Hand action mechanomyography based man-machine interaction method and interaction system
A technology of hand movement and human-computer interaction, applied in the field of human-computer interaction methods and interactive systems, can solve problems such as EEG signal interference and noise, achieve high sensitivity, strong anti-interference ability, and reduce the cost of the acquisition system
Inactive Publication Date: 2015-01-07
EAST CHINA UNIV OF SCI & TECH
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Abstract
The invention relates to a hand action mechanomyography based man-machine interaction method and an interaction system. The hand action mechanomyography based man-machine interaction method achieves a mouse click function due to collection of MMG (Mechanomyography) of a hand action and preformation of mode recognition on the MMG and achieves a mouse pointer movement function through hand movement information. The interaction system comprises an MMG sensor, an MMG processing circuit, an MMG biasing circuit, a data acquisition card, a mode recognition module, an interaction driving module and a hand movement information sensor; the MMG sensor, the MMG processing circuit, the MMG biasing circuit, the data acquisition card and the mode recognition module are sequentially connected; the interaction driving module is respectively connected with the mode identification module and the hand movement information sensor. Compared with the prior art, the hand action mechanomyography based man-machine interaction method has the advantages of being easy to achieve, high in accuracy and the like.
Description
technical field [0001] The invention relates to the application of muscle sound signals, in particular to a human-computer interaction method and an interactive system based on hand movement muscle sound signals. Background technique [0002] In the human-computer interaction system in the field of rehabilitation, most of the information sources for human-computer interaction are human biological signals. Finding a stable and complete information source and applying it to the human-computer interaction system is a hot and difficult point today. So far there have been many choices and attempts of different control signal sources. For example: Electromyography (EMG), EEG (Electroencephalography, EEG), sound information source, extended physiological proprioception information source, limb muscle circumference change information source, limb stump reconstruction finger control information source, limb machinery Sports information source, tendon information source, brain magne...
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IPC IPC(8): G06F3/01
CPCG06F3/015G06F2203/011
Inventor 夏春明董畅周静蒋志伟
Owner EAST CHINA UNIV OF SCI & TECH
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