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Hand action identification method based on surface electromyography decomposition

A recognition method and hand movement technology, applied in character and pattern recognition, computer components, instruments, etc., can solve problems such as increased sensors, noise interference, and increased system complexity

Active Publication Date: 2015-09-09
SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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  • Application Information

AI Technical Summary

Problems solved by technology

The increase in the number of sensors, on the one hand, increases the complexity of the system, on the other hand, it also brings greater noise interference, and due to the limitations of muscle shape and sensor volume, fewer sensors are used to recognize more gestures, is an important issue that needs to be resolved

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  • Hand action identification method based on surface electromyography decomposition
  • Hand action identification method based on surface electromyography decomposition
  • Hand action identification method based on surface electromyography decomposition

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Embodiment Construction

[0081] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0082] Such as figure 1 Shown is the method flow chart of the present invention, gathers the sEMG signal y of pronator quadratus muscle place t , and perform second-order differential filtering, the method is as follows:

[0083] x t =y t+2 -y t+1 -y t +y t-1

[0084] where x t is the filtered sEMG signal, and the subscript t is the sampling time.

[0085] For the filtered sEMG signal x t , for peak detection, the calculation formula of the threshold α is as follows:

[0086] α = c 1 [ Σ t = 1 T 1 x t 2 I ( α , t ) ...

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Abstract

The invention relates to a hand action identification method based on surface electromyography (sEMG) decomposition. The method comprises the following two parts including sEMG decomposition and a hand action identification method based on MUAPT (motor unit action potential train), wherein the sEMG decomposition is carried out to obtain the MUAPT and consists of sEMG signal preprocessing, sEMG peak detection and Gaussian mixture model (GMM) clustering; and the hand action identification based on the MUAPT comprises characteristic extraction, principal component analysis (PCA) dimensionality reduction, LDA (Linear Discriminant Analysis) classification and the like. Under a condition that only one channel sEMG is used, motor unit action potential information obtained by the sEMG signal decomposition is used for identifying hand action, an identification rate of single-channel sEMG is effectively improved, and the hand action identification method has important theoretical significance and practical application value.

Description

technical field [0001] The invention relates to the technical field of biological signal recognition, and specifically relates to a hand movement recognition method based on surface electromyography signal decomposition. Background technique [0002] Hand motion recognition has become one of the important methods of human-computer interaction, widely used in sign language recognition, prosthetic control, somatosensory game control, teleoperation and other fields. The hand movement recognition method based on electromyographic signal (sEMG) is real-time, convenient and non-invasive, and is more suitable for rehabilitation fields such as helping the elderly and the disabled, and has received more and more attention. [0003] Traditional hand motion recognition methods often use multiple channels of sEMG data [1-8] to extract the corresponding time domain [4,5], frequency domain [6,7], time-frequency domain [8] features, Use specific data classification algorithms [9-11] to co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
Inventor 韩建达赵新刚熊安斌丁其川赵忆文
Owner SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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