Status change revealed by electrocardiography (ECG) and electroencephalography (EEG) during cycling exercise

Long-term aerobic exercise can effectively improve the heart and lung function, stabilize mood and reduce the incidence of cardiopulmonary diseases. Brain activity can properly reflect physical and mental status of subjects during prolonged exercise, and long-term exercise may affect the power spectrum of EEG. Many studies showed that ECG, EMG and EEG, can effectively and accurately assess the status change during exercise. Safety and efficiency are the main concerns for promoting the aerobics for the elder. In this study, we aim to investigate the EEG and ECG features that can reveal status change during cycling exercise. Twenty-nine healthy subjects participated in this study. After four-minute resting stage, participants were asked to take cycling exercise continuously for twenty minutes, and the EEG, ECG signals were recorded and analyzed. The EEG data were divided into one-minute epoch and the wavelet transform was used to analyze five frequency bands, namely, theta (T), low alpha (LA), high alpha (HA), low beta (LB) and high beta (HB). The ECG signal was used to establish the average maximum heart rate ratio (AMHRR) and cardiac stress index (CSI). We found variations of RR intervals decreases during sustained cycling exercise. The CSI plot of a less frequent exerciser showed steeper than a frequent exerciser. If a participant has a steeper slope of CSI curve may imply an increase in cardiac stress. The AMHRR score at 65% could be a threshold for the occurrence of feeling hard during exercise. The CSI, HA and LB are the most proper features for assessing status change during exercise.