Self-reconfigurable micro-implants for cross-tissue wireless and batteryless connectivity

Abstract

We present the design, implementation, and evaluation of μmedIC, a fully-integrated wireless and batteryless micro-implanted sensor. The sensor powers up by harvesting energy from RF signals and communicates at near-zero power via backscatter. In contrast to prior designs which cannot operate across various in-body environments, our sensor can self-reconfigure to adapt to different tissues and channel conditions. This adaptation is made possible by two key innovations: a reprogrammable antenna that can tune its energy harvesting resonance to surrounding tissues, and a backscatter rate adaptation protocol that closes the feedback loop by tracking circuitlevel sensor hints. We built our design on millimeter-sized integrated chips and flexible antenna substrates, and tested it in environments that span both in-vitro (fluids) and ex-vivo (tissues) conditions. Our evaluation demonstrates μmedIC's ability to tune its energy harvesting resonance by more than 200 MHz (i.e., adapt to different tissues) and to scale its bitrate by an order of magnitude up to 6Mbps, allowing it to support higher data rate applications (such as streaming low-res images) without sacrificing availability. This rate adaptation also allows μmedIC to scale its energy consumption by an order of magnitude down to 350 nanoWatts. These capabilities pave way for a new generation of networked micro-implants that can adapt to complex and time-varying in-body environments. CCS CONCEPTS • Hardware → Full-custom circuits; • Computer systems organization → Sensor networks; • Applied computing → Life and medical sciences;

Batteryless, Wireless, and Secure SoC for Implantable Strain Sensing

“…The reasons why our design is particularly desirable for this application are multifold. First, our batteryless design eliminates the need for surgical replacement, mitigates the health hazards due to battery depletion risks for in-body implants, and reduces the overall size of the implant (since batteries can consume up to 50% of the volume of GI sensor) [1], [6] while directly integrating the power management with energy harvesting. Second, our built-in security builds on past work [7], [8] to bring privacy, confidentiality, and authentication to sensed in-body biometrics.…”

Content-agnostic backscatter from thin air

“…In recent years, ambient backscatter has attracted ever-growing attention as it is promising to deliver near zero-power communications for billions of tiny computing devices [18,32,39,41,42,49,54,57,60,63]. Different from traditional radio frequency identification (RFID) communications, it has three distinct features.…”

RectBoost: Start-Up Boosting for Rectenna Using an Adaptive Matching Network

“…However, it is shorter than that of far-field WPT (∼18 m) [3]. Secured power supply scalability of far-field WPT facilitates the development of many applications such as miniaturized battery-less backscatter sensor [4], radio frequency identification (RFID) localization technique [5], and power transfer for microchip implant [6].…”

“…To minimize overall system power dissipation, most batteryless nodes are usually turned off and they operate only for a short duty cycle by repeating cold start-up. For such nodes, a fast and efficient cold start-up is required to ensure their sensing and communication functionalities [6]. Hence, accelerating cold start-up is important to enhance the overall performance of battery-less nodes.…”

“…In [8], various matching networks are implemented to determine an optimum static matching network under a wide range of input powers. However, farfield wireless power transfer for mobile applications [4], [5], [6], is unpredictable in the upcoming IoT environment. Hence, the uncertainty causes divergent input power levels, thus threatening the current static impedance matching system.…”