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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages411-415
Number of pages5
ISBN (Electronic)9781538633717
DOIs
Publication statusPublished - Nov 21 2017
Event8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017 - Vancouver, Canada
Duration: Oct 3 2017Oct 5 2017

Other

Other8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017
CountryCanada
CityVancouver
Period10/3/1710/5/17

Fingerprint

electroencephalography
Electroencephalography
acceleration (physics)
sicknesses
immune systems
Immune system
recovery
Recovery

Keywords

  • Alpha activity
  • Brain computer interface
  • EEG

ASJC Scopus subject areas

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

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