Thermal comfort is a personal assessment of one's satisfaction with the surroundings. Yet, most thermal comfort delivery mechanisms preclude physiological and psychological precursors to thermal comfort. Accordingly, many people feel either cold or hot in an environment that is supposedly thermally comfortable to most people. To address this issue, this paper proposes to use people's heart rate variability (HRV) as an alternative indicator of thermal comfort. Since HRV is linked to homeostasis, we hypothesize that it could be used to predict people's thermal comfort status. To test our hypothesis, we analyzed statistical, spectral, and nonlinear HRV indices of 17 human subjects doing light office work in a cold, a neutral, and a hot environment. The resulting HRV indices were used as inputs to machine learning classification algorithms. We observed that HRV is distinctively altered depending on the thermal environment and that it is possible to steadfastly predict each subject's thermal environment (cold, neutral, and hot) with up to a 93.7% prediction accuracy. The result of this study implies that it could be possible to design automatic real-time thermal comfort controllers based on people's HRV.

Objectives: When either ventricular myocardium becomes ischemic or autonomic nervous system activity changes with age, the relationship between ventricular repolarization duration and RR interval will change as well. We studied the relationship between ventricular repolarization duration and RR interval among normal subjects in different age groups and between patients with myocardial infarction (MI) and age-matched healthy subjects. Methods: Ventricular repolarization duration variability (RDV) spectra were separated into RR-dependent and RR-independent components. We compared spectral measures among normal subjects in different age groups and between patients with MI and age-matched healthy subjects. Results: The RR-dependent component of RDV spectra, which is correlated with autonomic nervous system activity, significantly decreased with age for healthy subjects. The RR-independent component significantly increased in MI patients compared to age-matched healthy subjects. Conclusions: We demonstrated the increase in RDV upon decreasing age and in the presence of MI. Our results support the idea that the RR-dependent part corresponds to the physiology-related part of the RDV spectra and the RR-independent part corresponds to the pathology-related part of the RDV spectra. Our study suggests that these spectral measures are likely to be helpful in the evaluation of a patient with MI and merit further investigation.