experimental study:2.32± 0.7046 v.s. 1.92± 0.8014 ). The significantly improved performance is speculated to result from the ability of the SAG unit to precisely and timely capture the variation of the stimulation artifacts caused by the change of stimulation parameters, unlike previous methods relying on the stability of the characteristic of stimulation artifacts in the contaminated EMG signals. The developed StimEMG system provides a robust EMG acquisition module for the closed-loop FES system.
KW - EMG
KW - Electrical stimulation
KW - adaptive filter
KW - recursive least squares
KW - stimulation artifact
UR - https://www.scopus.com/pages/publications/105002647193
U2 - 10.1109/TNSRE.2025.3555572
DO - 10.1109/TNSRE.2025.3555572
M3 - 文章
C2 - 40168535
AN - SCOPUS:105002647193
SN - 1534-4320
VL - 33
SP - 1305
EP - 1315
JO - IEEE Transactions on Neural Systems and Rehabilitation Engineering
JF - IEEE Transactions on Neural Systems and Rehabilitation Engineering
ER -