Miniaturised Wireless Power Transfer Systems for Neurostimulation: A Review

In neurostimulation, wireless power transfer is an efficient technology to overcome several limitations affecting medical devices currently used in clinical practice. Several methods were developed over the years for wireless power transfer. In this review article, we report and discuss the three most relevant methodologies for extremely miniaturised implantable neurostimulator: ultrasound coupling, inductive coupling and capacitive coupling. For each powering method, the discussion starts describing the physical working principle. In particular, we focus on the challenges given by the miniaturisation of the implanted integrated circuits and the related ad-hoc solutions for wireless power transfer. Then, we present recent developments and progresses in wireless power transfer for biomedical applications. Last, we compare each technique based on key performance indicators to highlight the most relevant and innovative solutions suitable for neurostimulation, with the gaze turned towards miniaturisation

An integrated bidirectional multi-channel opto-electro arbitrary waveform stimulator for treating motor neurone disease

This paper presents a prototype integrated bidirectional stimulator ASIC capable of mixed opto-electro stimulation and electrophysiological signal recording. The development is part of the research into a fully implantable device for treating motor neurone disease using optogenetics and stem cell technology. The ASIC consists of 4 stimulator units, each featuring 16-channel optical and electrical stimulation using arbitrary current waveforms with an amplitude up to 16 mA and a frequency from 1.5 Hz to 50 kHz, and a recording front-end with a programmable bandwidth of 1 Hz to 4 kHz, and a programmable amplifier gain up to 74 dB. The ASIC was implemented in a 0.18μm CMOS technology. Simulated performance in stimulation and recording is presented

Bidirectional Neural Interface Circuits with On-Chip Stimulation Artifact Reduction Schemes

Bidirectional neural interfaces are tools designed to “communicate” with the brain via recording and modulation of neuronal activity. The bidirectional interface systems have been adopted for many applications. Neuroscientists employ them to map neuronal circuits through precise stimulation and recording. Medical doctors deploy them as adaptable medical devices which control therapeutic stimulation parameters based on monitoring real-time neural activity. Brain-machine-interface (BMI) researchers use neural interfaces to bypass the nervous system and directly control neuroprosthetics or brain-computer-interface (BCI) spellers. In bidirectional interfaces, the implantable transducers as well as the corresponding electronic circuits and systems face several challenges. A high channel count, low power consumption, and reduced system size are desirable for potential chronic deployment and wider applicability. Moreover, a neural interface designed for robust closed-loop operation requires the mitigation of stimulation artifacts which corrupt the recorded signals. This dissertation introduces several techniques targeting low power consumption, small size, and reduction of stimulation artifacts. These techniques are implemented for extracellular electrophysiological recording and two stimulation modalities: direct current stimulation for closed-loop control of seizure detection/quench and optical stimulation for optogenetic studies. While the two modalities differ in their mechanisms, hardware implementation, and applications, they share many crucial system-level challenges. The first method aims at solving the critical issue of stimulation artifacts saturating the preamplifier in the recording front-end. To prevent saturation, a novel mixed-signal stimulation artifact cancellation circuit is devised to subtract the artifact before amplification and maintain the standard input range of a power-hungry preamplifier. Additional novel techniques have been also implemented to lower the noise and power consumption. A common average referencing (CAR) front-end circuit eliminates the cross-channel common mode noise by averaging and subtracting it in analog domain. A range-adapting SAR ADC saves additional power by eliminating unnecessary conversion cycles when the input signal is small. Measurements of an integrated circuit (IC) prototype demonstrate the attenuation of stimulation artifacts by up to 42 dB and cross-channel noise suppression by up to 39.8 dB. The power consumption per channel is maintained at 330 nW, while the area per channel is only 0.17 mm2. The second system implements a compact headstage for closed-loop optogenetic stimulation and electrophysiological recording. This design targets a miniaturized form factor, high channel count, and high-precision stimulation control suitable for rodent in-vivo optogenetic studies. Monolithically integrated optoelectrodes (which include 12 µLEDs for optical stimulation and 12 electrical recording sites) are combined with an off-the-shelf recording IC and a custom-designed high-precision LED driver. 32 recording and 12 stimulation channels can be individually accessed and controlled on a small headstage with dimensions of 2.16 x 2.38 x 0.35 cm and mass of 1.9 g. A third system prototype improves the optogenetic headstage prototype by furthering system integration and improving power efficiency facilitating wireless operation. The custom application-specific integrated circuit (ASIC) combines recording and stimulation channels with a power management unit, allowing the system to be powered by an ultra-light Li-ion battery. Additionally, the µLED drivers include a high-resolution arbitrary waveform generation mode for shaping of µLED current pulses to preemptively reduce artifacts. A prototype IC occupies 7.66 mm2, consumes 3.04 mW under typical operating conditions, and the optical pulse shaping scheme can attenuate stimulation artifacts by up to 3x with a Gaussian-rise pulse rise time under 1 ms.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147674/1/mendrela_1.pd

