Can we automatically sense someone’s skill, stress, or well-being? With the surge of innovations in wearable devices (i.e., Garmin or Apple Watch), camera-based systems, and A.I.-driven methods, researchers have been exploring how sensor signals can reveal human activity, cognitive states, health status, and skills, and how these factors shape our work and daily life. Since 2010, our Interactive Technologies research group has been studying a variety of medical human factors. Through the close collaboration with clinicians, surgeons, and domain experts, we have developed computational methods that link objective measures from sensors with the subjective experiences, such cognitive workload, stress, listening efforts, and skill - the corner stones of expertise. In my talk, I will introduce our research lines and present several examples: dual eye tracking in novice training (in collaboration with Alberta University Hospital, Canada), deep learning-based instrument tracking and operation phase recognition (in collaboration with Kuopio University Hospital), and automatic recognition of Alzheimer disease progression from eye movements (in collaboration with Helsinki University Hospital, Kuopio University Hospital, and VTT, Finland). Our research bridges the fields of Computer Science, Cognitive Science, Social Sciences, and application domains (e.g., icrosurgery training, neurosurgery, and otolaryngology)