Exploration of continuous noninvasive assessment of left ventricular systolic function under exercise load by using simultaneous cardiac sounds and electrocardiographic signals monitoring technology
10.3760/cma.j.cn113854-20230203-00008
- VernacularTitle:运动负荷下心音心电同步监测技术连续无创评估左心室收缩功能
- Author:
Feng ZANG
1
;
Chongfa ZHONG
;
Jiangbei CAO
;
Libin MA
;
Yue WANG
;
Zemin HUANG
;
Bin WU
;
Chong XU
Author Information
1. 北京体育大学，北京 100084
- Publication Type:Journal Article
- Keywords:
Heart sounds;
Electrocardiography;
Ventricular function, Left;
Exercise load
- From:
Chinese Journal of Aerospace Medicine
2023;34(4):220-225
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To provide references for achieving long time continuous monitoring of cardiac functional changes of astronauts in spaceflight activities through continuously noninvasive assessment of left ventricular systolic function under exercise load by wearable cardiac sounds and ECG signals synchronization monitoring technology.Methods:Eleven healthy male youths were recruited for the study, and they did incremental load exercise on the recumbent power bicycle, starting at 50 W, increasing by 25 W every 3 minutes, until the maximum of 125 W reached. The subjects′ cardiac sounds and ECG signals at rest, 1 min after each level of load during exercise and 3 min after the end of exercise were selected; the transthoracic cardiac ultrasound examination of subjects was performed before and 5 min after exercise. The correlation between the cardiac sounds and ECG signals and left ventricular ejection fraction (LVEF) was analyzed, and a regression model was established to predict LVEF during exercise.Results:There were significant differences in heart rate, LVEF, electro-mechanical activation time (EMAT) and left ventricular ejection time (LVET) of subjects under different exercise loads ( F=53.22, 45.33, 3.65, 23.19, P<0.001, <0.001, =0.011, <0.001). Compared with the resting state, subjects showed increased heart rate and LVEF and a decreased EMAT and LVET during exercise loading, all of which were statistically significant ( P<0.01 or 0.05). In the correlation analysis, LVEF was negatively correlated with EMAT and LVEF ( r=-0.415, -0.758, P=0.002,<0.001), and positively correlated with the amplitude of the first heart sound ( r=0.606, P<0.001). The model for predicting LVEF was established by EMAT and LVET, and the multiple regression model was LVEF=108.698-0.092×LVET-0.134×EMAT ( r=0.87, P<0.001). Conclusions:The synchronous monitoring technology of cardiac sounds and ECG signals can continuously and non-invasively monitor LVEF changes during exercise. LVET is the most closely related to LVEF. LVEF is hopeful to predict the changes of cardiac function of astronauts in spaceflight activities.
