Abstract
The autonomic nervous system is important in maintaining homeostasis by mediating the opposing effects of the sympathetic and parasympathetic nervous activity on organs. Although it is known that the amplitude of RSA (Respiratory Sinus Arrhythmia) is an index of parasympathetic nervous activity, it is difficult to estimate that activity in real-time in everyday situations. It is partly caused by body motions and extrasystoles. Also, automatic recognition of the R-wave on electrocardiograms is required for real-time analysis of RSA amplitude, there is an unresolved problem of false recognition of the R-wave. In this paper, we propose a method to evaluate the amplitude of RSA accurately using statistical processing with probabilistic models. Then, we estimate parasympathetic nervous activity during body motion and isometric exercise to examine the validity of the method. As a result, using the proposed method, we demonstrate that the amplitude of RSA can be extracted with false recognition of the R-wave. In addition, an appropriate threshold for the estimate is one or five percent because waveforms of RSA amplitude do not follow the abrupt changes of the parasympathetic nervous activity evoked by isometric exercise with the threshold at ten percent. Furthermore, the method using normal distribution is found to be more appropriate than that of chi-square distribution for statistical processing. Therefore, we expect that the proposed method can evaluate parasympathetic nervous activity with high accuracy in everyday situations.
