http://iet.metastore.ingenta.com
1887

Biometric identification using single channel EEG during relaxed resting state

Biometric identification using single channel EEG during relaxed resting state

For access to this article, please select a purchase option:

Buy eFirst article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
— Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

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.

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-bmt.2017.0142
Loading

Related content

content/journals/10.1049/iet-bmt.2017.0142
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address