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An EMG Signal Recognition Method Based on Complexity, Fractal Dimension and Fractal Length

An electromyographic signal and recognition method technology, applied in the field of pattern recognition, can solve problems such as the need to further improve the real-time accuracy of multi-motion pattern recognition, and the unsatisfactory practicability of multi-motion pattern electromyography control research.

Active Publication Date: 2016-09-07
HANGZHOU DIANZI UNIV
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Problems solved by technology

However, the practicability of research on multi-sport EMG control is not ideal, and the key issues of multi-sport pattern recognition accuracy and real-time control need to be further improved

Method used

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  • An EMG Signal Recognition Method Based on Complexity, Fractal Dimension and Fractal Length
  • An EMG Signal Recognition Method Based on Complexity, Fractal Dimension and Fractal Length
  • An EMG Signal Recognition Method Based on Complexity, Fractal Dimension and Fractal Length

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Embodiment Construction

[0049] The embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings: this embodiment is implemented on the premise of the technical solution of the present invention, and provides detailed implementation methods and specific operating procedures.

[0050] Such as figure 1 As shown, this embodiment includes the following steps:

[0051] Step 1: Obtain the sample data of the human upper limb EMG signal, specifically: firstly pick up the human upper limb EMG signal through the EMG signal acquisition instrument, and then use the signal denoising method based on wavelet energy spectrum entropy to denoise the EMG signal containing interference noise noise cancellation.

[0052] (1) Collect the EMG signals of the upper limbs of the human body. The subjects performed 50 groups of clenching, stretching, wrist internal rotation and wrist external rotation respectively. The extensor carpi ulnaris and flexor carpi ulnaris of th...

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Abstract

The present invention proposes an electromyographic signal recognition method based on complexity, fractal dimension and fractal length to realize the synchronous control of the remote manipulator by the main operator in the remote operation robot system. The pattern recognition feature uses the L-Z complexity index and the fractal dimension index of the electromyographic signal, and the classifier uses an improved KNN model method that uses the clustering method as a means of data organization. This algorithm has incremental learning capabilities . The movement speed of the operator's hand depends on the activity intensity of the arm muscle group, which can be characterized by the maximum fractal length of the EMG signal. Within a certain range, the maximum fractal length of the EMG signal has a monotonically increasing relationship with the operator's hand movement speed. Taking the maximum fractal length of EMG signal as the input control quantity, the grasping speed control of the manipulator is realized, and a relatively ideal effect is achieved.

Description

technical field [0001] The invention belongs to the field of pattern recognition, and relates to a method for pattern recognition of electromyographic signals, in particular to a method for recognizing movement speed of upper limbs and multi-movement patterns based on electromyographic signals, which is applied to control a teleoperated robot. Background technique [0002] A teleoperated robot is an operator-robot symbiotic interactive system, whose function is to realize the operator's teleoperation and teleperception of the remote environment. Among them, teleoperation is the remote operation of the operator on the remote robot, and the human command is transmitted to the robot. The teleoperation requires the operator's instruction to be transmitted to the robot through an input interface. At present, there are many remote operation input interfaces, but most of them still have certain problems, such as unnatural input, single method, and ambiguity in information. Therefo...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06K9/66
Inventor 张启忠朱海港左静高云园罗志增席旭刚
Owner HANGZHOU DIANZI UNIV
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