Analysis of ECG Signals to Investigate the Effect of a Humorous Audio-Visual Stimulus on Autonomic Nervous System and Heart of Females

Abstract

This chapter is an attempt to understand the effect of audio-visual stimulus with a humorous content on the cardiac electrophysiology. Electrocardiogram (ECG) signals were acquired from 11 female volunteers under the pre- and the post-stimulus conditions. Artificial neural network (ANN)-based classification of the ARMA model coefficients computed from the RR interval signals suggested significant variation in the autonomic nervous system activity. Analysis of the Gabor denoised ECG signals indicated a change in the electrical activity of the heart in the post-stimulus condition, which was confirmed by the ANN-based classification. Recurrence analysis of the RR interval suggested plausible differences of the cardiac activity amongst both the conditions. The audio-visual stimulus has resulted in significant alterations in the ANS and the cardiac physiology.

A Review of Methods and Applications for a Heart Rate Variability Analysis

“…A number of parametric modelling approaches, including autoregressive (AR), moving average (MA), autoregressive moving average (ARMA), and autoregressive integrated moving average (ARIMA), have been proposed for the analysis of RR intervals [56]. AR, MA, and ARMA models have been used to analyze RR intervals of a small duration (e.g., 5 s) [57]. This may be attributed to the stationary nature of the small-duration RR intervals.…”