Stephen O'Driscoll

Optimal Frequency for Wireless Power Transmission Into Dispersive Tissue

RF wireless interface enables remotely-powered implantable devices. Current studies in wireless power transmission into biological tissue tend to operate below 10 MHz due to tissue absorption loss, which results in large receive antennas. This paper examines the range of frequencies that will optimize the tradeoff between received power and tissue absorption. It first models biological tissue as a dispersive dielectric in a homogeneous medium and performs full-wave analysis to show that the optimal frequency is above 1 GHz for small receive coil and typical transmit-receive separations. Then, it includes the air-tissue interface and models human body as a planarly layered medium. The optimal frequency is shown to remain in the GHz-range. Finally, electromagnetic simulations are performed to include the effect of load impedance and look at the matched power gain. The optimal frequency is in the GHz-range for mm-sized transmit antenna and shifts to the sub-GHz range for cm-sized transmit antenna. The multiple orders of magnitude increase in the operating frequency enables dramatic miniaturization of implantable devices.

Power feasibility of implantable digital spike-sorting circuits for neural prosthetic systems

A new class of neural prosthetic systems aims to assist disabled patients by translating cortical neural activity into control signals for prosthetic devices. Based on the success of proof-of-concept systems in the laboratory, there is now considerable interest in increasing system performance and creating implantable electronics for use in clinical systems. A critical question that impacts system performance and the overall architecture of these systems is whether it is possible to identify the neural source of each action potential (spike sorting) in real-time and with low power. Low power is essential both for power supply considerations and heat dissipation in the brain. In this paper we report that state-of-the-art spike sorting algorithms are not only feasible using modern complementary metal oxide semiconductor very large scale integration processes, but may represent the best option for extracting large amounts of data in implantable neural prosthetic interfaces.

A mm-sized implantable power receiver with adaptive link compensation

Wireless powering of implanted devices obviates the need for batteries, which must be periodically replaced and constitute a health risk. There has long been an assumption that efficient wireless transfer of power to biomedical implants requires fields operating in the low MHz in order to avoid excess losses in tissue, thus requiring antenna diameters of a few cm [1]. Such antennae increase device size and thereby restrict the range of viable applications. This work presents a wireless power transfer system that uses an antenna area 100× smaller than previous designs [2] while maintaining the same power transfer efficiency over the same range.

Signal Processing Challenges for Neural Prostheses

Cortically controlled prostheses are able to translate neural activity from the cerebral cortex into control signals for guiding computer cursors or prosthetic limbs. While both noninvasive and invasive electrode techniques can be used to measure neural activity, the latter promises considerably higher levels of performance and therefore functionality to patients. The process of translating analog voltages recorded at the electrode tip into control signals for the prosthesis requires sophisticated signal acquisition and processing techniques. In this article we briefly review the current state-of-the-art in invasive, electrode-based neural prosthetic systems, with particular attention to the advanced signal processing algorithms that enable that performance. Improving prosthetic performance is only part of the challenge, however. A clinically viable prosthetic system will need to be more robust and autonomous and, unlike existing approaches that depend on multiple computers and specialized recording units, must be implemented in a compact, implantable prosthetic processor (IPP). In this article we summarize recent results which indicate that state-of-the-art prosthetic systems can be implemented in an IPP using current semiconductor technology, and the challenges that face signal processing engineers in improving prosthetic performance, autonomy and robustness within the restrictive constraints of the IPP.

Optimal Operating Frequency in Wireless Power Transmission for Implantable Devices

This paper examines short-range wireless powering for implantable devices and shows that existing analysis techniques are not adequate to conclude the characteristics of power transfer efficiency over a wide frequency range. It shows, theoretically and experimentally, that the optimal frequency for power transmission in biological media can be in the GHz-range while existing solutions exclusively focus on the MHz-range. This implies that the size of the receive coil can be reduced by 104 times which enables the realization of fully integrated implantable devices.

