Neural Jitter-Shimmer and Extraction of Pitch from EEG Signals

Abstract

In this concluding chapter, the main emphasis is on the development of new features of EEG signal analysis—neural jitter/shimmer and pitch of EEG signals, which can lead to interesting observations in the domain of musical emotion analysis. The terms jitter, shimmer and pitch has long been used in the domain of speech and acoustic signal analysis as a parameter for speaker identification and other prosodic features. In this chapter, we look forward to use the same parameters in neural domain to identify and categorize emotional cues in different musical clips. Jitter conventionally refers to the variability of fundamental frequency while shimmer refers to the variability in the peak to peak amplitude. Applying the same concept to neural EEG domain, we have termed this as neural-jitter and neural-shimmer. In music signal processing, pitch in general refers to the fundamental frequency of a sound wave albeit having a subjective component that takes into account the relative placement of the frequency within the context of an established tuning system and in relation to other frequencies. Applied to EEG signal analysis, we use the same parametric to find the number of zero crossings per second in alpha, theta and gamma bands of EEG signal. For this, we chose same two pair of ragas of Hindustani music as in Chap. 1, which are conventionally known to portray contrast emotions and EEG study was conducted on 20 participants who were made to listen to 3 min clip of these two ragas with sufficient resting period in between. The neural jitter and shimmer components were evaluated for each experimental condition in the alpha theta and gamma frequency bands corresponding to the different lobes of human brain. The neural jitter is a subjective parameter which is very much dependent on the state of consciousness of a particular person and thus remains mostly unaffected by any type of emotional music stimuli. In the domain music signal analysis, jitter has largely been used as a parameter which defines the timbral characteristic of a musical instrument. In the same way, we propose to use neural jitter as a parameter which defines the state of consciousness of a human being. The neural shimmer, on the other hand, reveals interesting data regarding the arousal and retention of different emotions in human brain. In the alpha and gamma frequency range, elevated levels of neural shimmer are representation of positive emotion while diminished levels are marker for negative emotion. The retention is higher in case of positive emotion as compared to negative. A probability distribution of fundamentals is also obtained in different EEG bands to explore the possibility of existence of a preferred fundamental under the effect of any emotional music. This novel study can have far reaching conclusions if utilized for quantification and categorization of emotional arousal in respect to Hindustani classical music.