Abstract
With the advent of various techniques to assess the bioelectric signals on the surface of the body, it has become possible to develop various Human–Computer interface systems. In this study, for the first time a cross-correlation based data is reported for two different types of bio-signals, viz. Electroencephalography (EEG) and Electromyography (EMG). Whereas EEG refers to the neuro-electric impulses generated in the brain recorded in the form of electric potentials, EMG records the activation potentials of the muscle cells when they contract or relax. The ability of Hindustani Music (HM) to evoke a wide range of emotional experience in its listeners is widely known. For this study, we took simultaneous EEG and EMG data of 5 participants while they listened to two Hindustani ragas of contrast emotions namely Chayanat (corresponding to happy/joy) and Darbari Kanada (corresponding to sad/pathos) emotion. We make use of two latest signal processing algorithms—Wavelet-based power spectra and cross-correlation coefficient to assess the arousal based activities in response to the acoustic clips in the two different bio-signals. For the first time, an attempt is being made to quantify and categorize musical emotions using EMG signals and an attempt to correlate that with the EEG signals obtained from the brain. The alpha, theta, and gamma frequency range in the frontal and parietal electrodes is found to be the most responsive in case of musical emotions. The EMG response has been studied by segregating the entire signal into different frequency ranges as is done in case of EEG frequency bands. Interestingly, the response in case of EMG data is strongest in the same frequency bands as that of EEG signals. Novel pitch detection algorithm has also been applied to EMG signals to ratify the rationale behind the separation of frequency bands. This is the first of its kind study which looks for categorization and quantification of musical emotions using simultaneously two different bio-signals with the help of robust mathematical analysis. The results and implications have been discussed in detail.
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Acknowledgments
SS acknowledges the JU RUSA 2.0 Post Doctoral Fellowship (R-11/557/19) and Acoustical Society of America (ASA) to pursue this research AB acknowledges the Department of Science and Technology (DST), Govt. of India for providing (SR/CSRI/PDF-34/2018) the DST CSRI Post Doctoral Fellowship to pursue this research work. This study has been conducted under the guidelines of Ethical Committee of Jadavpur University (Approval No. 3/2013).
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Sarkar, U. et al. (2021). A Simultaneous EEG and EMG Study to Quantify Emotions from Hindustani Classical Music. In: Singh, M., Rafat, Y. (eds) Recent Developments in Acoustics. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-5776-7_26
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DOI: https://doi.org/10.1007/978-981-15-5776-7_26
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