Over View
The medical device industry is leaping forward by relying on electronics to improve life-saving medical devices’ safety and performance. The complex electronics, including microchips and FPGAs, run powerful software that helped further improved usability. However, the complex electro-mechanical systems introduced a new set of failure modes that are often difficult to identify and mitigate through traditional test protocols. The evolution of technology in connectivity and data collection paired with sensors opens the door for preventive and predictive maintenance to mitigate failure in critical devices. The predictive and preventive maintenance strategy uses fault detection techniques leveraging data, signal, process, or knowledge-based methods. These techniques detect and prevent faults that otherwise would result in a failure causing a safety issue or degraded performance. Through our independent study, we will be surveying the state of the art Fault Detection and Prediction algorithms and perform a feasibility study to understand the applicability to medical devices.
Team
Advisor: Dr. Vahid Behzadan
GitHub: N/A
Publications: N/A
Sponsor: Medtronic Plc