Gesture identification system based on multiple forearm bioelectric sensors

Abstract

The invention discloses a gesture identification system based on multiple forearm bioelectric sensors. A local server of the gesture identification system stores gesture data which is completed in characteristic extraction and fusion and uploads the gesture data to a cloud server when the system is networked. The local server establishes a local gesture models according to the gesture data. The cloud server receives the gesture data uploaded by one or more local servers, establishes cloud gesture models and updates the gesture models in each local server with the cloud gesture models, so that the local end and the cloud end of the gesture identification system are respectively provided with a data set module, a classifier model module and an identification module, a user is enabled to carry out gesture identification even under an offline condition, and the gesture identification system is suitable for a moving scene whose network environment changes in real time; in addition, the local gesture models in the local server are updated by the cloud gesture models, so that the gesture identification of the gesture identification system is more precise.

Description

technical field [0001] The invention relates to gesture recognition, in particular to a gesture recognition system based on forearm bioelectric multi-sensors. Background technique [0002] Gesture is the most widely used way of communication in people's daily life. In recent years, with the rapid development of computer technology, the research of gesture recognition technology has made great progress. Natural and intuitive communication is introduced into the human-machine interface. [0003] At present, there are mainly two recognition methods for existing gesture recognition devices: the first one uses computer vision methods, and the basic principle is: through optical sensors such as cameras, continuously capture frame image data, and then use image recognition technology to recognize user's gestures; The second method uses a single bioelectric method. The basic principle is: through a number of bioelectric electrodes placed on the skin surface of the user's arm, the c...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to overcome the technical problems in the prior art that the gesture data of different users cannot be reused, the recognition accuracy is difficult to improve, and the user experience is poor, so as to provide a gesture data that can be reused by different users. Gesture Recognition System for Accurate Recognition of Gesture Information

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