International Conference «Mathematical and Information Technologies, MIT-2016»

28 August – 5 September 2016

Vrnjacka Banja, Serbia – Budva, Montenegro

Grecheneva A.V.   Konstantinov I.S.   Kuzichkin O.R.  

Information processing in the diagnostics system of the musculoskeletal system based on accelerometric goniometers

Reporter: Grecheneva A.V.

In the paper is proposed to implement the correction of the dynamic model of the patient with the basis for measurement, and based on the obtained dynamic model of the patient, will be formed an information model. Information model, after the processing of the neural network will be entered in the database of models, thus, will be formed a statistics and selected the optimal operating parameters of the system rehabilitation for patients with a variety of neurophysiological features. According to the physiological parameters model of the patient, will be determined by the maximum pain thresholds and minimum thresholds of sensitivity upon the rehabilitation of the musculoskeletal system. With the help of neural network algorithms and algorithms for systems of decision support (DSS) based on database of the measurements, the database of the evoked potentials and the diseases database, determined an approximate diagnosis of the patient. Neurophysiological criteria are also formed based on statistical clinical studies of patients under normal conditions and in the presence of deviations.
The paper also examines the principle of construction of system of diagnostics and rehabilitation of the musculoskeletal system based on accelerometer method, synchronization algorithms measured patient parameters are considered. The optimum values оf the technical parameters of the accelerometer, goniometer system: sample rate converters accelerometer signal, the required sensitivity of the sensor, and others. The advantages of the proposed approaches to the construction of rehabilitation and diagnostic systems of the musculoskeletal system: adaptability, reliability of the diagnoses.

To reports list

© 1996-2019, Institute of computational technologies of SB RAS, Novosibirsk