Tensometric tremorography in high-precision medical diagnostic systems
Received 21 March 2018
Accepted for publication 12 May 2018
Published 13 September 2018 Volume 2018:11 Pages 321—330
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Scott Fraser
Zoya Aleksanyan,1 Olga Bureneva,2 Nikolay Safyannikov2
1Institute of the Human Brain, Russian Academy of Sciences, Saint Petersburg, Russia; 2Department of Computer Science and Engineering, Saint-Petersburg State Electrotechnical University “LETI”, Saint Peterburg, Russia
Background: The objective of the study was to develop a system for the precision diagnostics of pathologies of motor brain regions based on tensometric measurement and to explore its diagnostic capabilities.
Materials and methods: Tremor is a syndrome that indicates the abnormal state of the central nervous system, primarily in the motor brain regions. Analysis of tremor parameters provides significant information about the changes in the body motion control and can be used as an objective index of the central nervous system state. Existing methods are aimed at the analysis of visible tremor based on the use of different sensors. We suggest an alternative approach based on the use of a tensometric system performing tremor measurements when the tremor appears on the background of voluntary isometric efforts. The key advantage of our approach is that it allows to determine the tremor before its visible manifestation. In the article, we describe hardware implementation of our tremor analysis system.
Results: In the article, we represent the new methodology and the original equipment based on the control of isometric effort. Isometric effort formed by a patient is controlled with the use of a feedback system on the patient’s monitor. We evaluated the performance of our equipment with more than 400 healthy volunteers and patients with various pathologies of the central nervous system motor regions, and the results of the investigations, allowing to identify tremor parameters typical for parkinsonism, are represented in our article.
Conclusion: Testing of the system confirmed its high diagnostic validity and reliability, high sensitivity, simplicity and high speed of information processing. The approach based on tensometric measurements is very promising for the diagnostics of Parkinson disease and dysfunctions of a central nervous system.
Keywords: isometric method, hands oscillations, biological feedback, precision diagnostics, tremor
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