Adaptive Resolution ADC Array for an Implantable Neural Sensor

This paper describes an analog-to-digital converter (ADC) array for an implantable neural sensor which digitizes neural signals sensed by a microelectrode array. The ADC array consists of 96 variable resolution ADC base cells. The resolution of each ADC cell in the array is varied according to neural data content of the signal from the corresponding electrode. The resolution adaptation algorithm is essentially to periodically recalibrate the required resolution and this is done without requiring any additional ADC cells. The adaptation implementation and results are described. The base ADC cell is implemented using a successive approximation charge redistribution architecture. The choice of architecture and circuit design are presented. The base ADC has been implemented in 0.13 μm CMOS as a 100 kS/s SAR ADC whose resolution can be varied from 3 to 8 bits with corresponding power consumption of 0.23 μW to 0.90 μW achieving an ENOB of 7.8 at the 8-bit setting. The energy per conversion step figure of merit is 48 fJ/step at the 8-bit setting. Resolution adaptation reduces power consumption by a factor of 2.3 for typical motor neuron signals while maintaining an effective 7.8-bit resolution across all channels.

Neurons to Silicon: Implantable Prosthesis Processor

A processor architecture for neural prosthesis control is described. It implements real-time neural decoding from a permanently implanted electrode array to reduce the data rate from 80Mb/s to 20b/s, minimizing the wireless communication requirements. The neural signals are digitized by a 100-channel 100kS/s adaptive-resolution ADC array consuming 1muW per channel

Adaptive resolution ADC array for neural implant

This paper describes an ADC array for an implantable prosthetic processor which digitizes neural signals sensed by a microelectrode array. The ADC array consists of 96 variable resolution ADC base cells. The base ADC has been implemented in 0.13μπι CMOS as a 100kS/s SAR ADC whose resolution can be varied from 3 to 8-bits with corresponding power consumption of 0.23μ\Υ to 0.90^W achieving an ENOB of 7.8 at the 8-bit setting. The resolution of each ADC cell in the array is varied according to neural data content of the signal from the corresponding electrode. Resolution adaptation reduces power consumption by a factor of 2.3 whilst maintaining an effective 7.8-bit resolution across all channels.

Implant Position Estimation Via Wireless Power Link

Wireless power transmission is widely used in implantable medical devices (IMDs). Surgical placement of IMDs has limited precision, and after implantation, the device can move over time. Accurate knowledge of the IMDs position enables better interpretation of data sensed by the device and may allow wireless power to be focused on the IMD, thereby increasing power transfer efficiency and enabling greater implant depth. Existing positioning methods require device sizes and/or power consumption that exceed the limits of in vivo millimeter-sized IMD applications. We have previously proposed a novel implant positioning scheme by sensing the backscattered electromagnetic (EM) field to overcome those disadvantages, which is hence considered ideal for power- and area-constrained IMDs and suitable for wearable devices. This paper briefly reviews the previously proposed localization scheme and reports the progress of this research. Specifically, different approaches to realize this scheme are discussed and compared. Localization experiments in free space are then demonstrated, and the accuracy is shown on the order of millimeters. Different on-chip implementation procedures of measuring the backscattered EM field and their tradeoffs are described. Finally, conclusions and the future plan are presented.

Adaptive signal acquisition and wireless power transfer for an implantable prosthesis processor

This paper describes an ADC array and wireless power transfer link for an implantable prosthetic processor which digitizes neural signals sensed by a microelectrode array. The ADC array consists of 96 variable resolution ADC base cells. The base ADC has been implemented in 0.13µm CMOS as a 100kS/s SAR ADC whose resolution can be varied from 3 to 8 — bits with corresponding power consumption of 0.23µW to 0.90µW. The resolution of each ADC cell is adapted according to neural data content of the signal from the corresponding electrode, this reduces power consumption by a factor of 2.3 whilst maintaining an effective 7.8 — bit resolution across all channels. A wireless power transfer system for implanted medical devices which uses antenna area 100 times smaller than previous designs has also been realized. Adaptive simultaneous conjugate matching and a high efficiency rectifier and regulator in 0.13µm CMOS together with a 4mm antenna deliver 140µW at 1.2V DC from a 4cm transmit antenna and a 0.25W 915MHz source through 15mm of tissue to power the implanted device.