Eyes Open and Eyes Close Activity Recognition Using EEG Signals

  • Barjinder Kaur
  • Dinesh Singh
  • Partha Pratim Roy
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 801)


So far Electroencephalography (EEG) has been analyzed by the re- search community for interaction with the computers. Studies regarding EEG signals has gained attention in the recent past as it gives an alternate way of com- munication for the persons suffering from partially or fully paralytic disability. Every second different activities are performed by millions of neurons. Decoding and detecting such complex activity of the brain while analyzing the EEG signals is a challenging task. In this paper, we have proposed an activity recognition system using EEG signals. The two activities, namely, eyes open (EO) and eyes close (EC) have been considered in this work. The recorded signals are then decomposed using Discrete Wavelet Transform (DWT) to analyze the impact of both the activities. The recognition of activities has been performed using Support Vector Machine (SVM) classifier. For experimentation, a publicly available dataset i.e. PhysioNet consisting data of 109 users while performing one minute EO and EC activity has been used. A notable activity recognition rate of 86.08% has been recorded using gamma band feature. The paper further proposes that the system can be used as a reference to detect different types of activities performed at different instance of time and for rehabilitation purposes also.


Electroencephalography (EEG) Eyes open (EO) Eyes close (EC) Discrete Wavelet Transform (DWT) Support Vector Machine (SVM) 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.DCRUSTSonepatIndia
  2. 2.IIT RoorkeeRoorkeeIndia

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