System for intelligently assessing general movement quality

Abstract

The invention discloses a system for intelligently assessing general movement quality, which comprises multiple three-dimensional movement capturing cameras, a light high-reflectivity marking ball and a host, wherein the multiple three-dimensional movement capturing cameras are uniformly distributed, and the front ends are marking point central calculus function processing chips adopting circle fitting algorithms; the light high-reflectivity marking ball is captured by the movement capturing camera; the movement capturing camera captures and photographs and records a characteristic movement video of the light high-reflectivity marking ball; the characteristic movement video is inputted to the host; five sections of standards are divided according to GMs by the host, each section is pre-defined, a standard GMs database is stored and built in the host system, the host imports the characteristic movement video, movement target detection is carried out on the video, and later diagnosis accuracy rate is improved effectively. The field and the target can be away, and remote operation is realized.

Description

Technical field [0001] The invention relates to an intelligent assessment system for the quality of whole body exercise. Background technique [0002] General movement assessment (generalmovementsassess-ment) is an evaluation technique proposed by Prechtl in the 1990s, referred to as GMs. In order to facilitate the evaluation, the GM Association has established the criteria for defining normal and abnormal GMs. The pattern of normal GMs is not static. GMs of premature infants are divided into three stages of development: premature birth, twisting movement, and restless movement; GMs of term infants are divided into two development stages: twisting movement and restless movement. Each stage has its characteristic movement pattern. Nowadays, manual judgment is generally used, which is time-consuming, easy to make mistakes, and requires on-site judgment. The judgment result is the data basis. Once the data is wrong, misdiagnosis is easy to occur. Summary of the invention [0003] ...

AI Technical Summary

Problems solved by technology

Nowadays, manual judgment is generally used, which takes a long time, is prone to mistakes, and requires on-site judgment. The judgment result is based on data. Once the data is wrong, misdiagnosis is prone to occur.