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Performance characterization of self-calibrating protocols for wearable EEG applications

Authors:

Thrasyvoulos Karydis,

Simmie L. Foster,

Andreas MershinAuthors Info & Claims

PETRA '15: Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments

Article No.: 38, Pages 1 - 7

https://doi.org/10.1145/2769493.2769533

Published: 01 July 2015 Publication History

Abstract

Therapeutic Neurofeedback (NFB) using real-time electroencephalography (EEG) data works by reinforcing desired brainwave patterns. Although EEG is a well-established diagnostic tool and EEG-NFB shows great promise for enhancing cognitive performance and treating neurological disorders, proof of its efficacy has been limited. Here we characterize a novel Self-Calibrating Protocol (SCP) method coupled to five standard machine learning algorithms to classify brain states corresponding to the experience of "pain" or "no pain".

Our results indicate that commercially available, wearable EEG sensors provide sufficient data fidelity to robustly differentiate the two "perceptually opposite" brain states. Crucially, use of SCP allows us for the first time to bypass the pitfalls associated with trying to force an individual's brain wave patterns to match "normed" target patterns obtained over population averages. These are necessary steps towards personalized NFB therapies and bespoke Brain-Computer Interfaces and brain training suitable to a wide variety of individual needs.

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Korkiakoski MAnagnostopoulos TRajala OSarkiniemi MHirsimaki MKinnunen JAlavesa P(2023)Exploring the Potential of EEG for Real-Time Interactions in Immersive Virtual RealityWSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS10.37394/23209.2023.20.1220(98-108)Online publication date: 27-Mar-2023
https://doi.org/10.37394/23209.2023.20.12
Suhaimi NMountstephens JTeo J(2020)EEG-Based Emotion RecognitionComputational Intelligence and Neuroscience10.1155/2020/88754262020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/8875426
Tsiakas KAbujelala MMakedon F(2018)Task Engagement as Personalization Feedback for Socially-Assistive Robots and Cognitive TrainingTechnologies10.3390/technologies60200496:2(49)Online publication date: 14-May-2018
https://doi.org/10.3390/technologies6020049
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Index Terms

Performance characterization of self-calibrating protocols for wearable EEG applications
1. Computing methodologies
  1. Machine learning

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Published In

cover image ACM Other conferences

PETRA '15: Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments

July 2015

526 pages

ISBN:9781450334525

DOI:10.1145/2769493

Conference Chair:
Fillia Makedon
University of Texas Arlington
,
Program Chairs:
Gian-Luca Mariottini,
Oliver Korn,
Illias Maglogiannis,
Vangelis Metsis

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

NSF: National Science Foundation
University of Texas at Austin: University of Texas at Austin
Univ. of Piraeus: University of Piraeus
NCRS: Demokritos National Center for Scientific Research
Ionian: Ionian University, GREECE

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 2015

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PETRA '15

Sponsor:

NSF
University of Texas at Austin
Univ. of Piraeus
NCRS
Ionian

PETRA '15: 8th PErvasive Technologies Related to Assistive Environments

July 1 - 3, 2015

Corfu, Greece

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Cited By

Korkiakoski MAnagnostopoulos TRajala OSarkiniemi MHirsimaki MKinnunen JAlavesa P(2023)Exploring the Potential of EEG for Real-Time Interactions in Immersive Virtual RealityWSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS10.37394/23209.2023.20.1220(98-108)Online publication date: 27-Mar-2023
https://doi.org/10.37394/23209.2023.20.12
Suhaimi NMountstephens JTeo J(2020)EEG-Based Emotion RecognitionComputational Intelligence and Neuroscience10.1155/2020/88754262020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/8875426
Tsiakas KAbujelala MMakedon F(2018)Task Engagement as Personalization Feedback for Socially-Assistive Robots and Cognitive TrainingTechnologies10.3390/technologies60200496:2(49)Online publication date: 14-May-2018
https://doi.org/10.3390/technologies6020049
Karydis TLanger SFoster SMershin A(2018)Identification of post-meditation perceptual states using wearable EEG and Self-Calibrating ProtocolsProceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference10.1145/3197768.3201544(566-569)Online publication date: 26-Jun-2018
https://dl.acm.org/doi/10.1145/3197768.3201544
Rajavenkatanarayanan ABabu ATsiakas KMakedon FBalakrishnan PMcMahan R(2018)Monitoring task engagement using facial expressions and body posturesProceedings of the 3rd International Workshop on Interactive and Spatial Computing10.1145/3191801.3191816(103-108)Online publication date: 12-Apr-2018
https://dl.acm.org/doi/10.1145/3191801.3191816
Youssef AOuda HAzab M(2018)MUSE: A Portable Cost-efficient Lie Detector2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)10.1109/IEMCON.2018.8614795(242-246)Online publication date: Nov-2018
https://doi.org/10.1109/IEMCON.2018.8614795
Bashar MTipu RMutasim AAmin M(2017)Effect of EMG artifacts on video category classification from EEG2017 6th International Conference on Informatics, Electronics and Vision & 2017 7th International Symposium in Computational Medical and Health Technology (ICIEV-ISCMHT)10.1109/ICIEV.2017.8338603(1-4)Online publication date: Sep-2017
https://doi.org/10.1109/ICIEV.2017.8338603
Mutasim ATipu RRaihanul Bashar MAshraful Amin M(2017)Video Category Classification Using Wireless EEGBrain Informatics10.1007/978-3-319-70772-3_4(39-48)Online publication date: 16-Nov-2017
https://dl.acm.org/doi/10.1007/978-3-319-70772-3_4
Karydis TFoster SMershin A(2016)Self-Calibrating Protocols as diagnostic aids for personal medicine, neurological conditions and pain assessmentProceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments10.1145/2910674.2935852(1-4)Online publication date: 29-Jun-2016
https://dl.acm.org/doi/10.1145/2910674.2935852
Tsiakas KAbellanoza CMakedon F(2016)Interactive Learning and Adaptation for Robot Assisted Therapy for People with DementiaProceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments10.1145/2910674.2935849(1-4)Online publication date: 29-Jun-2016
https://dl.acm.org/doi/10.1145/2910674.2935849
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