Non-Invasive Measurement of Diaphragmatic Contraction Timing in Dogs

Abstract

The movement of thoracic cage (TM) measured with a piezoelectric contact sensor placed on the costal wall is presented in this work as a new non-invasive technique for diaphragmatic contraction period (CP) monitoring. Relationship between CP estimated with this technique is compared with estimations done with other respiratory signals commonly employed for physiological research studies: diaphragm length measured with sonomicrometry (DL), transdiafragmatic pressure (DP) and respiratory airflow (FL). Specific algorithms were developed to determinate the CP in the four signals. Experiments were performed in three pentotarbital-anesthetized mongrel dogs. Two respiratory tests were studied: spontaneous ventilations (SV) and respiration with an inspiratory load (IL). CP estimated with DL signal was used as reference because this signal is the directly related with the diaphragmatic contraction. Different parameters were estimated for the study of the relationship between CP measured with DL signal and CP measured with TM, FL and DP signals. High relationships were obtained in the IL respiratory test. Lower values were obtained in SV protocol, but the parameters obtained from TM signal correlated better with the ones obtained from DL signal than those from FL and DP signals. Results confirm that it is possible to monitor the diaphragmatic contraction timing with a non-invasive piezoelectric contact sensor.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA409563

Entities

People

  • A. E. Grassino
  • Andrei Torres
  • J. A. Fiz
  • J. Morera
  • Robert Jane

Organizations

  • Centre hospitalier de l'Université de Montréal

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Anesthesia
  • Coefficients
  • Detection
  • Detectors
  • Errors
  • Health Services
  • Measurement
  • Monitoring
  • Physiological Monitoring
  • Piezoelectric Crystals
  • Reliability
  • Respiration
  • Signal Processing
  • Skeletal Muscle
  • Statistical Analysis
  • Ventilation

Readers

  • Cardiovascular Physiology
  • Materials Science and Engineering.
  • Positioning, Navigation, and Timing (PNT) Technology.