Through-The-Body Localization Of Implanted Biochip In Wearable Nano-Biosensing Networks

Recent developments of nanotechnology are enabling new smart health monitoring and diagnosis systems based on wearable nano-biosensing networks. Such systems consist of at least one biochip implanted inside the human body and a wearable device that can activate nanosensors on the biochip and take measurements. Due to the motion of the human body, the wearable device may become misaligned with the implanted biochip. Since passive nanosensors and weak signals are utilized to protect biological tissues, such misalignment can significantly impact the sensing accuracy and even feasibility. Therefore, the relative position between wearable device and the implant has to be determined so that the wearable device can compensate the impacts of misalignment. There are two critical problems of through-the-body localization: 1) reflections from the biochip behind biological tissues are shadowed by reflections from tissues, which tend to dominate a long duration of time, and 2) the position of the implanted biochip cannot be calculated with a specific model of biological tissues. In this paper, a through-the-body (TTB) localization mechanism is proposed to estimate the position of implanted biochip without a priori knowledge of biological tissues of human body. The localization mechanism utilizes spatial filtering to mitigate reflections from biological tissues and uses support vector machine (SVM) regression to estimate the position of the implanted biochip. Through the analytical modeling and numerical simulations, it is shown that the reflections from biological tissues can be effectively mitigated by spatial filtering and SVM regression can estimate the position of the implant with high accuracy.