A Novel Technique to Reject Artifact Components for Surface EMG Signals Recorded During Walking With Transcutaneous Spinal Cord Stimulation: A Pilot Study.

Minjae Kim,Kelly A Mckenzie,Keehoon Kim,Jasmine Hunt,Levi J Hargrove,Yaejin Moon,Arun Jayaraman,Matt Mcguire,Adam Horin

doi:10.3389/fnhum.2021.660583

Abstract

Transcutaneous spinal cord electrical stimulation (tSCS) is an emerging technology that targets to restore functionally integrated neuromuscular control of gait. The purpose of this study was to demonstrate a novel filtering method, Artifact Component Specific Rejection (ACSR), for removing artifacts induced by tSCS from surface electromyogram (sEMG) data for investigation of muscle response during walking when applying spinal stimulation. Both simulated and real tSCS contaminated sEMG data from six stroke survivors were processed using ACSR and notch filtering, respectively. The performance of the filters was evaluated with data collected in various conditions (e.g., simulated artifacts contaminating sEMG in multiple degrees, various tSCS intensities in five lower-limb muscles of six participants). In the simulation test, after applying the ACSR filter, the contaminated-signal was well matched with the original signal, showing a high correlation (r = 0.959) and low amplitude difference (normalized root means square error = 0.266) between them. In the real tSCS contaminated data, the ACSR filter showed superior performance on reducing the artifacts (96% decrease) over the notch filter (25% decrease). These results indicate that ACSR filtering is capable of eliminating artifacts from sEMG collected during tSCS application, improving the precision of quantitative analysis of muscle activity.

Highlights

The result reflects that the algorithm was able to extract the surface electromyograms (sEMG) signal induced by muscle activity with minimal loss of data in all signals contaminated with various artifact-to-signal ratios
We evaluated the performance of the Artifact Component Specific Rejection (ACSR) filter with both simulated and actual Transcutaneous spinal cord electrical stimulation (tSCS) artifact-contaminated data and observed that the filter is capable of removing these artifacts
The performance of the ACSR filter was tested with simulated artifact-contaminated sEMG, which was generated with a linear combination of the sEMG without tSCS and simulated artifacts contaminating sEMG in multiple degrees

Summary

Introduction

Several studies have demonstrated that spinal stimulation has helped restore functionally integrated neuromuscular control of gait in individuals with spinal cord injury (Carhart et al, 2004; Hofstoetter et al, 2015; Minassian et al, 2016; Angeli et al, 2018; Gill et al, 2018; Wagner et al, 2018). There are several intrinsic and extrinsic sources of baseline noise including the amount of fatty tissue between the skin and the muscle tissue, skin-electrode interface, thermal noise, and power line noise (De Luca et al, 2010) Together, these noise sources generate various forms of sEMG artifacts, which might lead to erroneous interpretations of sEMG concerning the neuromuscular effects of tSCS

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Discussion

Conclusion