Motion Pattern Analysis for Autism Diagnosis
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Solution Overview
Problem
Current methods for diagnosing and treating autism spectrum disorders (ASD) are ineffective in distinguishing different types of autism and tracking individual cognitive and treatment progress objectively.
Innovation Solution
The use of artificial agents, such as robots or screens, to measure motion patterns of subjects interacting with them, allowing for the differentiation between ASD and healthy individuals, and assessing the effectiveness of therapies by monitoring changes in motion patterns before and after treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current diagnostic methods are used for autism spectrum disorders, then diagnosis can be performed, but the ability to distinguish different types of autism objectively is insufficient
Solution Approach 1:
The patent replaces traditional mechanical/observational diagnostic methods with an optical measurement system using motion capture technology. The system uses cameras to record and analyze movement patterns, substituting subjective clinical observation with objective optical measurement and computational analysis of kinematic parameters.
Solution Approach 2:
The patent changes the diagnostic parameters from behavioral checklists and clinical observations to quantitative motion parameters such as velocity, acceleration, trajectory, and temporal patterns of movement. This parameter transformation enables objective differentiation of autism subtypes through mathematical analysis of movement characteristics.
2Measurement precision
If current treatment tracking methods are used, then treatment can be administered, but the ability to objectively track individual cognitive and treatment progress is insufficient
Solution Approach 1:
The patent implements continuous motion monitoring during natural interactions with artificial agents, allowing treatment progress to be tracked continuously rather than through discrete periodic assessments. This continuous measurement approach captures subtle changes in movement patterns that occur throughout the treatment process.
Solution Approach 2:
The system provides real-time feedback by comparing measured motion patterns against baseline data and treatment goals. The automated analysis immediately identifies improvements or deviations in movement parameters, enabling timely adjustments to treatment protocols based on objective progress indicators.
3Reliability
If artificial agents are used to measure motion patterns, then objective diagnosis and treatment tracking are achieved, but the interaction system becomes more complex
Solution Approach 1:
The artificial agents serve multiple functions: they engage the subject in natural interaction, provide the context for movement assessment, and act as the measurement interface. This multi-functionality reduces the need for separate diagnostic equipment while maintaining high reliability through the integration of engagement and measurement functions.
Data Source
AI summary
The present invention provides objective methods of diagnosis and behavioural treatments of neurological disorders such as autism spectral disorders and Parkinson's disease.