EEG Processing Interface for Educational Applications

Luis F. Ordoñez-Ordoñez; Ámbar I. Sánchez Valarezo; Efren L. Lema Condo; Freddy L. Bueno Palomeque

doi:10.1109/ETCM58927.2023.10309082

EEG Processing Interface for Educational Applications

Luis F. Ordoñez-Ordoñez, Ámbar I. Sánchez Valarezo, Efren L. Lema Condo, Freddy L. Bueno Palomeque

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

Abstract

The acquisition, processing and analysis of brain signals play an essential role in the detection and diagnosis of mental disorders and brain abnormalities. The evaluation of signals recorded by electroencephalograms (EEG) currently benefits from a variety of computational tools, whose understanding and correct handling are essential. This article presents the development of a graphical interface in Matlab, designed for academic students, which allows them to effectively verify and validate the progress of their educational practices, approaching biosignal analysis in a more practical and understandable way. It enables the import of data from five different hardware devices (Emotiv EPOC, gNautilus, Biopac, iWorx and MADQ) and consists of two blocks dedicated to preprocessing and processing. Through its intuitive interface, it facilitates the execution of experiments and the understanding of underlying concepts in numerical analysis, thus providing users with an effective tool to expand their knowledge and skills in this area.

Original language	English
Title of host publication	ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting
Editors	David Rivas Lalaleo, Manuel Ignacio Ayala Chauvin
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350338232
DOIs	https://doi.org/10.1109/ETCM58927.2023.10309082
State	Published - 2023
Event	7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023 - Ambato, Ecuador Duration: 10 Oct 2023 → 13 Oct 2023

Publication series

Name	ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting

Conference

Conference	7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023
Country/Territory	Ecuador
City	Ambato
Period	10/10/23 → 13/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

digital filters
EEG
frequency bands
processing
user interface

Access to Document

10.1109/ETCM58927.2023.10309082

Cite this

Ordoñez-Ordoñez, L. F., Sánchez Valarezo, Á. I., Lema Condo, E. L., & Bueno Palomeque, F. L. (2023). EEG Processing Interface for Educational Applications. In D. R. Lalaleo, & M. I. A. Chauvin (Eds.), ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting (ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETCM58927.2023.10309082

Ordoñez-Ordoñez, Luis F. ; Sánchez Valarezo, Ámbar I. ; Lema Condo, Efren L. et al. / EEG Processing Interface for Educational Applications. ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting. editor / David Rivas Lalaleo ; Manuel Ignacio Ayala Chauvin. Institute of Electrical and Electronics Engineers Inc., 2023. (ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting).

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abstract = "The acquisition, processing and analysis of brain signals play an essential role in the detection and diagnosis of mental disorders and brain abnormalities. The evaluation of signals recorded by electroencephalograms (EEG) currently benefits from a variety of computational tools, whose understanding and correct handling are essential. This article presents the development of a graphical interface in Matlab, designed for academic students, which allows them to effectively verify and validate the progress of their educational practices, approaching biosignal analysis in a more practical and understandable way. It enables the import of data from five different hardware devices (Emotiv EPOC, gNautilus, Biopac, iWorx and MADQ) and consists of two blocks dedicated to preprocessing and processing. Through its intuitive interface, it facilitates the execution of experiments and the understanding of underlying concepts in numerical analysis, thus providing users with an effective tool to expand their knowledge and skills in this area.",

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year = "2023",

doi = "10.1109/ETCM58927.2023.10309082",

language = "English",

series = "ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Ordoñez-Ordoñez, LF, Sánchez Valarezo, ÁI, Lema Condo, EL & Bueno Palomeque, FL 2023, EEG Processing Interface for Educational Applications. in DR Lalaleo & MIA Chauvin (eds), ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting. ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting, Institute of Electrical and Electronics Engineers Inc., 7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023, Ambato, Ecuador, 10/10/23. https://doi.org/10.1109/ETCM58927.2023.10309082

EEG Processing Interface for Educational Applications. / Ordoñez-Ordoñez, Luis F.; Sánchez Valarezo, Ámbar I.; Lema Condo, Efren L. et al.
ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting. ed. / David Rivas Lalaleo; Manuel Ignacio Ayala Chauvin. Institute of Electrical and Electronics Engineers Inc., 2023. (ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting).

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

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AU - Sánchez Valarezo, Ámbar I.

AU - Lema Condo, Efren L.

AU - Bueno Palomeque, Freddy L.

PY - 2023

Y1 - 2023

N2 - The acquisition, processing and analysis of brain signals play an essential role in the detection and diagnosis of mental disorders and brain abnormalities. The evaluation of signals recorded by electroencephalograms (EEG) currently benefits from a variety of computational tools, whose understanding and correct handling are essential. This article presents the development of a graphical interface in Matlab, designed for academic students, which allows them to effectively verify and validate the progress of their educational practices, approaching biosignal analysis in a more practical and understandable way. It enables the import of data from five different hardware devices (Emotiv EPOC, gNautilus, Biopac, iWorx and MADQ) and consists of two blocks dedicated to preprocessing and processing. Through its intuitive interface, it facilitates the execution of experiments and the understanding of underlying concepts in numerical analysis, thus providing users with an effective tool to expand their knowledge and skills in this area.

AB - The acquisition, processing and analysis of brain signals play an essential role in the detection and diagnosis of mental disorders and brain abnormalities. The evaluation of signals recorded by electroencephalograms (EEG) currently benefits from a variety of computational tools, whose understanding and correct handling are essential. This article presents the development of a graphical interface in Matlab, designed for academic students, which allows them to effectively verify and validate the progress of their educational practices, approaching biosignal analysis in a more practical and understandable way. It enables the import of data from five different hardware devices (Emotiv EPOC, gNautilus, Biopac, iWorx and MADQ) and consists of two blocks dedicated to preprocessing and processing. Through its intuitive interface, it facilitates the execution of experiments and the understanding of underlying concepts in numerical analysis, thus providing users with an effective tool to expand their knowledge and skills in this area.

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KW - EEG

KW - frequency bands

KW - processing

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BT - ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting

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PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Ordoñez-Ordoñez LF, Sánchez Valarezo ÁI, Lema Condo EL , Bueno Palomeque FL. EEG Processing Interface for Educational Applications. In Lalaleo DR, Chauvin MIA, editors, ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting. Institute of Electrical and Electronics Engineers Inc. 2023. (ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting). doi: 10.1109/ETCM58927.2023.10309082

EEG Processing Interface for Educational Applications

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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