Hexoskin has announced the publication of a groundbreaking study by its Artificial Intelligence research team in the journal ´Computers in Biology and Medicine´. The study unveils a novel algorithm designed to reliably detect coughs in real time, representing a significant step forward for remote respiratory monitoring. Hexoskin, known for its wearable biosensors and connected health solutions, aims to leverage this innovation to deepen clinical insights and support patient monitoring for both chronic and acute respiratory illnesses.
The new algorithm utilizes advanced machine learning techniques to accurately distinguish coughs from other ambient noises and physiological signals captured by Hexoskin´s smart garments. The technology enables continuous and automated tracking, minimizing false positives and providing healthcare professionals with actionable data. Such precision is particularly valuable for ongoing disease management, clinical trials, and public health research, especially in the context of monitoring COVID-19 and other respiratory conditions remotely.
By integrating this algorithm into its wearable product ecosystem, Hexoskin seeks to position itself at the forefront of digital health innovation. The company envisions broader applications—from assisting clinicians in early disease detection to enabling pharmaceutical research with objective endpoints for cough frequency and severity. This development underscores Hexoskin´s commitment to harnessing Artificial Intelligence for actionable health analytics and paves the way for more effective, data-driven care in respiratory medicine.
