Gesture identification system based on multiple forearm bioelectric sensors

A gesture recognition and multi-sensor technology, applied in the field of gesture recognition, can solve problems such as poor user experience, unreusable gesture data, difficulty in improving recognition accuracy, etc., and achieve the effect of precise gesture recognition system

Active Publication Date: 2015-12-30
BEIJING CHUANGSI BODE TECH CO LTD
View PDF4 Cites 25 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Gesture identification system based on multiple forearm bioelectric sensors
  • Gesture identification system based on multiple forearm bioelectric sensors
  • Gesture identification system based on multiple forearm bioelectric sensors

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] The present invention will be further described below in conjunction with the embodiment shown in accompanying drawing:

[0044] In the following description, elements are denoted using suffixes such as 'module', 'part' or 'unit' only for convenience of description of the present invention, and the suffixes themselves do not have any special meaning.

[0045] Such as figure 1 As shown, a gesture recognition system based on a forearm bioelectric multi-sensor in this embodiment includes a signal collection terminal A, a local server and a cloud server C, wherein the signal collection terminal A collects the data of the target gesture and sends it to The local server performs processing, including: collection module 101: setting several sensing units on the target gesture object for collecting bioelectrical signals and spatial motion signals of the target gesture object; The bioelectric signal and the spatial motion signal are subjected to denoising preprocessing, and the...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 姜晓丹刘勤何永振
Owner BEIJING CHUANGSI BODE TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products