Using PCA Machine Learning Approach Based on Psychological Questionnaires and Spectral Characteristics of the EEG to Separate the Healthy Participants and Participants with Major Depressive Disorder › Research Explorer

Novosibirsk State University's Research Portal

Using PCA Machine Learning Approach Based on Psychological Questionnaires and Spectral Characteristics of the EEG to Separate the Healthy Participants and Participants with Major Depressive Disorder

Research output: Contribution to conference › Paper › peer-review

Links

https://ieeexplore.ieee.org/document/10225096/

DOI

https://doi.org/10.1109/EDM58354.2023.10225096
Final published version

Ekaterina a. Merkulova
Igor a. Kozulin
Alexandr n. Savostyanov
Andrey v. Bocharov
Evgeniya yu. Privodnova

Original language	English
Pages	1740-1745
Number of pages	6
DOIs	https://doi.org/10.1109/EDM58354.2023.10225096
Publication status	Published - 29 Jun 2023
Event	2023 IEEE 24th International Conference of Young Professionals in Electron Devices and Materials (EDM) - Novosibirsk, Russian Federation Duration: 29 Jun 2023 → 3 Jul 2023 Conference number: 24

Conference

Conference	2023 IEEE 24th International Conference of Young Professionals in Electron Devices and Materials (EDM)
Country/Territory	Russian Federation
City	Novosibirsk
Period	29.06.2023 → 03.07.2023

Research areas

PCA, electroencephalogram, hypothesis testing, machine learning, processing of experimental data

ID: 61403819