Characteristic features of measurements and modeling for biosystems in phase spaces of states

Eskov, Valeriy; Eskov, Valeriy; Филатова, О.

doi:10.1007/s11018-011-9673-4

Cited by 47 publications

(35 citation statements)

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“…Similar problems were described in [4] by a group of scientists from Stanford, who studied organization of movements. We can conclude that for multiple repetitions (trainings), the accuracy of execution of the movements increases [5,6].…”

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confidence: 71%

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Measuring Order Parameters Based on Neural Network Technologies

Vokhmina

Eskov²,

Гавриленко³

et al. 2015

Meas Tech

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We show convergence of a procedure for multiple training of a neural network, when during multiple repetitions of the solution of a binary classifi cation task based on unchanged packets of training samples the neural emulator can initially demonstrate a chaotic set of values for the feature weights, which as the number of iterations increases is reduced to a certain ranked series. Keywords: biosystem, order parameters, neural network, theory of chaos and self-organization.Development of synergetics has been associated with the possibility and need for solving problems involving identifi cation of order parameters and constructing a theory of systems synthesis as a whole. Despite tremendous efforts by scientists over the past 40 years, there have been no substantial achievements in the area of formalization of the procedure for identifi cation of order parameters and total systems synthesis. Identifi cation of order parameters remains a unique procedure for individual selected tasks. Universal formalization of systems synthesis is lacking at the moment for complex systems, which especially include biosystems [1,2].At the same time, there is a certain class of tasks and systems where such formalization is possible by application of neural network technologies. In recent years, neural emulators have been widely used for identifi cation of the most important diagnostic signs (features) in medicine and biology, but the result obtained with their application is not always unambiguous, and so it has not been worthwhile to use neural emulators for practical purposes. Is there a way out of this situation? An answer is presented in this paper, using binary classifi cation as an example, i.e., for attempts to identify order parameters and to rank the weights of diagnostic features: the components x i of the system state vector x = x(t).Nonparametric Distribution of Weighted Features in a Neural Emulator. The binary classifi cation task utilizing a neural computer is very widely used in medicine, since it lets us, without separate analysis of the dynamics of variation in each component x i of the state vector for the human body (the human state vector) x = x(t) = (x 1 , x 2 , ..., x m ) T , to establish in general how one group of patients (for example, an untreated group) differs from another group (with a specifi c type of treatment). Based on binary classifi cation, we can compare groups of patients receiving different types of care (drugs, physical therapy, etc.) [2, 3] and can establish the effi cacy of health-related measures and the effect of environmental factors, and to evaluate coaching in sports.After identifi cation of the differences by the neural emulator, we need to estimate the signifi cance (weight) of a specifi c ith diagnostic feature (i = 1, 2, ..., m, where m is the dimensionality of the phase space), i.e., the components x i of the human state vector, which is especially important when these features characterize the state of different functional systems in the human body. Guidelines for the doctor (wh...

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confidence: 71%

“…in order to identify, for example, regional (endemic) characteristics of diseases or, on going to personalized medicine, when the order parameters for each patient may be different for the same disease [4,5].…”

mentioning

confidence: 99%

Measuring Order Parameters Based on Neural Network Technologies

Vokhmina

Eskov²,

Гавриленко³

et al. 2015

Meas Tech

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“…Now we have a special theory (CCTB) where the basic postulate of H. Haken's proposition was presented [2,10,12] and the compartmental-cluster theory of bio-systems with modeling of compartmental and cluster structure of different similar systems was described [10][11][12]. Indeed the CCTB are based on H. Haken's postulate [4,5] where behavior of separate elements is not investigated and systems have the compartmental-cluster structure (the first basic property of synergetic systems presented by the authors, see Table 2 below) [2,10].…”

Section: Five Properties and Thirteen Differences Between The Third Pmentioning

confidence: 99%

Two types of systems and three types of paradigms in systems philosophy and system science

Еськов¹,

Филатова²,

Филатов³

2012

JBiSE

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Now it is evident that nature and society have a great number of special systems which very differ from traditional objects (systems) of physics, chemists and engineering. For such special (synergetic-chaotic) systems we propose the special third paradigm and construct five basic properties of (unique) systems and on 13 differences in the methods, basic concepts about such systems. The introduction of such basic properties and differences are presented in the article. We postulate the humanity evolution, dynamic of social and political systems, biosphere of Earth, the human organism and his functional systems and many other systems (Universe at all) have all five such properties and must be described according to special synergetic paradigm. Now the authors presents all these special properties and the special table where the differences between deterministic-stochastic systems (and its theoretical approaches) and the synergetic systems (complexity, self-organization systems) were presented more conveniently.

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“…Using a new approach - the theory of chaos and self-organization (TCS) [1] - we proved the existence of continuous chaotic motion of the state vector x = x ( t ) of any biological system (including the biomechanical) as complex of the system (complexity) [2,3]. This indicates a basic absence of stationary modes in biosystems ( dx / dt ≠ 0 at any time) and an impossibility of any arbitrary motor activity as an inability to obtain stationary modes in the form dx / dt = 0.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Movements in Tapping and Tremor from the Viewpoint of the Theory of Chaos and Self-Organization

2016

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Chaos in the organization of any human or animal movement has its own parameters in the form of quasi-attractors, and these parameters (quasi-attractors) have a diagnostically significant value. Motor activity of any biological entity in biomechanics consists of a real superposition of voluntary acts (i.e., having a goal and the mechanisms of its implementation) and an obligatory element of chaos when the arbitrary motor activity cannot really be implemented arbitrarily. This paper presents examples of the practical implementation of the parameters of chaos in clinical medicine and their diagnostic value.

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Characteristic features of measurements and modeling for biosystems in phase spaces of states

Cited by 47 publications

References 1 publication

Measuring Order Parameters Based on Neural Network Technologies

Measuring Order Parameters Based on Neural Network Technologies

Two types of systems and three types of paradigms in systems philosophy and system science

Evaluation of Movements in Tapping and Tremor from the Viewpoint of the Theory of Chaos and Self-Organization

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