Development of efficient algorithm to detect and classify alpha activity in real-time EEG signal using LabVIEW for mental state detection

Ahsen Mubarik Ali; Amir M. Abdulghani

doi:10.1109/IEMCON.2017.8117172

Development of efficient algorithm to detect and classify alpha activity in real-time EEG signal using LabVIEW for mental state detection

Ahsen Mubarik Ali^*, Amir M. Abdulghani

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The paper proposes an algorithm to process Alpha activity in real-time electroencephalogram signal using LabVIEW for mental state detection. The electroencephalogram signals from occipital region have direct relationship with the state of mind which can be utilized by physically challenged individuals to control their surrounding environment, providing an extent of independency. Being independent reduces the stress level which results in a boost in both neural system as well as the immune system, giving a higher chance of recovery and preventing the physically challenged individuals from further sicknesses. The relaxed state of mind exhibits pronounced alpha activity which is continuously varying and appears as aperiodic boosts. The projects aims to efficiently detect alpha activity in real-time electroencephalogram signal for mental state interpretation of the user and produce reliable results.

Original language	English
Title of host publication	2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	411-415
Number of pages	5
ISBN (Electronic)	9781538633717
DOIs	https://doi.org/10.1109/IEMCON.2017.8117172
Publication status	Published - Nov 21 2017
Event	8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017 - Vancouver, Canada Duration: Oct 3 2017 → Oct 5 2017

Other

Other	8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017
Country/Territory	Canada
City	Vancouver
Period	10/3/17 → 10/5/17

Keywords

Alpha activity
Brain computer interface
EEG

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Software
Electrical and Electronic Engineering
Instrumentation

Access to Document

10.1109/IEMCON.2017.8117172

Cite this

Ali, A. M., & Abdulghani, A. M. (2017). Development of efficient algorithm to detect and classify alpha activity in real-time EEG signal using LabVIEW for mental state detection. In 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017 (pp. 411-415). [8117172] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEMCON.2017.8117172

Development of efficient algorithm to detect and classify alpha activity in real-time EEG signal using LabVIEW for mental state detection. / Ali, Ahsen Mubarik; Abdulghani, Amir M.
2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 411-415 8117172.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ali, AM & Abdulghani, AM 2017, Development of efficient algorithm to detect and classify alpha activity in real-time EEG signal using LabVIEW for mental state detection. in 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017., 8117172, Institute of Electrical and Electronics Engineers Inc., pp. 411-415, 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017, Vancouver, Canada, 10/3/17. https://doi.org/10.1109/IEMCON.2017.8117172

Ali AM, Abdulghani AM. Development of efficient algorithm to detect and classify alpha activity in real-time EEG signal using LabVIEW for mental state detection. In 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 411-415. 8117172 doi: 10.1109/IEMCON.2017.8117172

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Development of efficient algorithm to detect and classify alpha activity in real-time EEG signal using LabVIEW for mental state detection

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Keywords

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