A Classification of EEG Signals Of Eye-Open and Eye-Closed Using Neural Network - Goregaonkar, Mrinmai Bhalchandra (International Journal of Computer Sciences and Engineering, 2019)
EEG (electroencephalography) is a famous modality to study the appearance of electrical activity over the scalp. This paper includes an experiment which gives 90% accuracy of recorded signals. In this experiment, classification is done in the open eye or closed eye. These signals are decomposed by using DWT into the sub-band frequencies. Then features are extracted from these frequencies. By these features, the classification will carry out by using the ANN classifier. Classification accuracy is a useful content that gives the reliability to perform the imagined movements.