Characteristics of Tremor in Normal Subjects and in the Diagnosis and Treatment of Parkinsonism

Romanov, S. P.; Aleksanyan, Z. A.; Manoilov, V. V.

doi:10.1023/b:neab.0000018751.74369.89

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…Thus, the prototype’s tests showed that tensometric tremorography as a part of isometric measurements can be used in medical diagnostics systems. 35 …”

Section: Resultsmentioning

confidence: 99%

Tensometric tremorography in high-precision medical diagnostic systems

Aleksanyan

Bureneva

Safyannikov

2018

MDER

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BackgroundThe 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 methodsTremor 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.ResultsIn 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.ConclusionTesting 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.

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“…Thus, the prototype’s tests showed that tensometric tremorography as a part of isometric measurements can be used in medical diagnostics systems. 35 …”

Section: Resultsmentioning

confidence: 99%

Tensometric tremorography in high-precision medical diagnostic systems

Aleksanyan

Bureneva

Safyannikov

2018

MDER

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“…After the AKM has performed, the centers coordinates, some adjustable parameters should be presented to the Gaussian Mixture Model Method (GMM) [2]. Gaussian Mixture Model [3] is a type of density model, comprising a number of functions (components), namely Gaussians. These component functions are combined to provide a density function.…”

Section: The Adaptive Binary Classifier Methods Descriptionmentioning

confidence: 99%

“…The received signaltensotremorogram (TTG) is being converted into the digital form and saved for the further processing. Earlier we showed, that in cases of the motor control system dysfunction, the characteristics of TTGs from patients differ from ones from healthy subjects [2][3][4]. It is necessary to note, that the method described in [1], differs principally from the frequently used methods of tremor registration as fingers ballistics by the accelerometers.…”

Section: Introductionmentioning

confidence: 99%

Application of adaptive classification of tensotremorograms for revealing the pathological states of human motor control system

Kuperin

Minin

Mekler

et al. 2009

Opt. Mem. Neural Networks

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-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.

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Analysis of fatigue and tremor during sustained maximal grip contractions using Hilbert-Huang Transformation

Hogrel

Duchêne

et al. 2012

Medical Engineering & Physics

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Characteristics of Tremor in Normal Subjects and in the Diagnosis and Treatment of Parkinsonism

Cited by 4 publications

References 4 publications

Tensometric tremorography in high-precision medical diagnostic systems

Tensometric tremorography in high-precision medical diagnostic systems

Application of adaptive classification of tensotremorograms for revealing the pathological states of human motor control system

Analysis of fatigue and tremor during sustained maximal grip contractions using Hilbert-Huang Transformation

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