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Abstract-Duty-cycled Medium Access Control (MAC) protocols certainly improve the energy efficiency of wireless networks. However, most of these protocols still suffer from severe degrees of overhearing and idle listening. These two issues prevent optimum energy usage, a crucial aspect in energy-constrained wireless networks such as Wireless Sensor Networks (WSN). Wake-up Radio (WuR) systems drastically reduce these problems by completely switching off the nodes' MicroController Unit (MCU) and main radio transceiver until a secondary, extremely low-power receiver is triggered by a particular wireless transmission, the so called Wake-up Call. Unfortunately, most WuR studies focus on theoretical platforms and/or custom-built simulators. Both these factors reduce the associated usefulness of the obtained results. In this paper, we model and simulate a real, recent and promising WuR hardware platform developed by the authors. The simulation model uses time and energy consumption values obtained in the laboratory and does not rely on custombuild simulation engines but rather on OMNET++ simulator. The performance of the WuR platform is compared with four of the most well-known and widely employed MAC protocols for WSN under three real-world network deployments. The paper demonstrates how the use of our WuR platform presents numerous benefits in several areas, from energy-efficiency and latency to packet delivery ratio and applicability, and provides the essential information for serious consideration of switching duty-cycled MAC-based networks to WuR.

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Wireless implants for interaction with the cortex have developed rapidly over the last decade and increasingly meet demands of clinical brain-computer interfaces. For such applications, well-established technologies are available, suitable for recording of neural activity at different spatial scales and adequate for modulating brain activity by cortical electrical stimulation. The incorporation of recording and stimulation into closed-loop systems is a major aim in active, fully implantable medical device design. To reduce clinical long-term implantation risk and to increase the spatial specificity of epicortical recordings and stimulation, micro-electrocorticography is a promising technology. However, currently there is a lack of implants suitable for chronic human clinical applications that utilize micro-electrocorticography and possess closed-loop functionality. Here, we describe the clinical importance of cortical stimulation, give an overview of existing implants that use mainly epicortical recording methods, and present results of a closed-loop microelectrocorticography system developed for clinical application within a collaborative framework. Finally, we conclude with our vision of future design options in the field of neuroprosthetic devices.

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