Real-time adaptive cancellation of TENS feedback artifact on sEMG for prosthesis closed-loop control.

ABSTRACT:

Introduction

The prosthetic hand has been aimed to restore hand functions by estimating the user's intention via bio-signal and providing sensory feedback. Surface electromyogram (sEMG) is a widely used signal, and transcutaneous electrical nerve stimulation (TENS) is a promising method for sensory feedback. However, TENS currents can transmit through the skin and interfere as noise with the sEMG signals, referred to as "Artifact," which degrades the performance of intention estimation.

Method

In this paper, we proposed an adaptive artifact removal method that can cancel artifacts separately across different frequencies and pulse widths of TENS. The modified least-mean-square adaptive filter uses the mean of previous artifacts as reference signals, and compensate using prior

SUBMITTER: Lee B 

PROVIDER: S-EPMC11617178 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature