Intelligent Autism Diagnostic Modular System
An intelligent AI-based system designed to analyze and predict Autism Spectrum Disorder (ASD) using multi-modal data such as vision, speech, and physiological signals. It combines computer vision, deep learning (CNN, LSTM), and real-time monitoring to track behavioral and emotional patterns. The system aims to support early diagnosis and assist caregivers and doctors in understanding and managing ASD more effectively.
Tech Stack
Tags
🧠 Intelligent Autism Diagnostic Modular System
📌 Executive Summary
An advanced AI-powered modular diagnostic system designed to analyze and predict Autism Spectrum Disorder (ASD) conditions in children using multi-modal data including vision, speech, physiological signals, and behavioral patterns.
This project leverages deep learning, time-series forecasting, and computer vision to assist medical professionals and caregivers in early diagnosis and continuous monitoring.
🧠 Problem Context
According to global health statistics, Autism Spectrum Disorder affects a significant number of children worldwide, with challenges including:
- Difficulty expressing emotions
- Limited communication abilities
- Complex behavioral patterns
- Lack of continuous monitoring tools
Key Challenge
How can we build a non-invasive, real-time AI system capable of analyzing multiple signals to predict and track ASD progression?
🎯 Objectives
- Detect emotional and behavioral patterns
- Track eye movement and attention
- Analyze speech signals
- Monitor physiological indicators (heart rate)
- Predict ASD state evolution over time
