NDLI: Biometric identification using single channel EEG during relaxed resting state

Content Provider	IET Digital Library
Author	Suppiah, Ravi Vinod, Achutavarrier Prasad
Abstract	Brain signals have long been studied within various fields like medical, physiotherapy, and neurology for many years. One of the main reasons for this interest is to better understand brain diseases like Parkinson's, Schizophrenia, Alzheimer's, epilepsy, spinal cord injuries, and stroke among others. More recently, they have been used in brain–computer interface systems for rehabilitation, entertainment, and assistance applications. Even with the growing interest in clinical applications, the scientific community has only recently investigated the possibility of using brain signals as a potential biometric feature that can be used in people authentication and recognition systems. In this research, the authors have studied the use of brain signals acquired using electroencephalogram (EEG) during both eyes open and eyes closed states for identification based on a large dataset of 109 subjects. The use of a novel mind relaxation metric to determine the optimum epochs to select for the classification and verification has generated very high classification results, in the range of 97–99% based on a single channel. The approach has also been validated against another dataset to verify its consistency and repeatability. The results demonstrate that it is possible to move towards a single-channel biometric identification system with a very high level of reliability and accuracy.
Starting Page	342
Ending Page	348
Page Count	7
ISSN	20474938
Volume Number	7
e-ISSN	20474946
Issue Number	Issue 4, Jul (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/7/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2017.0142
Journal	IET Biometrics
Publisher Date	2017-10-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bioelectric Signal Biometric Feature Biomimetics Brain Diseases Brain Signal Brain-computer Interface Brain-computer Interfaces Classification Clinical Application Data Security Digital Signal Processing Diseases Electrodiagnostics And Other Electrical Measurement Technique Electroencephalogram Electroencephalography Eyes Closed State Eyes Open State Feature Extraction Mind Relaxation Metric People Authentication People Recognition System Relaxed Resting State Scientific Community Signal Classification Signal Processing And Detection Single Channel EEG Single-channel Biometric Identification System
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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