Emotion Classification by EEG Signal Generated by Brain using Discrete Wavelet Transform and Artificial Neural Network Backpropagation with Classical Music Stimulus

Author:

Dimas Aditya

Abstract

People feel different emotions when listening to music on certain levels. Such feelings occur because the music stimuli causing reduced or increased brain activity and producing brainwave with specific characteristics. Results of research indicated that classical piano music can influence one’s emotional intelligent. By using Electroenchephalography (EEG) as a brainwave recording instrument, we can assess the effect of stimulation on the emotions generated through brain activity. This study aimed at developing a method that defines the effect of sound to brain activity using an EEG signal that can be used to identify one's emotion based on classical piano music stimulus reaction. Based on its frequency, this signal was the classified using DWT. To train Artificial Neural Network, some features were taken from the signal. This ANN research was carried out using the process of backpropagation

Publisher

Universitas Teknologi Yogyakarta

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Swarm Intelligence-Based Feature Selection Algorithm of EEG Classification for Brain Emotion Detection: A Review;2023 IEEE 8th International Conference for Convergence in Technology (I2CT);2023-04-07

2. Piano Music Teaching under the Background of Artificial Intelligence;Wireless Communications and Mobile Computing;2022-01-24

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