HEALSound: Healthcare Education And Labeling for Cardiopulmonary Sounds

Advances in digital stethoscopes and wearable health sensors now support real-time cardiopulmonary monitoring and AI-driven diagnostic tools. However, the extensive manual labeling required for large datasets of respiratory sounds presents a significant barrier, traditionally dependent on expert input. To address this, we introduce HEALSound, a mobile application designed to blend educational training with crowdsourced data labeling. By engaging users in interactive auscultation exercises and providing immediate feedback, HEALSound promotes skill development while generating high-quality labeled data through weighted consensus methods. Experimental results highlight the app's dual effectiveness: enhancing diagnostic learning for users and accelerating the development of machine-learning models through enriched datasets, thus addressing critical challenges in AI-based health diagnostics.