EEG based pattern recognition method for classification of different mental tasking: preliminary study for stroke survivors in Indonesia
This paper presents a result of pattern recognition method for different mental tasking of 8 volunteers. The EEG data used in this paper were acquired from 8 Indonesian volunteer using Emotiv EEG device with 16 channels. 24 feature extraction methods including time-domain and statistical features are applied to the EEG signal. An artificial neural network (ANN) is employed for classification. This is the preliminary study in developing a pattern recognition method for body prosthetic and wheelchair to disability person. The paper aims to investigate the reliable EEG signal from 14 channels. The results show that among 14 EEG channels, channel F7 and F8 are better in classification than other channels. The test classification of channel F7 and F8 is 66.7%.
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