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With the advent of ubiquitous sensing and real-time data processing, the demand for engineers with solid signal processing skills has exceeded the supply by a large margin. However, even students in technical subjects often perceive signal processing as demanding and somewhat dry [4]. 

By bringing research into the curriculum, this article explores new opportunities to refresh some classic signal processing courses. Since 2015, we in the Electrical and Electronic Engineering (EEE) Department of Imperial College London, United Kingdom, have explored the extent to which the level of student engagement and learning can be enhanced by inviting the students to perform signal processing exercises on their own physiological data.

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