Waist vertical spine muscle activity identification and prediction method based on unidirectional video signals

A video signal and activity recognition technology, applied in the field of ergonomics, can solve problems such as inability to correspond to subjective habits or subtle pain sensations, complex modeling methods, etc.

Pending Publication Date: 2020-03-06
SHANGHAI DIANJI UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Modeling approaches are too complex to account for the influence of interacting

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
  • Waist vertical spine muscle activity identification and prediction method based on unidirectional video signals
  • Waist vertical spine muscle activity identification and prediction method based on unidirectional video signals
  • Waist vertical spine muscle activity identification and prediction method based on unidirectional video signals

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] Attached below Figure 1-3 The present invention is further illustrated with specific examples.

[0023] The execution steps of this embodiment are described in detail below.

[0024] Measurement steps:

[0025] Firstly, the electromyography is collected in the laboratory, and the electromyographic signals of the right trapezius muscle and the longissimus lumbosus on both sides are collected synchronously, as well as the movement information of key points in 22 main parts of the whole body; these points are captured using the (Cortex) synchronization platform The position, velocity, and acceleration of the spine; the C7 cervical vertebrae, the S1 lumbar vertebrae, and their body surface midpoints are all used to express the posture of the spine; other key points are located at the main joints of the limbs and the top of the head.

[0026] The EMG high and low pass selection is 20-500HZ; complete the MVC measurement of different muscles (at this stage only include 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 relates to the technical field of ergonomics, in particular to a waist vertical spine muscle activity recognition and prediction method based on unidirectional video signals. The methodat least comprises the following steps: a measurement step firstly includes a signal acquisition sub-step, and when the signal acquisition sub-step is carried out, the electromyographic signals of a right trapezius muscle and longissimus lumbar muscles on two sides and motion information of key points of main parts of the whole body are synchronously acquired; a two-step clustering identificationstep comprises a pre-clustering sub-step and a quasi-clustering sub-step, and also comprises a step of constructing a clustering feature tree so as to divide the clustering feature tree into a plurality of sub-clusters; and a prediction step is based on the artificial neural network, multi-person comparison is carried out on signals for a long time. A part of target actions are recognized in the complex and long-time labor process, and on the basis of action recognition, muscle power generation percentage prediction can be conducted on tasks trained in a laboratory.

Description

technical field [0001] The invention relates to the technical field of ergonomics, in particular to a system for recognizing and predicting the activity of the erector spinae of the waist. Background technique [0002] There are following defects in the prior art. [0003] Because the conditions of electromyography testing require the contact interface to be stable, factors such as sweating and skin stretching will cause drastic changes in the results, and under working conditions, it is difficult to carry out large-scale electromyography (emg) acquisition for in-depth research on the causes of injuries and diseases Still restricted. The main reason is that the monitoring of human actions in the working environment faces a variety of possibilities, and the result of direct measurement takes too long, and many actions need to be eliminated based on classification and then identified. [0004] Also because it is difficult to simultaneously track EMG data and 3D motion data. ...

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): A61B5/0488A61B5/22
CPCA61B5/224A61B5/7267A61B5/389
Inventor 王琦祝程华
Owner SHANGHAI DIANJI UNIV
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap