Denoising of Diaphragmatic Electromyogram Signals for Respiratory Control and Diagnostic Purposes

Stephen R. Alty, William D. -C. Man, John Moxham, Kalok C. Lee

Research output: Chapter in Book/Report/Conference proceedingConference paper

13 Citations (Scopus)

Abstract

Diaphragmatic electromyogram (EMGdi) signals give important information about the respiratory muscle pump, can be used as an indicator of neural respiratory drive, and have been postulated as a method of designing neurally-activated intelligent ventilators. However diaphragmatic EMG signals measured with an esophageal catheter tend to be contaminated by electrical signals from the heart - electrocardiogram (ECG). This paper presents a novel method of rapidly separating and enhancing the Electromyogram signals from the combined EMG and ECG signals recorded from an esophageal catheter based sensor. Independent Component Analysis (ICA) is used to separate the EMG and ECG signals, then further processing is used to extract the frequency of the patient's breathing and the relative magnitudes of diaphragmatic muscle activity. These signals have two applications, firstly in artificial ventilator systems and as a diagnostic tool for health professionals.
Original languageEnglish
Title of host publicationUnknown
Place of PublicationNEW YORK
PublisherIEEE
Pages5560 - 5563
Number of pages4
ISBN (Print)978-1-4244-1814-5
Publication statusPublished - 2008
Event30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society - Vancouver, Canada
Duration: 20 Aug 200824 Aug 2008

Publication series

Name2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8

Conference

Conference30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society
Country/TerritoryCanada
CityVancouver
Period20/08/200824/08/2008

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