Comprehensive testing system for cardiorespiratory interaction research.
- Author:
Zhengbo ZHANG
1
;
Buqing WANG
;
Weidong WANG
;
Jiewen ZHENG
;
Hongyun LIU
;
Kaiyuan LI
;
Congcong SUN
;
Guojing WANG
Author Information
1. Department of Biomedical Engineering, Chinese PLA General Hospital, Beijing 100853, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artifacts;
Autonomic Nervous System;
physiopathology;
Diagnosis, Computer-Assisted;
methods;
Electrocardiography;
Equipment Design;
Heart;
physiology;
Humans;
Lung;
physiology;
Monitoring, Physiologic;
instrumentation;
methods;
Respiration;
Respiratory Mechanics;
physiology
- From:
Journal of Biomedical Engineering
2013;30(2):395-402
- CountryChina
- Language:Chinese
-
Abstract:
To investigate the modulation effects of breathing movement on cardiovascular system and to study the physiological coupling relationship between respiration and cardiovascular system, we designed a comprehensive testing system for cardiorespiratory interaction research. This system, comprising three parts, i. e. physiological signal conditioning unit, data acquisition and USB medical isolation unit, and a PC based program, can acquire multiple physiological data such as respiratory flow, rib cage and abdomen movement, electrocardiograph, artery pulse wave, cardiac sounds, skin temperature, and electromyography simultaneously under certain experimental protocols. Furthermore this system can be used in research on short-term cardiovascular variability by paced breathing. Preliminary experiments showed that this system could accurately record rib cage and abdomen movement under very low breathing rate, using respiratory inductive plethysmography to acquire respiration signal in direct-current coupling mode. After calibration, this system can be used to estimate ventilation non-intrusively and correctly. The PC based program can generate audio and visual biofeedback signal, and guide the volunteers to perform a slow and regular breathing. An experiment on healthy volunteers showed that this system was able to guide the volunteers to do slow breathing effectively and simultaneously record multiple physiological data during the experiments. Signal processing techniques were used for off-line data analysis, such as non-invasive ventilation calibration, QRS complex wave detection, and respiratory sinus arrhythmia and pulse wave transit time calculation. The experiment result showed that the modulation effect on RR interval, respiratory sinus arrhythmia (RSA), pulse wave transit time (PWTT) by respiration would get stronger with the going of the slow and regular breathing.
