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Electromyographic signal tumble detection method based on WKFDA

A technology of electromyographic signal and detection method, applied in the field of pattern recognition, can solve the problem of less recognition of falls

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Problems solved by technology

At present, there are few studies on fall recognition using EMG signals at home and abroad, and there is a lot of research space

Method used

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  • Electromyographic signal tumble detection method based on WKFDA
  • Electromyographic signal tumble detection method based on WKFDA
  • Electromyographic signal tumble detection method based on WKFDA

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Experimental program
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Embodiment Construction

[0065] Such as figure 1 As shown, this embodiment includes the following steps:

[0066] The first step is to obtain the sample data of the human lower limb EMG signal, specifically: firstly, the human lower limb EMG signal is picked up by the EMG signal acquisition instrument, and then the energy threshold method is used to determine the action signal of the EMG signal.

[0067] (1) Considering that the fall experiment of the elderly will cause body damage, healthy men were selected as the experimental subjects in the experiment, and the subjects were required to refrain from strenuous exercise one week before the experiment to avoid muscle shaking caused by muscle fatigue that would affect the accuracy of sEMG. The experiment uses the mt400 EMG signal acquisition instrument of Noraxon Company of the United States to collect the gastrocnemius and vastus lateralis when the subjects are walking, squatting (movement from standing to squatting), sitting (moving from standing to s...

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Abstract

The invention relates to an electromyographic signal tumble detection method based on a WKFDA. First, surface electromyographic signals are collected from the relevant muscle tissue of the lower limbs of a human body, the action signal segment of the surface electromyographic signals is determined through an energy threshold value, and fuzzy entropy is extracted from the surface electromyographic signals in the action signal segment to serve as characteristics to be classified; then, characteristic sample points are projected to a characteristic space, linear judgment is performed in the characteristic space, and therefore nonlinear discrimination of an original input space can be achieved in an implicit mode. Due to the contribution that corresponding balance weight is adopted for adjusting sample nuclear matrixes, influences of unbalanced data on the classification performance can be overcome. Due to the adoption of the nonlinear mapping, the data processing capacity of a Fisher linear discrimination algorithm based on nucleuses is greatly improved. The experiment result shows that a high tumble mode average recognition rate is achieved through the method, and the recognition result is superior to that of other classification methods.

Description

technical field [0001] The invention belongs to the field of pattern recognition, and relates to a pattern recognition method based on electromyographic signals, in particular to a pattern recognition method for electromyographic signals of falls. Background technique [0002] Falls are a high incidence and high hazard accident among the elderly population. It is estimated that one in three people over the age of 65 experience a fall each year. Falls bring huge economic burdens to individuals, families and even society, and have become a health issue of concern to the whole society. Therefore, many institutions at home and abroad have begun research on fall detection and protection. [0003] Electromyography (EMG) is a bioelectrical signal triggered by muscle activity, which contains a wealth of information about muscle activity. Since the acquisition of surface electromyography (sEMG) is easy to pick up and non-invasive, many studies have successfully identified the acti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0488
Inventor 席旭刚左静李成凯罗志增
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