Processing respiratory muscle signals of preterm infants

Nelson R. Claure, Wunnava V. Subbarao, Shahnaz Duara

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

Abstract

A digital signal processing method for the processing of electromyographic (EMG) signals from respiratory muscles of premature infants is presented. The EMG signals are digitized at 1000 Hz, filtered, and processed to eliminate electrocardiographic contamination. Software for the processing of the EMG signals which eliminates low-frequency noise from respiratory movement and 60-Hz electrical noise was developed. The most important part of the EMG signal processing is the extraction of the electrocardiographic (ECG) artifact to obtain an EMG signal that is free from the ECG contaminant. Once the EMG signal is cleaned, it is passed through a moving time averager for later analysis. The ECG signal that is used as timing reference for the clearing of the EMG signals is bandpass filtered.

Original languageEnglish (US)
Title of host publicationBiomedical Engineering Perspectives
Subtitle of host publicationHealth Care Technologies for the 1990's and Beyond
PublisherPubl by IEEE
Pages829-830
Number of pages2
Editionpt 2
ISBN (Print)0879425598
StatePublished - Dec 1 1990
Externally publishedYes
EventProceedings of the 12th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Philadelphia, PA, USA
Duration: Nov 1 1990Nov 4 1990

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 2
ISSN (Print)0589-1019

Other

OtherProceedings of the 12th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CityPhiladelphia, PA, USA
Period11/1/9011/4/90

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint Dive into the research topics of 'Processing respiratory muscle signals of preterm infants'. Together they form a unique fingerprint.

Cite this