Low cost EEG signal acquisition for health care and person identification

Abstract

The task of monitoring human health invasively and maintaining the security of any system is challenging in the current scenario. The proposed system integrates the health monitoring and biometric authentication for a healthy as well as secure world. The initial module comprises of analysing the change in EEG signals when blood pressure increases for the sick and elderly people while the latter module for security purposes. EEG signal is acquired from the subject. The acquiring of the signal undergoes several steps which include the filtering and amplification. The alpha wave which is unique is extracted, that avoids spoofing attacks is considered for biometry while the beta waves which alter the state according to the human mind state is considered for health monitoring. Data reduction along with SVM classifier and Hilbert transform is implemented in the proposed model.