An Efficient FPGA Realization of Seizure Detection from EEG Signal Using Wavelet Transform and Statistical Features

Abstract

Abnormal electrical activity of a group of brain cells is known as seizure. Electroencephalogram (EEG) is most commonly used for the detection of seizure. This paper presents an efficient method for seizure detection from EEG signal using wavelet transform and statistical features in Field Programmable Gate Array (FPGA). A hardware efficient multiplierless architecture of 3/5 B-Spline wavelet transform is used for subband decomposition. Variance, standard deviation, mean energy, maximum amplitude, skewness, and kurtosis are the various features analyzed. There is a significant difference in the feature values obtained from EEG database of patient and a normal individual. The classifier used to classify the selected features is support vector machine classifier. Confusion matrix is used for measuring the accuracy of the proposed classifier. The system has two phases named training phase and testing phase. In order to train the system in the training phase EEG database of both epileptic seizure affected and normal individual is given. In the testing phase, the system will detect the presence or absence of seizure in the inputted EEG database. It is possible to fully place and route the detection system in an FPGA. The system is verified by Verilog in ISim simulator and synthesized in Virtex 6.

Keywords:

• 3/5 B-spline wavelet
• Discrete wavelet transform (DWT)
• Electroencephalogram (EEG)
• Feature classification
• Feature extraction
• Field programmable gate array (FPGA)
• Support vector machine (SVM)

Additional information

Notes on contributors

V. Geethu

V Geethu received the BTech degree in electronics and communication Engineering from Cochin University of Science and Technology, India in 2015 and the MTech in VLSI and embedded systems from the Department of Electronics, Government Engineering College Idukki, APJ Abdul Kalam Technological University, Kerala, India in 2017. Corresponding author. Email: [email protected]

S. Santhoshkumar

S Santhoshkumar completed his BTech in electronics and communication from College of Engineering Trivandrum in 1994 and MTech from College of Engineering Trivandrum in 1997. He has completed his PhD from Kerala University in 2011. He has worked as Scientific Officer in Centre for Development of Imaging Technology from 1997 to1999 and joined as lecturer in College of Engineering Trivandrum in 1999 and currently working as Associate Professor, Government Engineering College, Painavu, Idukki. Email: [email protected]