Estimated ECG Subtraction method for removing ECG artifacts in esophageal recordings of diaphragm EMG

Annemijn H. Jonkman*, Ricardo Juffermans, Jonne Doorduin, Leo M.A. Heunks, Jaap Harlaar

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The accuracy of diaphragm electromyogram (EMGdi) derived parameters, as used in critically ill intensive care unit (ICU) patients, can be compromised due to electrocardiographic (ECG) interference in the EMGdi signal. Removal of ECG contamination from the esophageal recordings of the EMGdi is challenging due to spectral overlapping of EMG and ECG signals and because of variability in ECG shape and amplitude. Therefore, we designed an Estimated ECG Subtraction (EES) method, based on three steps: (1) identification of the timing of the ECG artifact without an ECG reference channel, (2) estimation of the normalized ECG, considering the EMGdi as noise, and (3) subtraction of the denormalized ECG estimate from the EMGdi recordings. We evaluated the EES method against the use of a single wavelet-based adaptive filter. Using EMGdi signals of ten ICU patients and simulated contaminated EMG, we demonstrated that the EES method yields uncontaminated EMGdi, and showed that it is more effective than a wavelet-based adaptive filter only. Implementation of this technique may offer means to improve diaphragm activity monitoring and control in clinical practice.

Original languageEnglish
Article number102861
JournalBiomedical Signal Processing and Control
Volume69
DOIs
Publication statusPublished - Aug 2021

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