ENTEG Seminar by Elisabeth Wilhelm

Human-centered control for medical devices

abstract: Symptoms of diseases vary over time and differ between individuals. To provide optimal support medical devices for prevention, treatment, and rehabilitation need to adapt to the needs of individual users in real-time. Unobtrusive sensing in combination with machine learning techniques allows estimation of the health state of a user. This information can be used for controlling medical device and enabling data-driven therapy. Within this talk, data-driven solutions for treating sleep-related breathing disorders, providing neurorehabilitation, and supporting prevention will be discussed.