Why the study?
The generation mechanism of the low-frequency component of heart rate variability remains controversial, despite HRV being a candidate for objectively measuring emotions in biosignal applications.
A novel mathematical model successfully simulates the complex interactions between emotion, respiration, and heart rate variability, suggesting mechanisms for the generation of the low-frequency component of HRV.
Simulation model reproduces LF-HRV emotion patterns; leaves open human validation before biosignal applications.
Although the generation mechanism of the low-frequency (LF) component of heart rate variability (HRV) is controversial, HRV is a potential candidate in designing objective measurement methodologies for emotions. These methodologies could be valuable for several biosignal applications. Here, we have conducted a simulation analysis using a novel mathematical model that integrates emotion, respiration, the nervous system, and the cardiovascular system. Our model has well reproduced experimental results, specifically concerning HRV with respiratory sinus arrhythmia and LF, the relation between HRV total power and the respiration frequency, and the homeostatic maintenance by the baroreflex. Our model indicates the following possibilities: (i) The delay in the heart rate control process of the parasympathetic activity works as a low-pass filter and the HRV total power decreases with a higher respiration frequency; (ii) the LF component of HRV and the Mayer wave are generated as transient responses of the baroreflex feedback control to perturbations induced by an emotional stimulus; and (iii) concentration on breathing to reduce the respiration frequency can reduce LF/HF and the reduction can be fed back to the emotional status.
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HIRABAYASHI et al. (2019) studied this question.
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