Proceedings of the 2nd International Conference on Consumer Technology and Engineering Innovation (ICONTENTION 2023)

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Analysis of brain wave signals using electroencephalography in people with depression

Authors
Muhammad Rizki Fadillah1, *, M. Ramdhani Firmansyah2, Rojudin3, Ilman Hilmawan K4
1Department of Electrical Engineering, Nusa Putra University, Sukabumi, Indonesia
2Department of Electrical Engineering, Nusa Putra University, Sukabumi, Indonesia
3Department of Electrical Engineering, Nusa Putra University, Sukabumi, Indonesia
4Department of Electrical Engineering, Nusa Putra University, Sukabumi, Indonesia
*Corresponding author. Email: Rizki.fadillah_te20@nusaputra.ac.id
Corresponding Author
Muhammad Rizki Fadillah
Available Online 13 May 2024.
DOI
10.2991/978-94-6463-406-8_2How to use a DOI?
Keywords
— electroencephalography; depression; analysis; sinyal; electrodes
Abstract

Electroencephalography is a brain signal processing technique used to detect abnormal brain waves. Electroencephalography signal recording using electrodes attached to the scalp. Electroencephalography signals are amplified by transmitting signals into notch filters, high pass filters, and low pass filters to improve signal quality such as eliminating and reducing noise. Electroencephalography recording focuses on analyzing alpha waves to determine if the subject suffers from depression. For cases of depression, the brain lobes that are installed with electrodes are the occipital and parietal lobes of the brain. In this study using the Patient Health Questionnaire Method-9 (PHQ-9). The results obtained after recording electroencephalography there are in the form of very large and abnormal alpha wave theta waves whose shape is very large.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Conference on Consumer Technology and Engineering Innovation (ICONTENTION 2023)
Series
Advances in Engineering Research
Publication Date
13 May 2024
ISBN
978-94-6463-406-8
ISSN
2352-5401
DOI
10.2991/978-94-6463-406-8_2How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Muhammad Rizki Fadillah
AU  - M. Ramdhani Firmansyah
AU  - Rojudin
AU  - Ilman Hilmawan K
PY  - 2024
DA  - 2024/05/13
TI  - Analysis of brain wave signals using electroencephalography in people with depression
BT  - Proceedings of the 2nd International Conference on Consumer Technology and Engineering Innovation (ICONTENTION 2023)
PB  - Atlantis Press
SP  - 3
EP  - 6
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-406-8_2
DO  - 10.2991/978-94-6463-406-8_2
ID  - Fadillah2024
ER  -