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Algorithm for Detection of Raising Eyebrows and Jaw Clenching Artifacts in EEG Signals Using Neurosky Mindwave Headset

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Authors
Vélez, Luis
Kemper, Guillermo
Issue Date
2021-01-01
Keywords
Artifacts detection
Brain–computer interface
EEG signals
Neurosky mindwave headset
Brain computer interface
Computer control systems
Computer games
Electroencephalography
Electrophysiology
Identification (control systems)
Internet of things
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Metadata
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Journal
Smart Innovation, Systems and Technologies
URI
http://hdl.handle.net/10757/653818
DOI
10.1007/978-3-030-57566-3_10
Additional Links
https://www.scopus.com/record/display.uri?eid=2-s2.0-85098124020&doi=10.1007%2f978-3-030-57566-3_10&origin=inward&txGid=26c069f02033f8a0b36d73b51209138e
Abstract
The present work proposes an algorithm to detect and identify the artifact signals produced by the concrete gestural actions of jaw clench and eyebrows raising in the electroencephalography (EEG) signal. Artifacts are signals that manifest in the EEG signal but do not come from the brain but from other sources such as flickering, electrical noise, muscle movements, breathing, and heartbeat. The proposed algorithm makes use of concepts and knowledge in the field of signal processing, such as signal energy, zero crossings, and block processing, to correctly classify the aforementioned artifact signals. The algorithm showed a 90% detection accuracy when evaluated in independent ten-second registers in which the gestural events of interest were induced, then the samples were processed, and the detection was performed. The detection and identification of these devices can be used as commands in a brain–computer interface (BCI) of various applications, such as games, control systems of some type of hardware of special benefit for disabled people, such as a chair wheel, a robot or mechanical arm, a computer pointer control interface, an Internet of things (IoT) control or some communication system.
Type
Other
Rights
info:eu-repo/semantics/embargoedAccess
Language
eng
Description
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
ISSN
21903018
EISSN
21903026
ae974a485f413a2113503eed53cd6c53
10.1007/978-3-030-57566-3_10
Scopus Count
Collections
Ingeniería Electrónica

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