Sonja Van Hala, Eliza Taylor, Susan Cochella
Leadership Development in Graduate Medical Education: A Pilot Study of Implementation of a Validated Self-assessment Instrument
Family medicine
growing importance data analytics biomedicine increasingly becoming recognized biomedical engineering curricula introduction machine learning classes generally run parallel separately traditional engineering courses signal systems analysis propose new approach systematically integrates signal processing systems analysis key techniques machine learning proposed course student obtains handson experience applying algorithms applied practical problems physiological signal conditioning analysis interpretation achieved exposing student sequence 4 applicationsbased modules represent different biomedical engineering problems human activity recognition wearable devices epileptic seizure detection quantification dynamic respiratorycardiac coupling humans different conditions detection sleep apnea episodes heart rate variability data within module student gains experience working data question ground also introduce general plan assessment student learning discuss expected outcomes limitations integrative approach teachingclinical relevance proposed course targeted biomedical engineering students senior undergraduate firstyear graduate level interested learning analyze physiological signals course would also suitable clinicianscientists prior training statistics exposure engineering mathematics