Implant Localization in Human Body Using Adaptive Least-Squares Based Algorithm

In this study, we focus on the problem of localizing an implant or a capsule device in the human body by a mobile sensor unit using distance measurements. As a particular distance measurement technique, time of flight (TOF) based approach involving ultra wide-band signals is used, noting the important effects of the medium characteristics for different organs and tissue. We propose a least-squares based adaptive algorithm with forgetting factor to estimate the 3-D location of an implant in the human body. After discussing convergence properties of the proposed localization algorithm, we perform simulations to analyze the transient characteristics of the proposed algorithm. Different white Gaussian noises are added to emulate the TOF measurement noises and environmental disturbances, and it is observed that the proposed algorithm is robust to such noises/disturbances. The algorithm is successful in keeping the estimation error at a very low admissible level.