Abstract
Respiratory sinus arrhythmia (RSA) is a phenomenon in which the heart rate (HR) changes with respiration, increasing during inspiration and decreasing during expiration. RSA biofeedback training has an effect in relieving negative mental conditions, such as anxiety and stress. Respiration is an important indicator affecting the parasympathetic activation within the body during RSA biofeedback training. Although there are existing studies that consider individual differences when selecting optimized respiration using heart rate variability, the studies that use the high frequency components of HRV, which is an indicator of parasympathetic activation, are insufficient. For this reason, this paper proposes a process to identify optimized respiration for efficient RSA feedback, consisting of three steps: (1) application, (2) optimization, and (3) validation. In the application phase, we measured PPG data against various respiratory cycles based on the HF components of HRV and calculated the proposed heart stabilization indicator (HSI) from the data. Then, we determined the optimized respiration cycle based on the HSI in the optimization step. Finally, we analyzed seven stress-related indices against the optimized respiration cycle. The experimental results show that HSI is associated with the parasympathetic nervous system activation, and the proposed method could help to determine the optimal respiratory cycle for each individual. Lastly, we expect that the proposed design could be used as an alternative to improving the efficiency of RSA biofeedback training.
Highlights
Publisher’s Note: MDPI stays neutralOccupations that require much psychological attention over a long time can cause emotional and psychological distress
The Respiratory sinus arrhythmia (RSA) is related to parasympathetic nervous activity, which is regulated by the vagal tone that changes heart rate variability (HRV) through activation [9,10,11,12,13,14]
Others suggested that there are differences in the rhythm of regular breathing between individuals [48,49,50]. From this point of view, this study proposed a process to find the breathing cycle optimized for the individual to improve the effectiveness of the RSA biofeedback, which consists of three processes: application, optimization, and validation
Summary
Publisher’s Note: MDPI stays neutralOccupations that require much psychological attention over a long time (e.g., telemarketers and service personnel) can cause emotional and psychological distress. Activities [1,2,3] Such as meditation (e.g., yogic therapy) can help to reduce the level of this stress in individuals. Yoga therapy uses spontaneous breathing and optimal breathing to maintain homeostasis of relaxation and rest. Studies on yoga breathing have shown that the practice of deep breathing (DB) strongly affects the human nervous system, especially the parasympathetic nervous system [2,4,5]. We call the fluctuations of the R–R interval RSA during this respiratory cycle, which means a cardiopulmonary response that changes the heart rate. The RSA is related to parasympathetic nervous activity, which is regulated by the vagal tone that changes heart rate variability (HRV) through activation [9,10,11,12,13,14]
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