Application of adaptive classification of tensotremorograms for revealing the pathological states of human motor control system
| Autor: | Y. A. Kuperin, A.A. Mekler, S. P. Romanov, A. S. Minin |
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| Rok vydání: | 2009 |
| Předmět: |
General Computer Science
Artificial neural network Computer science business.industry Healthy subjects Motor control Machine learning computer.software_genre Electronic Optical and Magnetic Materials Binary classification Artificial intelligence Electrical and Electronic Engineering business Pathological computer Classifier (UML) |
| Zdroj: | Optical Memory and Neural Networks. 18:304-311 |
| ISSN: | 1934-7898 1060-992X |
| DOI: | 10.3103/s1060992x09040092 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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