Design and Evaluation of an Inductive Powering Unit for Implantable Medical Devices Using Gpu Computing

Abstract

Nowadays inductive powering has become a widely spread technique in existing and emerging implanted medical devices (IMD). The geometry of coils couple plays a key role in the design, optimization and evaluation of a biomedical inductive powering unit (IPU). We have proposed a relatively fast method for an execution of these procedures, which is based on a mutual induction calculation using GPU parallel computing. Generally, our approach is to calculate mutual inductance as a function of uncontrolled (axial distance, lateral distance, inclination) and controlled (coils radii, turns numbers, distance between turns) geometric parameters of a coil couple. Calculated geometric functions in its turn are used in the design and optimization procedure to evaluate an IPU performance (e.g., load power). Achieved time gain of the GPU calculations in comparison with the host CPU computing is up to 80 for sequential summation and up to 8 for parallel computing. Also, it is shown that precision of our method is comparable to the precision of existing electromagnetic field solvers, and at the same time, computation time is substantially less (time gain is about 7 . . . 8 for 2D case and about 100 and higher for 3D case). Additionally, we have verified our method experimentally and shown that results of the calculations are accurate enough to predict real IPU performance. Finally, we have given an example of an IPU design optimization using geometric functions calculated with the help of the proposed method.

An Algorithm for the Computer Aided Design of Coil Couple for a Misalignment Tolerant Biomedical Inductive Powering Unit

“…One can obtain expression for a mutual inductance of a coil couple M C with turns number N and K [42]…”

“…The time lapse this high can be considered as significant and even excessive. It must be mentioned that simple CPU computing (clock rate 3.6 GHz) was used instead of more complex and expensive GPU techniques presented in the authors earlier work [42]. Thus, the optimization run with lower discretization (I , J = 60) was performed to evaluate how the discretization affects the results and time lapse.…”

“…In other words, the IPU performs well when misalignments are less than the difference between external diameters of transmitting and receiving coils. Among these relatively simple approaches, more sophisticated methods for optimization of the coils geometry exist [40]- [42]. These methods usually include an adjustment of various coil characteristics such as fill factor (e.g., ratio of the internal radius of a coil to the external one) [40], [41], pitch or line width for the printed coils [41] and turns number [42].…”

“…Thus, geometric optimization of an IPU cannot be considered a general solution. Nevertheless, it can be argued that the geometry of coils represents the single most important factor in the IPU design, because it directly affects the mutual and self-inductances, and, consequently, the coupling coefficient [41], [42]. Therefore, coils geometry optimization may be considered as a necessary first step in the IPU design process.…”

“…It also should be mentioned that optimization of the coils geometry can be performed in a wide variety of ways by changing of the various parameters (external and internal diameters, turns number, pitch). Thus, it is desirable to have a formal design procedure which can be performed automatically [42]. In this paper, such a procedure is devised.…”