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Pressure center nonlinear feature extraction method based on complexity

A non-linear feature, pressure center technology, applied in the field of biomechanics, can solve difficult problems such as COP signal analysis that has not yet been seen

Inactive Publication Date: 2013-12-04
HANGZHOU DIANZI UNIV
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Problems solved by technology

However, it is currently difficult to apply Lempel-Ziv complexity to COP signal analysis, mainly because the COP signal recorded by the force measuring platform and balance board is a two-dimensional signal. Although the one-dimensional complexity algorithm is very mature, the two-dimensional complex The complexity algorithm needs to be further studied, and there is no report on the application of Lempel-Ziv complexity to the analysis of COP signals.

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  • Pressure center nonlinear feature extraction method based on complexity
  • Pressure center nonlinear feature extraction method based on complexity
  • Pressure center nonlinear feature extraction method based on complexity

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Embodiment Construction

[0034] The present invention will be further described below in conjunction with accompanying drawing.

[0035] A method for extracting nonlinear features of the pressure center based on complexity, the specific implementation method is as follows:

[0036] Step 1. Acquisition of COP signal;

[0037] Step 2. Sequence reconstruction based on neighborhood coarse-graining;

[0038] Step 3. Calculate the normalized Lempel-Ziv complexity of the COP signal based on the reconstructed sequence.

[0039] The acquisition of the COP signal in the step 1 specifically adopts the following existing methods:

[0040] 1-1. Let the subject stand on the force measuring platform or balance board, and pick up the four pressure signals of the pressure sensors distributed at the four corners of the force measuring platform or balance board, respectively recorded as f 1 , f 2 , f 3 , f 4 ;Set the coordinate origin at the geometric center of the force measuring platform or the balance plate, se...

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Abstract

The invention discloses a complexity based pressure center nonlinear feature extraction method. Conventional COP (center of pressure) feature parameters cannot effectively describe nonlinear features of shaking of human bodies. The method is used for extracting COP nonlinear dynamical features by utilizing an established model based on neighborhood coarse graining two-dimensional Lempel-Ziv complexity and specifically includes step1, acquiring COP signals; step 2, performing sequence reconstructing based on neighborhood coarse graining; and step 3, calculating normalized Lempel-Ziv complexity of the COP signals based on a reconstructed sequence. The complexity based pressure center nonlinear feature extraction method effectively solves the problem about how to apply the Lempel-Ziv complexity to process the two-dimensional COP signals to extract nonlinear features of the COP signals, so that quantitative description can be performed to irregular degree of posture shaking of the human bodies.

Description

technical field [0001] The invention belongs to the field of biomechanics, and in particular relates to a method for extracting nonlinear features of a pressure center based on complexity. Specifically, it uses the two-dimensional Lempel-Ziv complexity based on neighborhood coarse-graining to extract the nonlinear dynamic characteristics of the center of pressure (COP) signal, and quantitatively describe the irregularity of human body posture shaking. method. Background technique [0002] People often take their ability to stand still for granted. But in fact, standing upright is a complex task. To complete this task, the multi-level nerve centers in the posture control system, including the vestibular nucleus, brainstem reticular structure, spinal cord, cerebellum and cerebral cortex, etc., control vision, The information acquired by proprioceptive and vestibular sensory organs is integrated and processed, and the musculoskeletal tissue related to motor function regulates...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/103
Inventor 孙曜罗志增孟明杜宇鹏
Owner HANGZHOU DIANZI UNIV
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