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Coma degree evaluating method based on multiple indexes of non-linearity and complexity

A technique for evaluating methods, complexity, applied in the field of signal processing

Inactive Publication Date: 2011-09-14
ZHEJIANG UNIV
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Problems solved by technology

However, the monitoring of coma depth applied to coma patients is still in the exploratory and experimental stage

Method used

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  • Coma degree evaluating method based on multiple indexes of non-linearity and complexity
  • Coma degree evaluating method based on multiple indexes of non-linearity and complexity
  • Coma degree evaluating method based on multiple indexes of non-linearity and complexity

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Embodiment Construction

[0023] Human tissue cells are always producing very weak bioelectrical activities spontaneously and continuously. Electrodes placed on the scalp are used to draw out the electrical activity of brain cells and amplified by an EEG machine to record, and then a graph and curve with a certain waveform, amplitude, frequency and phase can be obtained, which is the EEG. When pathological or functional changes occur in brain tissue, this curve will change accordingly, thus providing a basis for clinical diagnosis and treatment.

[0024] The principle of each characteristic parameter parameter

[0025] Approximate entropy (Approximate entropy, ApEn) was first proposed by Pincus in 1991. According to the definition of K's entropy, approximate entropy is defined as the conditional probability that similar vectors continue to maintain their similarity when they increase from m dimension to m+l dimension. The physical meaning is the probability of generating a new pattern in the time ser...

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Abstract

The invention discloses a coma degree evaluating method based on multiple indexes of non-linearity and complexity, which is used for monitoring the brain state of a patient in a coma, and can realize continuous coma depth monitoring, and coma phase grading and early warning. Multiple complexity indexes such as complexity, Lyapunov exponent, approximate entropy, related dimensions, and the like are extracted from coma electroencephalographic signals by adopting a nonlinear dynamics analytical method, and a comprehensive coma state exponent is obtained by combining a traditional GOS (Glasgow Outcome Scale) evaluation system and a traditional GCS (Glasgow Coma Scale) evaluation system; the coefficients of the correlation between the parameters are obtained by clinical experiments; a coma state grading database is founded and a parameter fusion coefficient is determined on the basis of clinical effects; and finally, complete conscious state grading evaluation exponents are founded to guide the treatment of a patient and make prognosis.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a feature extraction and information fusion technology of an electroencephalogram signal (EEG) in a coma state. Background technique [0002] Coma is the most severe stage of disturbance of consciousness, a state of high depression of the cerebral cortex and subcortical neural structures. Clinically, it manifests as extremely reduced clarity of consciousness and no response to external stimuli. Defense reflexes and vital signs may exist in mild cases, and disappear in severe cases. Coma can be caused by central nervous system lesions (accounting for 70%), or the consequences of systemic diseases, such as acute infectious diseases, endocrine and metabolic disorders, cardiovascular diseases, poisoning and electric shock, heat stroke, altitude sickness, etc. coma. [0003] For coma classification, the most widely used is the Glasgow Coma Scale (GCS, GlasgowComaScale). T...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/0476G06K9/62
Inventor 孟濬倪振强王磊陈啸
Owner ZHEJIANG UNIV
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