Computer Optics
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Computer Optics:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Computer Optics, 2022, Volume 46, Issue 6, Pages 988–1019
DOI: https://doi.org/10.18287/2412-6179-CO-1134
(Mi co1095)
 

NUMERICAL METHODS AND DATA ANALYSIS

Biometric data and machine learning methods in the diagnosis and monitoring of neurodegenerative diseases: a review

I. A. Hodashinsky, K. S. Sarin, M. B. Bardamova, M. O. Svetlakov, A. O. Slezkin, N. P. Koryshev

Tomsk State University of Control Systems and Radioelectronics
Abstract: A review of noninvasive biometric methods for detecting and predicting neurodegenerative diseases is presented. An analysis of various modalities used to diagnose and monitor diseases is given. Such modalities as handwritten data, electroencephalography, speech, gait, eye movement, as well as the use of compositions of these modalities are considered. A detailed analysis of modern methods and solutions based on machine learning is conducted. Data sets, preprocessing methods, machine learning models, and accuracy estimates for disease diagnosis are presented. In the conclusion current open problems and future prospects of research in this direction are considered.
Keywords: non-invasive diagnostic methods, neurodegenerative diseases, biometric signal processing, machine learning
Funding agency Grant number
Russian Science Foundation 22-21-00021
This work was supported by the Russian Science Foundation (project no. 22-21-00021).
Received: 26.03.2022
Accepted: 30.08.2022
Document Type: Article
Language: Russian
Citation: I. A. Hodashinsky, K. S. Sarin, M. B. Bardamova, M. O. Svetlakov, A. O. Slezkin, N. P. Koryshev, “Biometric data and machine learning methods in the diagnosis and monitoring of neurodegenerative diseases: a review”, Computer Optics, 46:6 (2022), 988–1019
Citation in format AMSBIB
\Bibitem{HodSarBar22}
\by I.~A.~Hodashinsky, K.~S.~Sarin, M.~B.~Bardamova, M.~O.~Svetlakov, A.~O.~Slezkin, N.~P.~Koryshev
\paper Biometric data and machine learning methods in the diagnosis and monitoring of neurodegenerative diseases: a review
\jour Computer Optics
\yr 2022
\vol 46
\issue 6
\pages 988--1019
\mathnet{http://mi.mathnet.ru/co1095}
\crossref{https://doi.org/10.18287/2412-6179-CO-1134}
Linking options:
  • https://www.mathnet.ru/eng/co1095
  • https://www.mathnet.ru/eng/co/v46/i6/p988
  • Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
    Statistics & downloads:
    Abstract page:39
    Full-text PDF :46
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2025