Design, Fabrication, and Validation of a Highly Miniaturized Wirelessly Powered Neural Implant

We have recently witnessed an explosion in the number of neurons that can be recorded and/or stimulated simultaneously during neurophysiological experiments. Experiments have progressed from recording or stimulation with a single electrode to Micro-Electrode Array (MEA) such as the Utah Array. These MEAs can be instrumented with current drivers, neural amplifiers, digitizers and wireless communication links. The broad interest in these MEAs suggests that there is a need for large scale neural recording and stimulation. The ultimate goal is to coordinate the recordings and stimulation of potentially thousands of neurons from many brain areas. Unfortunately, current state-of-the-art MEAs are limited by their scalability and long-term stability because of their physical size and rigid configuration. Furthermore, some applications prioritize a distributed neural interface over one that offers high resolution. Examples of biomedical applications that necessitate an interface with neurons from many sites in the brain include: i) understanding and treating neurological disorders that affect distributed locations throughout the CNS; ii) revolutionizing our understanding of the brain by studying the correlations between neural networks from different regions of the brain and the mechanisms of cognitive functions; and iii) covering larger area in the sensorimotor cortex of amputees to more accurately control robotic prosthetic limbs or better evoke a sense of touch. One solution to make large scale, fully specifiable, electrical stimulation and recording possible, is to disconnect the electrodes from the base, so that they can be arbitrarily placed, using a syringe, freely in the nervous system. To overcome the challenges of system miniaturization, we propose the “microbead”, an ultra-small neural stimulating implant, that is currently implemented in a 130nm CMOS technology with the following characteristics: 200 μm × 200 μm × 80 μm size; optimized wireless powering, all micro-electronics on single chip; and integrated electrodes and coil. The stimulating microbead is validated in a sciatic nerve by generating leg movements. A recording microbead is also investigated with following characteristics: wireless powering using steerable phased coil array, miniaturized front-end, and backscattering telemetry. These microbeads could eventually replace the rigid arrays that are currently the state-of-the-art in electrophysiology set-ups

Energy-Efficient Circuit Designs for Miniaturized Internet of Things and Wireless Neural Recording

Internet of Things (IoT) have become omnipresent over various territories including healthcare, smart building, agriculture, and environmental and industrial monitoring. Today, IoT are getting miniaturized, but at the same time, they are becoming more intelligent along with the explosive growth of machine learning. Not only do IoT sense and collect data and communicate, but they also edge-compute and extract useful information within the small form factor. A main challenge of such miniaturized and intelligent IoT is to operate continuously for long lifetime within its low battery capacity. Energy efficiency of circuits and systems is key to addressing this challenge. This dissertation presents two different energy-efficient circuit designs: a 224pW 260ppm/°C gate-leakage-based timer for wireless sensor nodes (WSNs) for the IoT and an energy-efficient all analog machine learning accelerator with 1.2 µJ/inference of energy consumption for the CIFAR-10 and SVHN datasets. Wireless neural interface is another area that demands miniaturized and energy-efficient circuits and systems for safe long-term monitoring of brain activity. Historically, implantable systems have used wires for data communication and power, increasing risks of tissue damage. Therefore, it has been a long-standing goal to distribute sub-mm-scale true floating and wireless implants throughout the brain and to record single-neuron-level activities. This dissertation presents a 0.19×0.17mm2 0.74µW wireless neural recording IC with near-infrared (NIR) power and data telemetry and a 0.19×0.28mm2 0.57µW light tolerant wireless neural recording IC.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169712/1/jongyup_1.pd

Implantable Neural Probes for Electrical Recording and Optical Stimulation of Cellular Level Neural Circuitry in Behaving Animals.

In order to advance the understanding of brain function, it is critical to monitor how neural circuits work together and perform computational processing. For the past few decades, a wide variety of neural probes have been developed to study the electrophysiology of the brain. This work is focused on two important objectives to improve the brain-computer interface: 1) to enhance the reliability of recording electrodes by optimizing the shank structure; 2) to incorporate optical stimulation capability in addition to electrical recording for applications involving optogenetics. For the first objective, a flexible 64-channel parylene probe was designed with unique geometries for reduced tissue reactions. In order to provide the mechanical stiffness necessary to penetrate the brain, the miniaturized, flexible probes were coated with a lithographically patterned silk fibroin, which served as a biodegradable insertion shuttle. Because the penetration strength is independent from the properties of the probe itself, the material and geometry of the probe structure can be optimally designed without constraints. These probes were successfully implanted into the layer-V of motor cortex in 6 rats and recorded neural activities in vivo for 6 weeks. For the second objective, either optical waveguides or μLEDs were monolithically integrated on the probe shanks for optogenetic applications. Compared to existing methods, this work can offer high spatial-temporal resolution to record and stimulate from even subcellular neural structures. In the experiments using wild type animals, despite optimized recording of spontaneous neural activities, the cells never responded to illumination. In contrast, for the ChR2 expressed animals, light activation of neural activities was extremely robust and local, which phase-locked to the light waveform whenever the cell was close to the light source. In particular, the probes integrated with μLEDs were capable of driving different neural circuit behaviors using two adjacent μLEDs separated only by a 60-μm-pitch. With 3 μLEDs integrated at the tip of each of the 4 probe shanks, this novel optogenetic probe can provide more than 480 million (12!) different spiking sequences at the sub-cellular resolution, which is ideal to manipulate high density neural network with versatility and precision.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111604/1/wufan_1.pd

