Smart Wearable EEG Sensor

Currently, traditional and ambulatory EEG systems are beyond ideal for patients suffering from different brain diseases. Traditional monitoring of electrical activity in a diseased brain is limited to the clinical environment where patients being put away from natural environment in which provoking...

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Main Authors: Kannan, R., Ali, S.S.A., Farah, A., Adil, S.H., Khan, A.
Format: Article
Published: Elsevier B.V. 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016117896&doi=10.1016%2fj.procs.2017.01.193&partnerID=40&md5=ab458fc20be264df17698328d6845cd6
http://eprints.utp.edu.my/20316/
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spelling my.utp.eprints.203162018-04-23T01:04:11Z Smart Wearable EEG Sensor Kannan, R. Ali, S.S.A. Farah, A. Adil, S.H. Khan, A. Currently, traditional and ambulatory EEG systems are beyond ideal for patients suffering from different brain diseases. Traditional monitoring of electrical activity in a diseased brain is limited to the clinical environment where patients being put away from natural environment in which provoking factors of abnormalities in the electrical activity of the brain are more likely to occur. Similarly, ambulatory EEG systems have a drawback of being cumbersome and impose some restrictions on the patient, such as not being able to show in public due to the social acceptability of wearing such a head-mounted device. The will of the patients to not publicizing their disorder or illnesses is a major drawback for current EEG system to be widely adopted. This paper presents an attempt to develop a wearable EEG prototype using off-the-shelf components to record EEG signal from the ear and display the obtained brain signals in the LabVIEW software. The developed prototype was able to record Ear-EEG in real-time. © 2017 The Authors. Elsevier B.V. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016117896&doi=10.1016%2fj.procs.2017.01.193&partnerID=40&md5=ab458fc20be264df17698328d6845cd6 Kannan, R. and Ali, S.S.A. and Farah, A. and Adil, S.H. and Khan, A. (2017) Smart Wearable EEG Sensor. Procedia Computer Science, 105 . pp. 138-143. http://eprints.utp.edu.my/20316/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Currently, traditional and ambulatory EEG systems are beyond ideal for patients suffering from different brain diseases. Traditional monitoring of electrical activity in a diseased brain is limited to the clinical environment where patients being put away from natural environment in which provoking factors of abnormalities in the electrical activity of the brain are more likely to occur. Similarly, ambulatory EEG systems have a drawback of being cumbersome and impose some restrictions on the patient, such as not being able to show in public due to the social acceptability of wearing such a head-mounted device. The will of the patients to not publicizing their disorder or illnesses is a major drawback for current EEG system to be widely adopted. This paper presents an attempt to develop a wearable EEG prototype using off-the-shelf components to record EEG signal from the ear and display the obtained brain signals in the LabVIEW software. The developed prototype was able to record Ear-EEG in real-time. © 2017 The Authors.
format Article
author Kannan, R.
Ali, S.S.A.
Farah, A.
Adil, S.H.
Khan, A.
spellingShingle Kannan, R.
Ali, S.S.A.
Farah, A.
Adil, S.H.
Khan, A.
Smart Wearable EEG Sensor
author_facet Kannan, R.
Ali, S.S.A.
Farah, A.
Adil, S.H.
Khan, A.
author_sort Kannan, R.
title Smart Wearable EEG Sensor
title_short Smart Wearable EEG Sensor
title_full Smart Wearable EEG Sensor
title_fullStr Smart Wearable EEG Sensor
title_full_unstemmed Smart Wearable EEG Sensor
title_sort smart wearable eeg sensor
publisher Elsevier B.V.
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016117896&doi=10.1016%2fj.procs.2017.01.193&partnerID=40&md5=ab458fc20be264df17698328d6845cd6
http://eprints.utp.edu.my/20316/
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score 13.22586