# Emotion Specification from Musical Stimuli: An EEG Study with AFA and DFA

arXiv: https://arxiv.org/abs/1705.00228 · HTML: https://mlsanity.com/paper/1705.00228/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Apr 2017.

## Built on by (most cited first, 3 of 3)

- [Neural Network architectures to classify emotions in Indian Classical Music](https://mlsanity.com/paper/2102.00616/) (2021)
- [Language Independent Emotion Quantification using Non linear Modelling of Speech](https://mlsanity.com/paper/2102.06003/) (2021)
- [A Fractal Approach to Characterize Emotions in Audio and Visual Domain: A Study on Cross-Modal Interaction](https://mlsanity.com/paper/2102.06038/) (2021)

## Abstract (arXiv)

The present study reports interesting findings in regard to emotional arousal based activities while listening to two Hindustani classical ragas of contrast emotion. EEG data was taken on 5 naive listeners while they listened to two ragas Bahar and Mia ki Malhar which are conventionally known to portray contrast emotions. The EEG data were analyzed with the help of two robust non linear tools viz. Adaptive Fractal Analysis (AFA) and Detrended Fluctuation Analysis (DFA). A comparative study of the Hurst Exponents obtained from the two methods have been shown which shows that DFA provides more rigorous results compared to AFA when it comes to the scaling analysis of biosignal data. The results and implications have been discussed in detail.