Infant three-dimensional spontaneous movement intelligent evaluation system based on complex network

Abstract

The invention discloses an infant three-dimensional spontaneous movement intelligent evaluation system based on a complex network. The intelligent evaluation system comprises a three-dimensional somatosensory information input module, a movement information feature extraction module, a computer with a complex network analysis module and a movement quality output module, wherein the output of the three-dimensional somatosensory information input module is connected with the input of the motion information feature extraction module, the output of the motion feature extraction module is connected with the input of the computer with the complex network analysis module, and the output of the computer with the complex network analysis module is connected with the input of the movement quality output module; according to the system, the movement characteristics of the infant can be comprehensively reflected, targeted complexity characteristic evaluation is carried out on spontaneous movement of the infant, and large-scale and intelligent popularization and application of infant cerebral palsy screening are met.

Description

technical field [0001] The invention belongs to the technical field of human body motion evaluation, and in particular relates to an intelligent evaluation system for infant three-dimensional spontaneous motion based on a complex network. Background technique [0002] Professional doctors can realize the early prediction of neurodevelopmental disorders such as cerebral palsy through clinical observation of infant spontaneous movement and analysis of movement characteristics, and promote neural remodeling by strengthening the intervention treatment of brain development process, thereby reducing the negative effects of cerebral palsy on children However, the training cycle of such early diagnosis methods is long and inefficient. In order to improve the efficiency of early screening of cerebral palsy in infants, computers and visual sensors can be used to assist doctors in completing the observation and analysis process, and provide strong technical support for early screening ...

AI Technical Summary

Problems solved by technology

However, the current motor assessment for the early prediction of infant cerebral palsy is mostly based on the statistical distribution of motion, which fails to consider the temporal change process of the motion itself, and cannot fully and essentially reflect the characteristics of the whole body motion. Low

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