Automating Peak Flow Data Extraction for Asthma Monitoring and Management
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UNIVERSITI MALAYSIA SARAWAK
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Asthma is a common chronic condition that requires consistent monitoring to effectively manage symptoms and prevent exacerbations. Traditional peak flow meters, although affordable and accessible, rely on manual recording, making them prone to error and limiting their reliability. Digital alternatives, while accurate, are expensive and complex, posing accessibility challenges for many users. This project bridges the gap by developing a system that automates the extraction of peak expiratory flow (PEF) readings from manual peak flow meters using image processing techniques. The system uses OpenCV for preprocessing and Tesseract.js for Optical Character Recognition (OCR), ensuring accurate and reliable data capture. A user-friendly Web Application allows patients to record, track and visualize their respiratory data while maintaining affordability and ease of use. Through extensive testing across multiple conditions, the system demonstrated its robustness, providing an accessible and effective solution for asthma monitoring. By integrating advanced image processing with manual devices, the project improves asthma care, ensuring equity and accuracy for a diverse user group.