This paper presents a framework to explore the effect of music (motivational song) on cardiac physiology using recurrence analysis. For the characterization of the ECG signals, recurrence has been reported to be an effective tool. This non-linear dynamic method has been considered economical than other computational methods. The ECG data were acquired from eighteen male volunteers. The signals were further processed to extract the R-R intervals (RRI). Recurrence analysis of the ECG and the RRI signals suggested a reduction in the isometric recurrence in the post-stimulus condition, and hence, a corresponding increase in the heart rate variability. The variation was also evidenced from the ANN classification of the ECG and the RRI signals with efficiency of ≥ 85%. © 2017 IEEE.