Effect of heat exposure on pulse wave dynamics using pulse rate variability

Heat stress is a well-known stressor that causes heat illnesses. Heat stress causes significant cardiovascular changes needed for temperature control through vasodilation and sweating. Therefore, the objective was to assess photoplethysmogram (PPG)-derived pulse rate variability (PRV) characteristics for predicting heat stress in a preclinical model. Ten male Wistar rats (10-12 weeks old) were divided into control (<i>n </i>= 5) and experimental (<i>n </i>= 5) groups. The subjects were exposed to 38 ± 1 °C and 24 ± 1 °C for 30 minutes daily for five consecutive days. The rectal temperature, electrocardiogram (ECG), and PPG signals were recorded after the 5th day of exposure. Pulse rate variability (PRV) was analyzed using time-domain, frequency-domain, and nonlinear metrics derived from PPG signals. Pulse arrival time (PAT) was estimated from synchronized ECG-PPG recordings and used to compute pulse wave velocity (PWV). A Naive Bayes classifier was trained using selected PRV features to distinguish heat stress from control conditions. The core body temperature increased by 0.5 °C (<i>p</i> < 0.05) under elevated heat stress for five consecutive days. The results also indicated a reduction in PRV under heat stress, suggesting increased sympathetic and withdrawal of parasympathetic activity, highlighting the physiological alterations induced by heat stress. A slight increase in pulse wave velocity (PWV) was also observed, revealing minimal heat-related changes in arterial stiffness. Further, the PRV parameters-based Naive Bayes algorithm demonstrated an accuracy of 94.58% in the prediction of the heat stress event. The findings highlighted the withdrawal of parasympathetic activity and the potential of PPG-derived parameters as a modality for predicting heat stress events.