Developing and validating a wearable device to assess cardiac function during sleep

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This proposal describes the development and validation of signal processing algorithms based on heart sound analysis to detect the risk and symptoms of cardiovascular disorders such as hypertension, stroke, and heart disease. In a close collaboration with BresoTec Inc, this work will improve management of breathing disorders during sleep and their cardiovascular consequences. In particular, this project will develop robust algorithms to detect heart rate, blood pressure, and cardiac function. The proposed algorithms can be used for tele-monitoring of cardiac function and diagnosing the risk of cardiovascular disorders when the patients are at home, such as during sleep, or during everyday activities.The workplan involves two projects that will address two objectives of the project. The first objective is to detect heart sounds with high accuracy during sleep and to extract them from other sounds that will be recorded simultaneously, such as breathing sounds, snoring and ambient noise. The second objective will focus on developing models and signal processing algorithms to estimate cardiac function parameters from the extracted heart sounds. Both projects are based on the algorithms that we have developed recently for analyzing respiratory and heart sounds, and both will uniquely benefit the industry.BresoTec Inc is strongly supporting this project through both cash and in-kind contribution. BresoTec Inc has established a track record of collaboration with the research group in the past three years. BresoTec Inc is uniquely positioned to leverage the research and HQP outputs of the proposed research program.