Photovoltaic Energy Harvesting for Millimeter-Scale Systems

The Internet of Things (IoT) based on mm-scale sensors is a transformational technology that opens up new capabilities for biomedical devices, surveillance, micro-robots and industrial monitoring. Energy harvesting approaches to power IoT have traditionally included thermal, vibration and radio frequency. However, the achievement of efficient energy scavenging for IoT at the mm-scale or sub mm-scale has been elusive. In this work, I show that photovoltaic (PV) cells at the mm-scale can be an alternative means of wireless power transfer to mm-scale sensors for IoT, utilizing ambient indoor lighting or intentional irradiation of near-infrared (NIR) LED sources through biological tissue. Single silicon and GaAs photovoltaic cells at the mm-scale can achieve a power conversion efficiency of more than 17 % for silicon and 30 % for GaAs under low-flux NIR irradiation at 850 nm through the optimized device structure and sidewall/surface passivation studies, which guarantees perpetual operation of mm-scale sensors. Furthermore, monolithic single-junction GaAs photovoltaic modules offer a means for series-interconnected cells to provide sufficient voltage (> 5 V) for direct battery charging, and bypassing needs for voltage up-conversion circuitry. However, there is a continuing challenge to miniaturize such PV systems down to the sub mm-scale with minimal optical losses from device isolation and metal interconnects and efficient voltage up-conversion. Vertically stacked dual-junction PV cells and modules are demonstrated to increase the output voltage per cell and minimize area losses for direct powering of miniature devices for IoT and bio-implantable applications with low-irradiance narrowband spectral illumination. Dual-junction PV cells at small dimensions (150 µm x 150 µm) demonstrate power conversion efficiency greater than 22 % with more than 1.2 V output voltage under low-flux 850 nm NIR LED illumination, which is sufficient for batteryless operation of miniaturized CMOS IC chips. The output voltage of dual-junction PV modules with eight series-connected single cells is greater than 10 V while maintaining an efficiency of more than 18 %. Finally, I demonstrate monolithic PV/LED modules at the µm-scale for brain-machine interfaces, enabling two-way optical power and data transfer in a through-tissue configuration. The wafer-level assembly plan for the 3D vertical integration of three different systems including GaAs LED/PV modules, CMOS silicon chips, and neural probes is proposed.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163261/1/esmoon_1.pd

Wireless tools for neuromodulation

Epilepsy is a spectrum of diseases characterized by recurrent seizures. It is estimated that 50 million individuals worldwide are affected and 30% of cases are medically refractory or drug resistant. Vagus nerve stimulation (VNS) and deep brain stimulation (DBS) are the only FDA approved device based therapies. Neither therapy offers complete seizure freedom in a majority of users. Novel methodologies are needed to better understand mechanisms and chronic nature of epilepsy. Most tools for neuromodulation in rodents are tethered. The few wireless devices use batteries or are inductively powered. The tether restricts movement, limits behavioral tests, and increases the risk of infection. Batteries are large and heavy with a limited lifetime. Inductive powering suffers from rapid efficiency drops due to alignment mismatches and increased distances. Miniature wireless tools that offer behavioral freedom, data acquisition, and stimulation are needed. This dissertation presents a platform of electrical, optical and radiofrequency (RF) technologies for device based neuromodulation. The platform can be configured with features including: two channels differential recording, one channel electrical stimulation, and one channel optical stimulation. Typical device operation consumes less than 4 mW. The analog front end has a bandwidth of 0.7 Hz - 1 kHz and a gain of 60 dB, and the constant current driver provides biphasic electrical stimulation. For use with optogenetics, the deep brain optical stimulation module provides 27 mW/mm2 of blue light (473 nm) with 21.01 mA. Pairing of stimulating and recording technologies allows closed-loop operation. A wireless powering cage is designed using the resonantly coupled filter energy transfer (RCFET) methodology. RF energy is coupled through magnetic resonance. The cage has a PTE ranging from 1.8-6.28% for a volume of 11 x 11 x 11 in3. This is sufficient to chronically house subjects. The technologies are validated through various in vivo preparations. The tools are designed to study epilepsy, SUDEP, and urinary incontinence but can be configured for other studies. The broad application of these technologies can enable the scientific community to better study chronic diseases and closed-loop therapies