부산대학교 도서관

With the increased functionality of implantable medical devices (IMDs), real-time thermal management of these devices has gained growing attention to prevent overheating in the surrounding tissue of IMDs in certain applications, such as neural prostheses like deep brain stimulators (DBS). In this paper, a novel identification method is developed to predict the thermal dynamics of bio-implants, e.g. Utah electrode array (UEA). The proposed method adopts a thermal model with multiple heat sources to characterize the thermal dynamics of IMDs with multiple modules using the data collected by spatially distributed heat sensors. Algorithm predicts the temperature readings of heat sensors in an online fashion within a time window and updates the system parameters iteratively to improve the performance of the algorithm. Algorithm validation is realized using COMSOL software simulations as well as using an in vitro experimental system.