NEURAL MECHANISM OF PHYSICAL EXERCISE IN PREVENTING AND TREATING CARDIOVASCULAR DISEASE BY DEEP LEARNING AND EDGE COMPUTING

Author:

XU HONG1,BAEKB SEUNG-SOO1ORCID

Affiliation:

1. Department of Physical Education, Sangmyung University, Jongno-gu 03016, Seoul, Korea

Abstract

This paper is to explore the improvement of clinical symptoms in patients with cardiovascular neurosis (CN) by physical exercise based on the deep learning architecture of edge computing, and to deeply explore the effect of physical exercise on autonomic function. Fifty-two patients with CN in this cardiovascular rehabilitation center were randomly divided into drug group and exercise group, with 26 cases in each group, and their electrocardiogram (ECG) was examined. Based on the deep learning architecture of edge computing, a four-layer stacked sparse auto encoder (SSAE) deep neural network was constructed, and the accuracy rates of least squares support vector machine (LSSVM), message passing neural network (MPNN), convolutional neural network (CNN), and SSAEs were measured to be 95.4%, 93.6%, 96.3%, and 99.5%, respectively. After physical exercise intervention, the total score of Symptom Checklist 90 (SCL-90) as well as each single item score were lower in the exercise group than in the drug group ([Formula: see text]). Heart rate recovery (HRR1) improved more significantly after 1[Formula: see text]min of exercise in patients in the exercise group ([Formula: see text]). The low-frequency (LF) power and normalized low-frequency (LFn) power of blood pressure variability (BPV) parameters in the exercise group were lower than those in the drug group ([Formula: see text]); the total power (TP), high-frequency (HF) power, and normalized high-frequency (HFn) power of heart rate variability (HRV) parameters in the exercise group were higher than those in the drug group ([Formula: see text]), LF/HF in the exercise group was lower than that in the drug group ([Formula: see text]); and the baroreflex sensitivity (BRS) in the exercise group was higher than that in the drug group ([Formula: see text]). A four-layer SSAEs was successfully constructed; the mechanism of exercise may be related to the regulation of cardiovascular autonomic nervous function, and it can effectively prevent and treat the clinical symptoms of patients with CN.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Biomedical Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

全球学者库

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"全球学者库"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前全球学者库共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2023 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3