Objective. This work aimed to explore the application and optimization of the electrophysiological monitoring system to real-time monitor the exercise-induced fatigue (EIF) animals and investigate the intervention mechanism of hyperbaric oxygen (HBO) combined with natural astaxanthin (NAX) on EIF. Methods. First, a system was constructed for acquisition, processing, and feature extraction of electrocardiograph (ECG) signal and surface electromyography (EMG) signal for EIF monitoring. The mice were randomly divided into a control group (CG), EIF group (EG), HBO treatment (HBO) group, and HBO combined with NAX treatment (HBO + NAX) group. The effect of the constructed system on classification recognition of EIF was analyzed. The levels of serum antioxidative stress indicators of mice in each group were detected, including malondialdehyde (MDA), catalase (CAT), superoxide dismutase (SOD), glutathione (GSH), glutathione-peroxidation (GSH-Px), and total antioxidant capacity (T-AOC). In addition, the mRNA and protein levels of Keap1/Nrf2/HO-1 pathway related genes in liver tissue were detected. Results. The results showed that the normalized least mean squares algorithm effectively removed the motion artifact interference of ECG signal and can clearly display the signal peak, and high-pass filtering and power frequency filtering effectively removed the motion and baseline drift interference of surface EMG signal. The recognition sensitivity, specificity, and accuracy of the EIF recognition model based on the long- and short-term memory network were 90.0%, 93.3%, and 92.5%, respectively. Compared with the CG, the characteristics of ECG signal and surface EMG signal of the mice in the EIF group changed greatly (P < 0.05); the serum MDA level was increased obviously; the CAT, SOD, GSH, GSH-Px, and T-AOC levels were observably reduced (P < 0.05); the expressions of Keap1 and HO-1 in the liver were reduced remarkably, while the expression of Nrf2 was increased notably (P < 0.05). Compared with the EIF group, the characteristics of ECG signal and surface EMG signal of the mice in the HBO and HBO + NAX groups were obviously improved (P < 0.05); the serum MDA level was significantly reduced; the CAT, SOD, GSH, GSH-Px, and T-AOC levels were greatly increased (P < 0.05); the expressions of Keap1 and HO-1 in the liver were greatly increased, while the expression of Nrf2 was decreased sharply (P < 0.05). Conclusion. Therefore, the feature extraction and classification system of ECG signal combined with surface EMG signal could realize real-time monitoring of EIF status. HBO intervention could improve the body's ability to resist oxidative stress through the Keap1/Nrf2/HO-1 pathway and then improve the EIF state. In addition, the improvement effect of HBO + NAX was more obvious.
