An improved method to evaluate heart rate variability based on time-variant cardiorespiratory relation

Сardiorespiratory relationships in people of young age depending on the composite composition of the body

BACKGROUND: The decisive importance of the sympathetic and parasympathetic nervous system in maintaining vegetative homeostasis requires the determination of sensitive non-invasive parameters of multidimensional outpatient monitoring of cardiorespiratory adaptation under various physiological and clinical conditions, taking into account the function of external respiration (FER), compound body composition and heart rate variability (HRV).

AIM: To identify concomitant changes in HRV, HR and compound body composition in young people as markers of cardiorespiratory adaptation and rehabilitation.

MATERIALS AND METHODS: On the basis of the Kuban State Medical University, a single-centre, interventional, cross-sectional, single-sample, comparative, uncontrolled study of a general group of young people in which respiratory parameters and parameters of the compound body composition were determined. Some individuals in this group additionally underwent Holter monitoring of the electrocardiogram (ECG) at short intervals.

RESULTS: In young people, a change in the compound body composition with an increase in total fat mass, visceral and body fat is associated with a decrease in respiratory function (a decrease in the Tiffno index, a decrease in the maximum middle-expiratory flow — MMEF), manifested by a decrease in HRV (according to the TI indicator), the absence of an increase in the autonomic regulation circuit (according to SDNN indicator), a decrease in parasympathetic activity (in terms of rMSSD) and the absence of sympathetic activation (in terms of SDANN). Positive shifts in the form of an increase in trunk muscles, the total amount of water and a decrease in the total fat mass are accompanied by an increase in lung capacity, forced expiratory volume in the first second and a change in HRV with sympathetic (in terms of LF / HF, SDANN) and parasympathetic activation (in terms of rMSSD), an increase in HRV (in terms of TI) and an increase in the autonomic regulation circuit of the vegetative nervous system (in terms of SDNN).

CONCLUSION: Accurate and rapid diagnostics of vegetative homeostasis requires a comprehensive correlative analysis of the parameters characterizing HRV in short recordings, the compound composition of the human body and respiratory function.

The Assessment of Autonomic Nervous System Activity Based on Photoplethysmography in Healthy Young Men

Noninvasive assessment of autonomic nervous system (ANS) activity is of great importance, but the accuracy of the method used, which is primarily based on electrocardiogram-derived heart rate variability (HRV), has long been suspected. We investigated the feasibility of photoplethysmography (PPG) in ANS evaluation. Data of 32 healthy young men under four different ANS activation patterns were recorded: baseline, slow deep breathing (parasympathetic activation), cold pressor test (peripheral sympathetic activation), and mental arithmetic test (cardiac sympathetic activation). We extracted 110 PPG-based features to construct classification models for the four ANS activation patterns. Using interpretable models based on random forest, the main PPG features related to ANS activation were obtained. Results showed that pulse rate variability (PRV) exhibited similar changes to HRV across the different experiments. The four ANS patterns could be better classified using more PPG-based features compared with using HRV or PRV features, for which the classification accuracies were 0.80, 0.56, and 0.57, respectively. Sensitive features of parasympathetic activation included features of nonlinear (sample entropy), frequency, and time domains of PRV. Sensitive features of sympathetic activation were features of the amplitude and frequency domain of PRV of the PPG derivatives. Subsequently, these sensitive PPG-based features were used to fit the improved HRV parameters. The fitting results were acceptable (p < 0.01), which might provide a better method of evaluating ANS activity using PPG.