AI Analysis Apparatus for ASD Diagnostic Support
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Solution Overview
Problem
Current ASD diagnostic tools rely heavily on observational assessments by specialists, which are time-consuming and often delayed, lacking objective and efficient screening methods.
Innovation Solution
An interaction-based AI analysis apparatus and method that structures video content to elicit interactions from examinees, collects response data through cameras and microphones, and analyzes this data using AI modules corresponding to evaluation indices, thereby providing objective diagnostic support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If observational assessments by specialists are used for ASD diagnosis, then diagnostic accuracy can be maintained, but the process becomes time-consuming and delayed
Solution Approach 1:
The patent replaces the mechanical system of specialist observation and manual assessment with an automated AI-based analysis system. The apparatus uses cameras and microphones to capture examinee responses, then employs AI modules to automatically analyze video and audio data for ASD diagnostic indicators, eliminating the time-consuming manual observation process while maintaining diagnostic accuracy through multiple evaluation indices.
Solution Approach 2:
The system enables self-service by allowing the examinee to complete the assessment independently without requiring a specialist's continuous observation. The automated apparatus captures and analyzes responses autonomously, with the AI system performing all diagnostic evaluation functions that previously required specialist intervention, thereby dramatically reducing diagnosis time.
2Measurement precision
If multiple AI analysis modules are executed to comprehensively evaluate examinee responses, then analysis accuracy improves, but computing resource consumption increases
Solution Approach 1:
The patent segments the comprehensive AI analysis into multiple independent analysis modules, each dedicated to specific evaluation indices such as eye contact detection, facial expression analysis, and speech pattern recognition. This segmentation allows the system to execute only the necessary modules based on the examinee's responses, improving analysis accuracy through specialized evaluation while reducing overall computing resource consumption by avoiding unnecessary analysis.
Solution Approach 2:
The system implements partial action by selectively executing AI analysis modules based on the specific evaluation requirements and examinee responses. Rather than running all possible analysis modules simultaneously, the system activates only those modules needed for the current diagnostic assessment, thereby maintaining high analysis accuracy while optimizing computing resource utilization.
Data Source
AI summary
Disclosed herein are an interaction-based artificial intelligence analysis apparatus and method. The interaction-based artificial intelligence analysis apparatus is configured to output structured video content for each evaluation index so as to elicit an interaction to an examinee at each stimulus time-frame of a preset timeline, collect response data of the examinee for each evaluation index through a camera and a microphone at each response time-frame of the preset timeline, and analyze the response data for each evaluation index using an Artificial Intelligence (AI) analysis module corresponding to the evaluation index.