Cough Detection

Cough detection research aims to develop accurate and efficient methods for identifying and classifying coughs using audio analysis, often leveraging wearable sensors like smartwatches and earbuds. Current research heavily utilizes deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs like LSTMs), and vision transformers, to analyze cough audio features and distinguish between healthy coughs and those indicative of specific respiratory diseases (e.g., COVID-19, tuberculosis). This work is significant for its potential to provide objective, remote diagnostic tools for respiratory illnesses, improving disease surveillance, monitoring treatment efficacy, and facilitating early intervention.