alexa Real Time Fear Detection Using Wearable Single Channel Electroencephalogram
ISSN: 2090-4886

International Journal of Sensor Networks and Data Communications
Open Access

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Research Article

Real Time Fear Detection Using Wearable Single Channel Electroencephalogram

Surya Cheemalapati1, Prashanth Chetlur Adithya2, Michael Del Valle1, Michael Gubanov3* and Anna Pyayt1*

1Department of Chemical and Biomedical Engineering, University of South Florida, USA

2Department of Electrical Engineering, University of South Florida, USA

3Department of Computer Science, University of Texas at San Antonio, USA

*Corresponding Authors:
Mikhail Gubanov
Department of Computer Science, University of Texas
San Antonio, USA
Tel: 18139742011
E-mail: [email protected]
Anna Pyayt
Department of Chemical and Biomedical Engineering
University of South Florida, USA
Tel: 18139742011
E-mail: [email protected]

Received March 15, 2016; Accepted May 06, 2016; Published May 13, 2016

Citation: Cheemalapati S, Adithya PC, Valle MD, Gubanov M, Pyayt A (2016) Real Time Fear Detection Using Wearable Single Channel Electroencephalogram. Sensor Netw Data Commun 5:140. doi:10.4172/2090-4886.1000140

Copyright: © 2016 Cheemalapati S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Real time detection of emotional state has multiple applications for security, safety and identification of dangerous situations. Traditionally electroencephalogram (EEG) based emotion studies are conducted in controlled lab environment with multi-channel systems and large signal processing power. In order to be useful in real world situation the system for emotion detection has to be miniature, portable and working in real time supported by calculations that can be provided by a processor power of a mobile phone. Here we present our results on real time fear detection using portable single electrode EEG system conducted on 10 subjects. We studied possibility of translation of the markers previously identified for complex multi-electrode system - ratios of slow waves to fast waves into real time portable system. It was demonstrated using Student’s t-test that the average value of the monitored parameter during normal state was significantly higher than that of during a scary stimulus with a P value of (0.027) ~ 0.03 for Theta/ Beta. The framework for portable fear detection together with the markers discussed in this study can enable many applications important for the soldiers in the battlefield or police officers while being under attack as an indicator that help is urgently needed.


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