Biosensory computing is the multidisciplinary study and development of systems and practices that sense, represent, communicate, and interpret biological signals from the body.
Biosignals are expansive in scope, and can enable a diverse range of biosensory computing applications. They can include physiological (e.g., ECG/PPG, EDA, EEG) and kinesthetic signals (e.g., accelerometry, eye gaze, facial expressions). Many inferences can be drawn about the person from these signals, including their activities, emotional and mental states, health, and even their identities, intentions, memories, and thoughts.
While generated by the person, biosensory data have important characteristics that distinguish them from other types of user-generated data. They are intimate yet leakable, precise yet ambiguous, familiar yet unverifiable, and have limited controllability. Therefore, responsible stewardship of biosensory data must be in place before the full potential of biosensory computing can be realized.
This multidisciplinary course will explore the intellectual foundations and research advances in biosensory computing. We will survey the range of biosensing modalities and technologies, study temporal and spectral data analysis and visualization techniques, interrogate the designs of novel biosensing applications, and tackle issues of user privacy and research ethics. Students signing up for the 3-unit option will continue in the second half of the semester with a student-led research project.