Literature DB >> 23915829

High-pass filtering to remove electrocardiographic interference from torso EMG recordings.

M Redfern1, R Hughes, D Chaffin.   

Abstract

UNLABELLED: Removal of electrocardiographic (ECG) contamination of electromyographic (EMG) signals from torso muscles is often attempted by high-pass filtering. This study investigated the effects of the cut-off frequency used in this high-pass filtering technique on the resulting EMG signal. Surface EMGs were recorded on five subjects from the rectus abdominis, external oblique, and erector spinae muscles. These signals were then digitally high-pass filtered at cut-off frequencies of 10, 30, and 60 Hz. Integration and power analyses of the filtered EMGs were subsequently performed. It was found that an increase in the cut-off frequency affects the integrated EMG signal by (1) reducing the ECG contamination, (2) decreasing the amplitude, and (3) smoothing the signal. It was concluded that the use of a high-pass filter is effective in reducing ECG interference in integrated EMG recordings, and a cut-off frequency of approximately 30 Hz was optimal. RELEVANCE: Electromyographic recordings of torso muscles are often used in the development of low-back biomechanical models. Unfortunately, these recordings are usually contaminated by electrocardiographic interference. High-pass filtering methods are sometimes used to diminish the influence of ECG from surface EMGs; however, the effects of these filters on the recorded and processed EMG have not been reported. The findings show that high-pass filtering is effective in reducing ECG contamination and motion artefact from integrated EMGs when the appropriate cut-off frequency is used. Inappropriate cut-off frequencies lead to either incomplete ECG removal or excess filtering of the EMG signal.
Copyright © 1993. Published by Elsevier Ltd.

Entities:  

Year:  2005        PMID: 23915829     DOI: 10.1016/S0268-0033(05)80009-9

Source DB:  PubMed          Journal:  Clin Biomech (Bristol, Avon)        ISSN: 0268-0033            Impact factor:   2.063


  20 in total

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