Quantitative analysis of breathing patterns based on wearable systems.
10.7507/1001-5515.202004047
- Author:
Jiachen WANG
1
;
Hong LIANG
2
;
Yajing WANG
3
;
Weitao WANG
4
;
Ke LAN
5
;
Lu CAO
6
;
Zhengbo ZHANG
2
;
Yuzhu LI
6
;
Zhiwen LIU
3
;
Desen CAO
2
Author Information
1. Medical School of Chinese PLA, Beijing 100853, P.R.China.
2. Department of Biomedical Engineering, Chinese PLA General Hospital, Beijing 100853, P.R.China.
3. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, P.R.China.
4. School of Computer Science and Engineering, Southeast University, Nanjing 211189, P.R.China.
5. Beijing Sensecho Science & Technology Co. Ltd, Beijing 100853, P.R.China.
6. Pneumology Department, Chinese PLA General Hospital, Beijing 100853, P.R.China.
- Publication Type:Journal Article
- Keywords:
breathing pattern;
chronic obstructive pulmonary disease;
respiratory inductive plethysmography;
signal quality;
wearable system
- MeSH:
Humans;
Lung;
Pulmonary Disease, Chronic Obstructive;
Respiration;
Tidal Volume;
Wearable Electronic Devices
- From:
Journal of Biomedical Engineering
2021;38(5):893-902
- CountryChina
- Language:Chinese
-
Abstract:
Breathing pattern parameters refer to the characteristic pattern parameters of respiratory movements, including the breathing amplitude and cycle, chest and abdomen contribution, coordination, etc. It is of great importance to analyze the breathing pattern parameters quantificationally when exploring the pathophysiological variations of breathing and providing instructions on pulmonary rehabilitation training. Our study provided detailed method to quantify breathing pattern parameters including respiratory rate, inspiratory time, expiratory time, inspiratory time proportion, tidal volume, chest respiratory contribution ratio, thoracoabdominal phase difference and peak inspiratory flow. We also brought in "respiratory signal quality index" to deal with the quality evaluation and quantification analysis of long-term thoracic-abdominal respiratory movement signal recorded, and proposed the way of analyzing the variance of breathing pattern parameters. On this basis, we collected chest and abdomen respiratory movement signals in 23 chronic obstructive pulmonary disease (COPD) patients and 22 normal pulmonary function subjects under spontaneous state in a 15 minute-interval using portable cardio-pulmonary monitoring system. We then quantified subjects' breathing pattern parameters and variability. The results showed great difference between the COPD patients and the controls in terms of respiratory rate, inspiratory time, expiratory time, thoracoabdominal phase difference and peak inspiratory flow. COPD patients also showed greater variance of breathing pattern parameters than the controls, and unsynchronized thoracic-abdominal movements were even observed among several patients. Therefore, the quantification and analyzing method of breathing pattern parameters based on the portable cardiopulmonary parameters monitoring system might assist the diagnosis and assessment of respiratory system diseases and hopefully provide new parameters and indexes for monitoring the physical status of patients with cardiopulmonary disease.
