Gesture recognition system fusing bioelectrical impedance information and myoelectricity information

Abstract

The invention discloses a gesture recognition system fusing bioelectrical impedance information and bioelectromyographic information. The gesture recognition system comprises a power module, an electrical impedance information acquisition module, a bioelectromyographic signal acquisition module, a microcontroller module, a wireless transmission module and an upper computer, wherein the upper computer comprises a data fusion module and a machine learning classification module. The electrical impedance information acquisition module is responsible for acquiring impedance distribution informationinside a wrist, the bioelectromyographic signal acquisition module is responsible for acquiring arm electromyographic information, and under coordination control of the microcontroller, the two kindsof biological information are transmitted to the upper computer through the wireless transmission module to be subjected to data processing. And on the upper computer, the two kinds of biological information are fused through a data fusion processing algorithm, and training and gesture recognition completion are carried out by adopting a machine learning classification algorithm. Through the fusion of the two biological signals, the robustness and diversity of the gesture recognition method can be enhanced, and the accuracy of the gesture recognition method is improved.

Description

technical field [0001] The invention relates to the field of gesture recognition in the field of human-computer interaction, in particular to a method for merging bioelectrical impedance signals and biomyoelectric signals for gesture recognition. Background technique [0002] With the continuous development of computer technology, human-computer interaction has attracted more and more attention from researchers. However, traditional human-computer interaction methods such as mouse and keyboard can no longer meet the needs. New human-computer interaction methods pay more attention to humanization and perception. interact. As the most flexible limb of the human body, hands can express rich meanings through gestures, especially for deaf people, sign language is the most important way for them to communicate with the outside world. Therefore, the research on gesture recognition has always been an important content in the field of human-computer interaction. [0003] Gesture re...

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