title: Application of Adaptive Classification of Tensotremorograms for Revealing the Pathological States of Human Motor Control System
metadata.name: dc.contributor.author
metadata.value: Kuperin, Y. A.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Minin, A. S.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Mekler, A. A.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Romanov, S. P.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2015-08-27T12:21:11Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2015-08-27T12:21:11Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2009
metadata.lang: -
metadata.name: dc.identifier.issn
metadata.value: 1060-992X
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/1684
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: In this paper the adaptive binary classifier is applied for the classification of the tensotremorogramm
  (TTG) time series. The idea is to reveal pathological states of human motor control system.
  Adaptive binary classifier being a new type of trained classifiers can be trained on the data for healthy
  subjects. Then the trained classifier can be used for the examinees division into healthy and sick patients.
  It is shown, that the trained adaptive binary classifier is able to classify the patients with acceptable accuracy.
  Other method of classification—Neural Clouds—has also been used. The comparison both methods
  has been done.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: Allerton Press, Inc.
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Optical Memory and Neural Networks (Information Optics);Vol. 18, No. 4
metadata.lang: -
metadata.name: dc.subject
metadata.value: neural network
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: tremor
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: Parkinson disease
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: Neural Clouds binary classifier method
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Application of Adaptive Classification of Tensotremorograms for Revealing the Pathological States of Human Motor Control System
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: Kuperin_OMNN304.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/1684/1/Kuperin_OMNN304.pdf
resources.format: Adobe PDF
resources.size: 355,04 kB