Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Handwriting recognition method based on surface electromyographic signal

An electromyographic signal and handwriting recognition technology, which is applied in the field of signal processing to solve the problem of difficult recognition.

Active Publication Date: 2010-12-29
上海念通智能科技有限公司
View PDF0 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Make the human-computer interaction

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
  • Handwriting recognition method based on surface electromyographic signal
  • Handwriting recognition method based on surface electromyographic signal
  • Handwriting recognition method based on surface electromyographic signal

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0031] The embodiments of the present invention will be described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention. Detailed implementation modes and specific operation procedures are given, but the protection scope of the present invention is not limited to the following implementations. example.

[0032] Such as figure 1 As shown, this embodiment includes the following steps:

[0033] The first step is to collect the surface EMG signal of the main muscle groups of the human forearm through the EMG signal acquisition device. The collected signal consists of 6 channels, corresponding to the brachioradialis, pronator teres, flexor carpi radialis, and palm length. The main muscle groups of the forearm of the flexor carpi ulnaris and superficial digita.

[0034] The second step, preset parameter stage 100:

[0035] (1) Notch the 50Hz power frequency interference, and use the Butterworth IIR digital filter to perform 10-20...

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 relates to a handwriting recognition method based on a surface electromyographic signal in the technical field of signal processing, which comprises the following steps of: obtaining a real-time electromyographic signal, computing the sequence number of a passage with the maximum contrast value and the signal mean value of the passage, manufacturing a real-time sample signal, determining the start time and the end time, manufacturing a training template of characters, and recognizing each written character of a user to obtain a recognition result. The invention is used for recognizing the character needing to be input by acquiring the surface electromyographic signal on a forearm to interact with a user terminal, so that a man-machine interactive system is more approximate to a natural state.

Description

technical field [0001] The invention relates to a recognition method in the technical field of signal processing, in particular to a handwriting recognition method based on surface electromyographic signals. Background technique [0002] EMG signals have important applications in artificial limb control, grasping recognition, human-machine interface and other fields. For EMG signal recognition, it can be roughly divided into signal detection, decomposition, processing and classification. [0003] Existing recognition methods usually treat non-stationary EMG signals as segmented stationary signals, and study the recognition of some static movements, such as fist stretching, fist clenching, turning up, turning down, cutting up, and cutting down. In recent years, due to the development of signal processing technology and mathematical models, various mathematical methods and artificial intelligence technologies have been applied in EMG signal processing, such as wavelet transfo...

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
IPC IPC(8): G06F3/01
Inventor 黄淦李顺冲盛鑫军朱向阳
Owner 上海念通智能科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com