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THE METHOD OF THE ESTIMATION OF THE ACCEPTABLE DEGREE OF THE DEFLECTION OF THE SPINE AND OF BIAS OF VERTEBRAE IN SYSTEMS OF THE DIAGNOSTIC AND THE REHABILITATION

N.V. Dorofeev, Anastasia Grecheneva, O.R. Kuzichkin, Roman Romanov

First published: 2017-06-20https://doi.org/10.5593/sgem2017/61/s25.151View metrics

Abstract

The article discusses the method of the estimation of the permissible degree of the deflection of the spine and of bias of vertebrae. The proposed method is based on measurement of steering angles and degree of deviation of vertebrae by accelerometric transducers, application of neural network algorithms of the processing of capture data for adapt of the system of the diagnostics and of the rehabilitation under patients with different physiological characteristics and disorders of the spine and musculoskeletal system as a whole. Neural network algorithms are based on optimal Bayesian detector, the accumulated information database of previous patients, patient records and statistical information of disorders and diseases of spine and musculoskeletal system. Implementation of proposed methods and of approaches will allow to automate the process of the diagnosis and of the rehabilitation of spine, to minimize the subjectivity of diagnosis, improve the efficiency of the rehabilitation. With proper formation of the structure of neural networks, basic models and additional information the structure of the system of the diagnostics and of the rehabilitation will reflect the structure of the work of the human nervous system when the painful sensation are occurrence .

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Publication details

Title
THE METHOD OF THE ESTIMATION OF THE ACCEPTABLE DEGREE OF THE DEFLECTION OF THE SPINE AND OF BIAS OF VERTEBRAE IN SYSTEMS OF THE DIAGNOSTIC AND THE REHABILITATION
Authors
N.V. Dorofeev, Anastasia Grecheneva, O.R. Kuzichkin, Roman Romanov
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 17th International Multidisciplinary Scientific GeoConference SGEM2017, Nano, Bio and Green - Technologies for a Sustainable Future
Publisher
STEF92 Technology
Year
2017
Pages
1161-1168
SWS Citekey
Dorofeev20172511611168
ISSN
1314-2704
ISBN
978-619-7408-12-6
Language
en
Publication type
Conference Paper
Keywords
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Number of times cited according to Crossref: 2

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