Nonlinear Signal Processing Method Detects Emotional Changes Induced by Indian Classical Music
Sushrutha Bharadwaj M1, Shantala Hegde2, D Narayana Dutt3, Anand Prem Rajan4
1Sushrutha Bharadwaj M*, Department of Medical Electronics, Dayananda Sagar College of Engineering, Bangalore, India.
2Shantala Hegde, Music Cognition Laboratory, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India.
3D. Narayana Dutt, Department of Medical Electronics, Dayananda Sagar College of Engineering, Bangalore, India.
4Anand Prem Rajan, School of Biosciences and Biotechnology, VIT University, Vellore, India.
Manuscript received on September 21, 2019. | Revised Manuscript received on October 05, 2019. | Manuscript published on October 30, 2019. | PP: 6200-6206 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1853109119/2019©BEIESP | DOI: 10.35940/ijeat.A1853.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Music is one of the major activities that alters the emotional experience of a person. Musical processing in the brain is a complex process involving coordination between various areas of the brain. There are less number of studies that focus on analyzing brain responses due to music using modern signal processing techniques. This research aims to apply a nonlinear signal processing technique i.e. the Recurrence Quantification Analysis (RQA) technique to analyze the brain correlates of happy and sad music conditions while listening to happy and sad ragas of North Indian Classical Music (NICM). EEG signals from 20 different subjects are acquired while listening to excerpts of raga elaboration phases of NICM. Along with behavioural ratings, the signals were analyzed using the Recurrence Quantification Analysis technique. The results showed significant differences in the recurrence plot and recurrence parameters extracted from the frontal and fronto temporal regions in the right and left hemispheres of the brain. Therefore, from the results, it can be concluded that RQA parameters can detect emotional changes due to happy and sad music conditions.
Keywords: Classical Music, EEG, Happy and sad emotions, Music and cognition, Nonlinear analysis, RQA.