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Determination of angry condition based on EEG, speech and heartbeat

Mohamed, Masnani and Lee, Ri Quan and Ahmad, Ida Laila and Hamid, Siti Hanira (2012) Determination of angry condition based on EEG, speech and heartbeat. International Journal on Computer Science and Engineering (IJCSE), 4 (12). pp. 1897-1909. ISSN 0975-3397

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This paper determines the angry emotion condition by analyzing and recognizing speech signal, EEG signal, as well as detecting the heartbeat. For the speech analyzing experiment, several digital signal processing methods such as autocorrelation and linear predication technique was introduced to analyze the features. Then, Artificial Neural Network (ANN) was used to classify each parameter features such as mean fundamental frequency, maximum fundamental frequency, standard deviation fundamental frequency, mean amplitude, pause length ratio and first formant frequency to recognize the emotion. For the EEG analysis, the raw EEG signal was undergone preprocessing to remove the artifacts to minimal. Some features as mean, standard deviation, the peak amplitude, the peak amplitude in alpha band (PAA) and the peak frequency in alpha band (PAF) of the EEG signals were extracted. The selected features were classified by using ANN to obtain the maximum classification accuracy rate. Meanwhile, a heartbeat monitoring circuit was developed to measure the heartbeat. The result showed that angry emotion has relatively low condition in mean value, maximum peak amplitude and relatively high peak frequency in alpha band (PAF) of the EEG signals. The mean fundamental frequency, standard deviation fundamental frequency and mean intensity of the speech signal are good in determining the angry emotion. This method can be used further to recognize angry emotion of patient during counseling session.

Item Type: Article
Uncontrolled Keywords: artificial neural network; digital signal processing; electroencephalogram (EEG); emotion recognition; emotional speech signal and heartbeat
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-5865 Telecommunication. Telegraph.
Divisions: Faculty of Electrical and Electronic Engineering > Department of Electronic Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 17 Dec 2014 08:21
Last Modified: 17 Dec 2014 08:21
URI: http://eprints.uthm.edu.my/id/eprint/6128
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