Early Health Alerts From Implanted Medical Devices

ECE Assistant Professor Francesco Restuccia and ECE William Lincoln Smith Professor Tommaso Melodia were awarded a patent for “Embedded networked deep learning for implanted medical devices.”

Abstract Source: USPTO

A deep learning medical device implantable in a body is provided. The device includes a processing and communication unit and a sensing and actuation unit. The processing and communication unit includes a deep learning module including a neural network trained to process the input samples, received from the sensing and actuation unit, through a plurality of layers to classify physiological parameters and provide classification results. A communication interface in communication with the deep learning module receives the classification results for ultrasonic transmission through biological tissue. Methods of sensing and classifying physiological parameters of a body and methods of embedding deep learning into an implantable medical device are also provided.

Related Faculty: Francesco Restuccia, Tommaso Melodia

Related Departments:Electrical & Computer Engineering