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

Area of Science:

• Physiology
• Cardiovascular Research
• Biomedical Engineering

Background:

• Heat stress poses significant health risks, leading to heat illnesses.
• Cardiovascular adjustments, including vasodilation and sweating, are crucial for thermoregulation during heat stress.
• Non-invasive monitoring of physiological responses to heat stress is essential for early detection and prevention.

Purpose of the Study:

• To evaluate the efficacy of photoplethysmogram (PPG)-derived pulse rate variability (PRV) metrics for predicting heat stress.
• To investigate the cardiovascular alterations associated with heat stress in a preclinical model.
• To develop a predictive model for heat stress events using PRV characteristics.

Main Methods:

• Wistar rats were exposed to elevated temperatures (38°C) daily for five consecutive days.
• Rectal temperature, electrocardiogram (ECG), and PPG signals were recorded.
• PRV was analyzed using time-domain, frequency-domain, and nonlinear metrics; Pulse Wave Velocity (PWV) was calculated from ECG-PPG.
• A Naive Bayes classifier was trained using PRV features to differentiate heat stress from control conditions.

Main Results:

• Core body temperature increased significantly (0.5°C, p<0.05) in the heat-stressed group.
• A reduction in PRV was observed under heat stress, indicating increased sympathetic and reduced parasympathetic activity.
• Pulse wave velocity (PWV) showed a slight increase, suggesting minimal arterial stiffness changes.
• The Naive Bayes algorithm achieved 94.58% accuracy in predicting heat stress events based on PRV parameters.

Conclusions:

• Heat stress induces significant physiological alterations, including changes in autonomic nervous system activity.
• PPG-derived PRV parameters are valuable indicators of heat stress.
• The developed Naive Bayes model demonstrates the potential of PPG-based analysis for non-invasive heat stress prediction.