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Hand Training and Evaluation Method Based on Myoelectric and Inertial Information

A myoelectric and inertial technology, applied in the field of virtual myoelectric feedback, can solve problems such as single mode and lack of fatigue feedback adjustment, and achieve the effect of accelerating health recovery, accelerating hand rehabilitation speed and rehabilitation effect, and ensuring high efficiency

Active Publication Date: 2022-04-19
YANSHAN UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, the current rehabilitation training has defects such as single mode and lack of fatigue feedback adjustment.

Method used

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  • Hand Training and Evaluation Method Based on Myoelectric and Inertial Information
  • Hand Training and Evaluation Method Based on Myoelectric and Inertial Information
  • Hand Training and Evaluation Method Based on Myoelectric and Inertial Information

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Embodiment Construction

[0058] In order to elaborate the technical content, achieved purpose and effect of the present invention, the following will be described in detail in conjunction with the accompanying drawings.

[0059] like figure 1 As shown, the hand training and evaluation method based on EMG and inertial information mainly collects EMG signals on the first side, transmits them wirelessly to the host computer, and processes them through the host computer software MATLAB. (LOF) common space mode (CSP) improved algorithm extracts data features, and classifies and processes through support vector machine (SVM), distinguishes the actions of the first side, and wirelessly transmits the action instructions to the wearable device worn on the second side. The wearable rehabilitation manipulator enables the second side to complete the same action, combining different virtual scenes and leap motion to realize the virtual and real interaction between the left and right virtual hands and the real hand...

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Abstract

The present invention provides a kind of hand training and evaluation method based on myoelectricity and inertial information, the steps are as follows: S1, according to different training intensity, design two kinds of virtual training scenes; One side is connected with the second side, and the myoelectric inertial signal collected is transmitted to the host computer; S3, before entering the virtual training scene, the action training prompt of the virtual training scene in S1 is used for classifier training; S4, the The myoelectric signal of the first side collected by S2 is preprocessed and feature extracted by S3, and sent to the classifier trained by S3 to distinguish actions to generate corresponding action instructions; S5, the action instructions generated by S4 are transmitted to the rehabilitation In the manipulator, complete the corresponding action; S6, evaluate the result after the training of the action trained in S5. The present invention utilizes the cooperative movement of the first side and the second side, and combines the rehabilitation manipulator to assist the second side in grasping training, thereby accelerating hand rehabilitation speed and rehabilitation effect.

Description

technical field [0001] The invention relates to the field of virtual myoelectric feedback, in particular to a hand training and evaluation method based on myoelectricity and inertial information. Background technique [0002] Stroke, commonly known as apoplexy, is the most common and most frequent cerebrovascular disease. According to the 2016 Global Burden of Disease Study, due to life and work pressure, irregular life and other reasons, stroke is not only prone to occur in the elderly, the first batch of post-90s It has also become a high-risk group for stroke. An article in the authoritative international magazine "circulation" pointed out that my country is currently a big country with stroke, and the incidence rate is very high. Studies have shown that more than 75% of stroke patients have varying degrees of limb dysfunction, which affects personal health and family happiness. If not treated in time or handled properly after a stroke, it may lead to hemiplegia or even...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A63B23/16A63B71/06A61B5/389A61B5/11A61H1/02
CPCA63B23/16A63B21/00181A63B24/0062A63B71/0622A61B5/389A61B5/7203A61B5/725A61B5/7267A61B5/1101A61H1/0274A61H1/0218A61H2201/1657A63B2220/40A63B2230/60
Inventor 谢平蔚建王子豪王颖王新宇于金须焦云涛陈晓玲李增勇
Owner YANSHAN UNIV
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