Revista internacional de redes de sensores y comunicaciones de datos

Real Time Fear Detection Using Wearable Single Channel Electroencephalogram

Abstract

Surya Cheemalapati, Prashanth Chetlur Adithya, Michael Del Valle, Mikhail Gubanov and Anna Pyayt

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.