TY  - CONF
SN  - 18770509
PB  - Elsevier B.V.
Y1  - 2016///
VL  - 105
EP  - 143
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016117896&doi=10.1016%2fj.procs.2017.01.193&partnerID=40&md5=ab458fc20be264df17698328d6845cd6
A1  - Kannan, R.
A1  - Ali, S.S.A.
A1  - Farah, A.
A1  - Adil, S.H.
A1  - Khan, A.
AV  - none
KW  - Brain; Computer programming languages; Electroencephalography; Software prototyping; Wearable sensors
KW  -  'current; Brain disease; Clinical environments; Ear-EEG; Electrical activities; LabVIEW; Natural environments; Patient's suffering; Smart wearables; Social acceptability
KW  -  Electrophysiology
TI  - Smart Wearable EEG Sensor
SP  - 138
ID  - scholars7356
N2  - 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.
N1  - cited By 6; Conference of IEEE International Symposium on Robotics and Intelligent Sensors, IRIS 2016 ; Conference Date: 17 December 2016 Through 20 December 2016; Conference Code:134518
ER  -