Center Offers Hands-On, Deep Learning Short Course for the Processing of Biosignals

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Headquartered at North Carolina State University, the NSF-funded Engineering Research Center (ERC) for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST) offered a deep learning short course for processing biosignals in December 2021. The course introduced students to cutting-edge approaches for applying data-driven learning to fields like healthcare.


Machine learning, and deep learning specifically, has the capacity to perform complex tasks using data-driven methods. Participants in this course were introduced to a state-of-the-art library for deep learning and engaged with tutorials about how to process biosignals, such as detecting cough events from acoustic signals.


Deep learning is a type of machine learning and artificial intelligence that imitates the way humans acquire certain types of knowledge. Deep learning has the potential to perform complex tasks, as well as to collect, analyze, and interpret large amounts of data. Over three sessions, instructors Edgar Lobaton, Ph.D., and Chau-Wai Wong, Ph.D., provided a brief introduction to the concept of deep learning and some of its most popular mechanisms. Students learned how to apply these techniques to the processing of biosignals, such as a beating heart or a contracting muscle.