Early-stage autism screening system based on joint attention ability test and audio-video behavior analysis

Abstract

The invention discloses an early-stage autism screening system based on a joint attention ability test and an audio-video behavior analysis. Audio-video multimodal data of an evaluator and a testee iscollected and analyzed so as to evaluate and predict autistic spectrum disorders. The system includes a data acquisition module, a preprocessing module, a feature extraction module, a training classification module and a prediction module. The data acquisition module is used for multi-view and multi-channel collection of the audio-video multimodal data of the evaluator and the testee in a test; the preprocessing module synchronously collects the audio-video data, detects and marks the time when the evaluator issues a command through voice recognition, and extracts and analyzes an audio videoafter the point in time; the feature extraction module is used for feature extraction of the pre-processed audio-video data, and speech content, facial emotions and other features are obtained; the training classification module takes the extracted combination features as an input of a machine learning classifier for training, and a classifier model for predicting the autism is obtained; by usingthe classifier model obtained through training, the prediction module performs autism classification and prediction on the testee whose data is collected.

Description

technical field [0001] The present invention relates to the fields of image processing and speech recognition, and in particular to an early screening system for autism based on joint attention ability test and audio-video behavior analysis. state data and analyzed to evaluate a system for predicting autism spectrum disorder. Background technique [0002] Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder in children. Since autism mainly affects the ability of social communication, behavior, interest, etc., its screening evaluation is mainly realized through manual diagnosis by experienced professional medical personnel. However, this requires extremely high professionalism and experience of medical staff, which makes it difficult to popularize purely manual screening methods. Therefore, more and more scientific research teams are investing in the study of how to use artificial intelligence equipment to assist in the careful assessment of autism. Among...

AI Technical Summary

Problems solved by technology

These methods only analyze the short-term behavior of children after receiving stimulation, and do not consider the interaction between children and the outside world after receiving stimulation and various other activities that cannot be controlled

Moreover, video analysis from a single angle makes it difficult to accurately capture complete test data and accurately assess the risk factor of children suffering from autism

Images