Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices.

A magnetoelectric antenna (ME) can exhibit the dual capabilities of wireless energy harvesting and sensing at different frequencies. In this article, a behavioral circuit model for hybrid ME antennas is described to emulate the radio frequency (RF) energy harvesting and sensing operations during circuit simulations. The ME antenna of this work is interfaced with a CMOS energy harvester chip towards the goal of developing a wireless communication link for fully integrated implantable devices. One role of the integrated system is to receive pulse-modulated power from a nearby transmitter, and another role is to sense and transmit low-magnitude neural signals. The measurements reported in this paper are the first results that demonstrate simultaneous low-frequency wireless magnetic sensing and high-frequency wireless energy harvesting at two different frequencies with one dual-mode ME antenna. The proposed behavioral ME antenna model can be utilized during design optimizations of energy harvesting circuits. Measurements were performed to validate the wireless power transfer link with an ME antenna having a 2.57 GHz resonance frequency connected to an energy harvester chip designed in 65nm CMOS technology. Furthermore, this dual-mode ME antenna enables concurrent sensing using a carrier signal with a frequency that matches the second 63.63 MHz resonance mode. A wireless test platform has been developed for evaluation of ME antennas as a tool for neural implant design, and this prototype system was utilized to provide first experimental results with the transmission of magnetically modulated action potential waveforms.

A 30% Efficient High-Output Voltage Fully Integrated Self-Biased Gate RF Rectifier Topology for Neural Implants.

This paper presents a fully integrated RF energy harvester (EH) with 30% end-to-end power harvesting efficiency (PHE) and supports high output voltage operation, up to 9.3V, with a 1.07 GHz input and under the electrode model for neural applications. The EH is composed of a novel 10-stage self-biased gate (SBG) rectifier with an on-chip matching network. The SBG topology elevates the gate-bias of transistors in a non-linear manner to enable higher conductivity. The design also achieves >20% PHE range of 12-dB. The design was fabricated in 65 nm CMOS technology and occupies an area of 0.0732-mm2 with on-chip matching network. In addition to standalone EH characterization measurement results, animal tissue stimulation test was performed to evaluate its performance in a realistic neural implant application.

Ultra-compact dual-band smart NEMS magnetoelectric antennas for simultaneous wireless energy harvesting and magnetic field sensing.

Ultra-compact wireless implantable medical devices are in great demand for healthcare applications, in particular for neural recording and stimulation. Current implantable technologies based on miniaturized micro-coils suffer from low wireless power transfer efficiency (PTE) and are not always compliant with the specific absorption rate imposed by the Federal Communications Commission. Moreover, current implantable devices are reliant on differential recording of voltage or current across space and require direct contact between electrode and tissue. Here, we show an ultra-compact dual-band smart nanoelectromechanical systems magnetoelectric (ME) antenna with a size of 250 × 174 µm2 that can efficiently perform wireless energy harvesting and sense ultra-small magnetic fields. The proposed ME antenna has a wireless PTE 1-2 orders of magnitude higher than any other reported miniaturized micro-coil, allowing the wireless IMDs to be compliant with the SAR limit. Furthermore, the antenna's magnetic field detectivity of 300-500 pT allows the IMDs to record neural magnetic fields.

A chip-less and battery-less subharmonic tag for wireless sensing with parametrically enhanced sensitivity and dynamic range.

Massive deployments of wireless sensor nodes (WSNs) that continuously detect physical, biological or chemical parameters are needed to truly benefit from the unprecedented possibilities opened by the Internet-of-Things (IoT). Just recently, new sensors with higher sensitivities have been demonstrated by leveraging advanced on-chip designs and microfabrication processes. Yet, WSNs using such sensors require energy to transmit the sensed information. Consequently, they either contain batteries that need to be periodically replaced or energy harvesting circuits whose low efficiencies prevent a frequent and continuous sensing and impact the maximum range of communication. Here, we report a new chip-less and battery-less tag-based WSN that fundamentally breaks any previous paradigm. This WSN, formed by off-the-shelf lumped components on a printed substrate, can sense and transmit information without any need of supplied or harvested DC power, while enabling full-duplex transceiver designs for interrogating nodes rendering them immune to their own self-interference. Also, even though the reported WSN does not require any advanced and expensive manufacturing, its unique parametric dynamical behavior enables extraordinary sensitivities and dynamic ranges that can even surpass those achieved by on-chip sensors. The operation and performance of the first implementation of this new WSN are reported. This device operates in the Ultra-High-Frequency range and is capable to passively and continuously detect temperature changes remotely from an interrogating node.

Integration of a Novel CMOS-Compatible Magnetoelectric Antenna with a Low-Noise Amplifier and a Tunable Input Matching.

A low-noise amplifier (LNA) topology with tunable input matching and noise cancellation is introduced and described in this paper, which was designed and optimized to interface with a magnetoelectric (ME) antenna in a 0.35 µm MEMS-compatible CMOS process. Compared to conventional antennas, acoustically actuated ME antennas have significantly smaller area for ease of integration. The LNA was simulated with an ME antenna model that was constructed based on antenna measurements. Input matching at the LNA-antenna interface is controlled with a circuit that varies the effective impedance of the gate inductor using a control voltage. Tunability of 455 MHz around 2.4 GHz is achieved for the optimum S11 frequency with a control voltage range of 0.3 V to 1.2 V. The proposed LNA has a noise cancelling feedback loop that improves the noise figure by 4.1 dB. The post-layout simulation results of the LNA show a 1-dB compression point of -7.4 dBm with an S21 of 17.8 dB.