Remotely Powered Wireless Cortical Implants for Brain-Machine Interfaces

Brain-machine interfaces hold promise for restoring basic functions such as movement or speech for severely disabled patients, as well as for controlling neuroprosthetic devices for amputees. One of the major challenges of clinically viable neuroprostheses for chronic use is the implementation of fully implantable recording devices for stable, long-term recordings over large populations of neurons. Recent progress in the microelectronics and MEMS technologies has enabled miniaturization of microelectrode arrays which can be used for recording the neural activity of the brain and for stimulating the neurons. Nevertheless, the demanding requirements of fully implantable recording devices necessitate the incorporation of other active components with the microelectrodes. The presence of the active components in the implant requires power to be delivered to the device. Transcutaneous wires are commonly used for this purpose as well as for communication with the outside world. However, these wires pose the risk of infection to the patient. Another common method of powering is to utilize batteries in the implant. Nevertheless, this method is not desirable as the batteries have to be replaced at the end of their lifetime with a surgical procedure. This thesis presents the development of a remotely powered wireless cortical neural interface system for brain-machine interface applications. In the scope of this work, firstly, the requirements and specifications of the system are analyzed to examine the limits of operation. In addition, the thermal impact of cortical implant operation in the head is investigated to determine the maximum allowable power consumption in the implant. In order to supply power to the active components in the cortical implant, a closed-loop inductive remote powering link operating from a single external battery is implemented. The closed-loop operation enables adaptive delivery of power depending on the implant activity. For improving the power efficiency of the link, a discrete optimization algorithm is developed to design the geometry of the power transmission coils. In addition, application specific integrated circuits are designed to enhance the overall performance of the system and to decrease the footprint of the implant electronics. Moreover, wireless data communication for cortical implants is discussed and a solution for coexistence of the power and data links is presented. For implanting the cortical recording device into the body, a two-body packaging topology is proposed to position the implant inside the cranial bone. With this topology, the performance of the cortical neural interface is significantly improved. The fabricated cortical implants with the two-body package are characterized in air and in vitro. The power transfer efficiency of the closed-loop remote powering link operating from a single supply is measured to be 10.6% in vitro for 10 mW power delivered to the implant load. Finally, the operation of the implant in vitro is validated for over five weeks.

Electronic dura mater soft, multimodal neural interfaces

Arthur Edouard Hirsch

Neuroprosthetic devices are engineered to study, support or replace impaired functions of the nervous system. The neural interface is an essential element of neuroprosthetic systems as it allows for transduction of signals and stimuli of desired functions (recording, stimulation, neuromodulation). A persistent challenge for translating neuroprosthetics from the laboratory to the clinic is the lack of long-term biointegration of neural interfaces. This thesis aims at improving biointegration of neural interfaces by reducing the mechanical mismatch between implant and neural tissue. In this thesis, the design, fabrication and characterization of soft surface neural interfaces is described. These soft neural interfaces, termed electronic dura mater or e-dura, were designed to mimic the mechanical properties of dura mater. In contrast with conventional neural technologies, e-dura neural interfaces were made of soft and compliant materials. They conform to the circumvolutions of the brain and spinal cord and follow their dynamic deformation without damaging the surrounding neural tissues. These soft multimodal neural interfaces were fabricated on silicone substrates using techniques imported from the microfabrication industry and incorporate compliant electrodes, stretchable electrical interconnects and a micro-catheter for drug delivery. Evaluation of the e-dura biointegration with spinal tissues demonstrated reduced foreign body reaction, compared to stiff polyimide based implants. Additionally, mechanical tests on an in-vitro spinal surrogate provided insights on the complex biomechanical coupling between implants and neural tissue. E-dura interfaces, implanted in rodents, maintained their functionality over extended periods and provided high-resolution neuronal recordings and concurrent delivery of electrical and chemical neuromodulation. Eventually, the use of gallium thin films was explored to create highly conductive and stretchable interconnects for integration of active electronic components in e-dura neural interfaces.

EPFL2018

Inductive Power Link for a Wireless Cortical Implant with Biocompatible Packaging

Michel Declercq, Catherine Dehollain, Kanber Mithat Silay

This article presents an inductive power link for a cortical implant. The link includes a Class-E power amplifier, an inductive link, a matching network, and a rectifier. The coils of the inductive link are designed and optimized for a distance of 10mm (scalp thickness). The power amplifier is designed in order to allow closed loop power control by controlling the supply voltage. A new packaging topology is proposed in order to position the implant in the skull, without occupying much area, but still obtaining short distance between the remote powering coils. The package is fabricated using biocompatible materials such as PDMS and Parylene-C, and it includes the secondary coil, the matching network, and the rectifier. The power efficiency of the link is characterized for a wide range of load power (1-20mW) and found to be 8.1% for nominal load of 10mW. The matching network improves the power efficiency on the whole range, compared to the link without the matching network.

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Low-Power Circuit and System Design for Epileptic Seizure Detection at High Spatiotemporal Resolution

Mahsa Shoaran

Smart and miniaturized implantable microsystems with diagnostic and therapeutic capabilities are becoming increasingly important for patients suffering from neurological disorders such as epilepsy. Recent developments in microfabrication technology have provided new insights into seizure generation at an unprecedented spatial scale. Based on these findings, designing powerful acquisition systems capable of probing the wide-range spatiotemporal activities within the brain holds a great promise to improve the quality of life of epileptic patients. It is expected that future neural recording interfaces will integrate hundreds of acquisition channels at relatively high sampling rates, making it crucial to perform sophisticated signal conditioning tasks within the sensors. A small size of the implantable system is critical to minimize potential clinical issues associated with implantation. The total power consumption should be minimized to avoid heat generation inside the brain. Substantial improvements in neural implant safety and longevity are needed to translate existing multisite neural recording systems into technology suitable for long-term use in patients. As a major technological barrier, the high overall data rates of digitized neural signals collected by dense electrode arrays can drastically increase the power consumption of the wireless transmission module. Consequently, extensive system-level design improvement is needed to meet the requirements of the implantable device, while preserving the high-resolution monitoring capability. In this context, we target the exploration and development of novel methods and tools for more accurate monitoring of the electrical activity of the epileptic brain during seizures. A precise focus localization and accurate early seizure detection are two major goals. Low-power circuit and system design techniques for data acquisition, compression and seizure detection in multichannel cortical implants are presented. In this context, the first fully-integrated circuit that addresses the multichannel compressed-domain feature extraction is proposed. Circuit challenges and techniques to optimize the neural amplifier topology at the frontend of the signal acquisition chain, in terms of power consumption, die area and noise are discussed. Then, compressive sensing is utilized as the main data reduction method in the proposed system. The existing microelectronic implementations of compressive sensing are applied in a single-channel basis. Therefore, these topologies incur a high power consumption and large silicon area. To overcome these issues, a new multichannel measurement scheme and an appropriate recovery scheme are proposed, which encode the whole array into a single compressed data stream. This technique circumvents the need to place one analog-to-digital converter inside each channel, which results in a significant area saving. Taking benefit of the area-efficient implementation of compressive sensing, the number of recording units implantable on the cortex which satisfy the energy constraints of the system is scaled up by a factor equal to the compression ratio. Finally, a new feature extraction method applied on the compressed signal of several channels is proposed. The spatial evolution of the intracranial EEG signals recorded by the adjacent electrodes and the corresponding behaviour in the compressed domain are exploited for detecting seizure onset.