Introduction

The benchmark suite at this website aims to provide information about the state-of-the-art in bioelectromagnetic (BioEM) simulation methods for computing electromagnetic scattering from human models illuminated by impressed time-harmonic sources in the UHF band (300 MHz-3 GHz).

Such simulations are important in the design of body-centric wireless communication systems, wireless implants, and medical imaging systems. They are also needed to develop body-area networking standards and to ensure that exposure to non-ionizing radiation remains lower than values specified in safety standards. As a result of decades long research and development efforts in computational electromagnetics and advances in computer hardware/software infrastructure, today, a large (and expanding) set of computational methods are available for performing such BioEM simulations [1]. Indeed, various commercial and academic simulation tools currently rely on implementations of these methods. It is becoming more and more difficult to identify the “best” simulation method among alternatives to solve a BioEM problem of interest or to determine “how much better” one method is over others [2] because

• a large and increasing number of competitive methods can be used
• underlying computer hardware/software infrastructure continues to evolve rapidly
• a high level of expertise is needed to apply specialized methods effectively
• methods are often evaluated primarily by their developers, who become judge, jury, and executioner of their own work; such assessments are prone to intentional or unintentional biases and over-optimistic performance estimates [3]

As a result, there is an increasing risk that BioEM simulation methods will be judged primarily on subjective factors (e.g., generality, simplicity, familiarity/popularity, or user friendliness) rather than objective scientific/engineering merits (e.g., accuracy, efficiency, scalability) [2]. It is our contention that publicly available verification, validation, and performance benchmarks like those presented at this website can

• help systematically combat the problem of the ubiquity of error [4]
• inform researchers in the field and the public about the state of the art
• lower barriers to entry for new researchers/methods
• reduce importance of subjective factors when judging simulation methods
• increase the credibility of the results obtained and claims made by computational scientists and engineers