Ispol'zovanie iskusstvennykh neirosetei dlia raspoznavaniia tipa myslitel'nykh operatsii po EEG.i
Ivanitskii, G. A. ; Nikolaev, A. R. LU
and Ivanitskii, A. M.
(1997)
In Aviakosmicheskaia i ekologicheskaia meditsina = Aerospace and environmental medicine
31(6).
p.23-28
- Abstract
Reflection in EEG parameters of the process of solving two types of mental tasks, i.e. spatial-imaginary and verbal-logical, was investigated in nine test-subjects. Mental efforts were found to specify EEG spatiofrequency patterns depending on the task type and subject's identity. These patterns were unique and reproducible enough to enable identification of this or the other type of mental task within several seconds of EEG record. Recognition was executed with the use of an artificial neural network algorithm in order to simultaneously weigh a wealth of signs of a specific EEG pattern. Recognition precision was 85% on the average.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/c553e8cb-85c5-4d40-8b46-c53d2bc6c69b
- author
- Ivanitskii, G. A.
; Nikolaev, A. R.
LU
and Ivanitskii, A. M.
- alternative title
- Use of artificial neural networks in recognition of types of thinking by EEG
- publishing date
- 1997-01-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Aviakosmicheskaia i ekologicheskaia meditsina = Aerospace and environmental medicine
- volume
- 31
- issue
- 6
- pages
- 6 pages
- publisher
- Slovo Ltd
- external identifiers
-
- scopus:17144440774
- pmid:9483276
- ISSN
- 0233-528X
- language
- Russian
- LU publication?
- no
- id
- c553e8cb-85c5-4d40-8b46-c53d2bc6c69b
- date added to LUP
- 2020-04-06 19:45:58
- date last changed
- 2024-01-02 08:28:59
@article{c553e8cb-85c5-4d40-8b46-c53d2bc6c69b,
abstract = {{<p>Reflection in EEG parameters of the process of solving two types of mental tasks, i.e. spatial-imaginary and verbal-logical, was investigated in nine test-subjects. Mental efforts were found to specify EEG spatiofrequency patterns depending on the task type and subject's identity. These patterns were unique and reproducible enough to enable identification of this or the other type of mental task within several seconds of EEG record. Recognition was executed with the use of an artificial neural network algorithm in order to simultaneously weigh a wealth of signs of a specific EEG pattern. Recognition precision was 85% on the average.</p>}},
author = {{Ivanitskii, G. A. and Nikolaev, A. R. and Ivanitskii, A. M.}},
issn = {{0233-528X}},
language = {{rus}},
month = {{01}},
number = {{6}},
pages = {{23--28}},
publisher = {{Slovo Ltd}},
series = {{Aviakosmicheskaia i ekologicheskaia meditsina = Aerospace and environmental medicine}},
title = {{Ispol'zovanie iskusstvennykh neirosetei dlia raspoznavaniia tipa myslitel'nykh operatsii po EEG.i}},
volume = {{31}},
year = {{1997}},
}