Autism Aid is an application developed using Python, OpenCV, and the Google Speech Recognition libraries. This project aims to provide assistance in assessing the likelihood of autism in children aged 1-4. The application features various tests and functionalities to collect and analyze data, helping to identify potential signs of autism. Additionally, the project includes a research paper published in IEEE Xplore, discussing the analysis of autism and its characteristics.
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Assessment of autism likelihood: The application provides a range of tests to assess the likelihood of autism in children aged 1-4. These tests utilize computer vision techniques and speech analysis to evaluate specific characteristics associated with autism.
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Data storage using Google Firebase: Test results are securely stored in a Google Firebase database, ensuring data integrity and accessibility for further analysis.
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Statistical analysis: The project includes functionality to calculate the average percentage of autism based on test results. It also generates monthly and weekly scores for repeated tests, enabling monitoring and tracking of progress.
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Eye detection test accuracy: The eye detection test implemented in the application achieves an accuracy of 80%, enabling the detection of specific eye-related characteristics related to autism.
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Speech analysis test accuracy: The speech analysis test exhibits an accuracy of 86.7%, providing insights into speech patterns and characteristics that can aid in autism assessment for children.
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Python
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OpenCV
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Google Speech Recognition
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Google Firebase
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Clone the repository:
git clone https://github.com/your-username/autism-aid.git -
Navigate to the project directory:
cd autism-aid -
Install the required dependencies
- Run the application:
python autism_aid.py
- This will start the application, providing a user interface for conducting autism assessments.
- Perform an assessment:
- The application will guide you through the various tests and functionalities available.
- Follow the on-screen instructions to conduct the desired tests and collect data.
- The test results will be automatically stored in the Google Firebase database for further analysis.
- Analyze results:
- Use the provided functionalities to calculate the average percentage of autism based on test results.
- Generate monthly and weekly scores to track progress and observe changes over time.
Contributions to this project are welcome and appreciated. If you would like to contribute, please follow these steps:
- Fork the repository and create a new branch for your feature/bug fix.
- Commit your changes and push the branch to your forked repository.
- Submit a pull request with a detailed description of your changes.
- Please ensure that your contributions align with the project's coding style and adhere to best practices.
A research paper titled "Analysis of Autism and its Characteristics" has been co-authored for this project. The paper explores the analysis of autism and its associated characteristics, providing insights and findings based on the application's assessments. The paper is published in IEEE Xplore and can be accessed here.