Developing electronic medical devices is challenging. Simulations or in vivo experiments are not sufficient to obtain pertinent comparisons between potential design options. This paper presents a new artificial tool allowing objective comparisons between electronic device topologies. The main idea is to build a tool which is sensitive to targeted biological parameters only. These tools are generally called phantoms. The phantom presented in this paper is dedicated to IntraOcular Pressure (IOP) Measurement devices used in glaucoma diagnosis and treatment. It is called Biomechanical Eye Emulator (BEE). The BEE emulates the main biomechanical parameters influencing the IOP measurements. Because it is not sensitive to the living context, the BEE is the most efficient tool to investigate the best sensor design. BEE specifications are defined to be as close as possible to chosen models (humans or animals). Its efficiency is shown with a case study on rabbits. The results clearly demonstrate the BEE phantoms efficacy in providing objective assessment metrics during the sensor design process.

International audienceIn the context of mission-critical, safety-critical, and remote-controlled applications, it is required to equip systems with self-adapting capabilities. Adaptation is required in post-manufacturing to correct yield loss and achieve zero defective parts-per-million as well as during normal operation to account for different application scenarios and for varying environmental conditions. A self-adaptive system must be capable of providing the required high performances after manufacturing and throughout its normal operation regardless the application scenario wherein it is deployed and despite the varying environmental conditions. In this paper, we describe a generic post-manufacturing self-adaptation technique for RF circuits as well as concurrent self-adaptation techniques for a safety-critical medical sensor for glaucoma diagnosis and for a NFC system which is very sensitive to the environment in which it operates

Abstract-In this paper, a new model-based method is presented for the development of calibration technique of inductively coupled biosensors. This method is applied to the case of a lensbased intra-ocular pressure sensor. A new performance indicator is proposed. It is the 2 nd -order coefficient of the single-variable quadratic polynomial regression approximating the Bode phase plot of the system. This new indicator is reliable to significant distance and angle variations between primary and secondary and to small signal-to-noise-ratio.