Open AccessStationary Bike Training Performance Using Heart Rate Variability
Author(s) -
Quoc Cuong Pham,
Tran Duc Minh Nguyen,
Dang Le Cao,
Quoc Khai Le,
Quang Linh Huynh
Publication year - 2020
Publication title -
kalpa publications in engineering
Language(s) - English
Resource type - Conference proceedings
ISSN - 2515-1770
DOI - 10.29007/j6zx
Subject(s) - overtraining , heart rate variability , heart rate , training (meteorology) , autonomic nervous system , stressor , computer science , adaptation (eye) , physical medicine and rehabilitation , psychology , medicine , physical therapy , athletes , blood pressure , neuroscience , physics , meteorology
Exercising is said to bring benefits to people taking part in, not only physical but also physiological gain. Heart Rate Variability (HRV) is an important marker reflecting the function of the autonomic nervous system (ANS), which has shown potentials in some exercise therapy and sport physiology studies. HRV analysis is said to be used for getting a better understanding of our body’s response to exercise and the reaction to different stressors from the workout. Thus, it is essential to monitor and optimize the recovery to avoid overtraining. This study aims to investigate the influence of HRV reflecting the physical stress level on participants when exercising, therefore, building a concept of self-training guide to improve the adaptation and performance. Electrocardiogram (ECG) is acquired by the BIOPAC system over 10 healthy college students during a proposed training protocol on the stationary bike, and post-exercising. HRV data from ECG is analyzed in time, frequency and nonlinear domains to extract various features to evaluate physiological recovery status, manage physical fatigue, intensity adjustment. From the evaluation of these indexes, participants are able to keep track of their physiological condition as well as to have more effective training exercises.