Proceedings of the International Conference on Digital Transformation in Business: Navigating the New Frontiers Beyond Boundaries (DTBNNF 2024)

The Effect of Emotions and Parkinson’s Disease Prediction Using Classification Learner Models with EEG Dataset Generation

Authors
S. Arockiya Selvi1, *, T. Kamalakannan2
1Research Scholar, Department of Computer Science, VISTAS, Chennai, India
2Research Supervisor, Department of Computer Science, VISTAS, Chennai, India
*Corresponding author. Email: selvi.arockiya@gmail.com
Corresponding Author
S. Arockiya Selvi
Available Online 3 June 2024.
DOI
10.2991/978-94-6463-433-4_43How to use a DOI?
Keywords
Parkinson’s disease (PD). Electroencephalogram (EEG). MATLAB; Support Vector Machine (SVM)
Abstract

Nearly all hazardous illnesses that affect humans are mostly brought on by emotion. Emotion influences blood pressure, heart rate, renal functionality as well as a few neurological issues. Parkinson’s disease movement dysfunction is one of the neurological issues. This problem is caused by a decrease in dopamine secretion in our brains. Dopamine production abnormalities are associated with essential hypertension. Dopamine is important in anxiety modulation in various parts of the brain. Patients with PD frequently encounter that moments of acute stress make their motor symptoms, such as gait freezing, dyskinesia, and tremors, worse. We can say with absolute certainty that emotions play a crucial role in Parkinson’s disease. The Classification Learner algorithms and the EEG dataset, which covers the clinical range of Parkinson’s disease progression, were the main topics of this research study. We look at the supervised machine learning algorithms: Course Gaussian SVM, Medium Gaussian SVM, Quadratic SVM, and Linear SVM. This yields the accuracy required to detect Parkinson’s disease early on with the aid of SVM algorithms and the EEG dataset. With MATLAB, we were able to predict the following: accuracy, sensitivity, specificity, precision, and error rate.

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 International Conference on Digital Transformation in Business: Navigating the New Frontiers Beyond Boundaries (DTBNNF 2024)
Series
Advances in Economics, Business and Management Research
Publication Date
3 June 2024
ISBN
978-94-6463-433-4
ISSN
2352-5428
DOI
10.2991/978-94-6463-433-4_43How 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

TY  - CONF
AU  - S. Arockiya Selvi
AU  - T. Kamalakannan
PY  - 2024
DA  - 2024/06/03
TI  - The Effect of Emotions and Parkinson’s Disease Prediction Using Classification Learner Models with EEG Dataset Generation
BT  - Proceedings of the International Conference on Digital Transformation in Business: Navigating the New Frontiers Beyond Boundaries (DTBNNF 2024)
PB  - Atlantis Press
SP  - 566
EP  - 577
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-433-4_43
DO  - 10.2991/978-94-6463-433-4_43
ID  - Selvi2024
ER  -