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Conference paperLiu Y, Constandinou TG, Georgiou P, 2019,
A 32 x 32 ISFET array with in-pixel digitisation and column-wise TDC for ultra-fast chemical sensing
, IEEE International Symposium on Circuits and Systems (IEEE ISCAS), Publisher: IEEE, ISSN: 0271-4302This paper presents a 32×32 ISFET sensing array with in-pixel digitisation for pH sensing. The in-pixel digitisation is achieved using an inverter-based sensing pixel that is controlled by a triangular waveform. This converts the pH response of the ISFET into a time-domain signal whilst also increasing dynamic range and thus the ability to tolerate sensor offset. The pixels are interfaced to a 15-bit asynchronous column-wise time-to-digital converter (TDC), enabling fast sensor readout whilst using minimal silicon area. Parallel output of 32 TDC interfaces are serialised to achieve fast data though-put. This system is implemented in a standard 0.18 μm standard CMOS technology, with a pixel size of 26 μm × 26 μm and a TDC of 26 μm × 180 μm. Simulation results demonstrate that chemical sampling of up to 5k frames per second can be achieved with a clock frequency of 160 MHz and a TDC resolution of 190 ps. The total power consumption of the overall system is 7.34 mW.
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Conference paperCavuto ML, Constandinou TG, 2019,
Investigation of insertion method to achieve chronic recording stability of a semi-rigid implantable neural probe
, 9th IEEE/EMBS International Conference on Neural Engineering (NER), Publisher: IEEE, Pages: 665-669, ISSN: 1948-3546Brain machine interfaces notoriously face difficulties in achieving long term implanted recording stability. It has been shown that damage and inflammation, caused during insertion by electrodes that are too large and stiff, provoke a sustained inflammatory tissue response. This is commonly referred to as the foreign body response, resulting in encapsulation and thus increased electrode impedance over time. Accordingly, neural interfaces with ever smaller and more flexible electrodes are continually in development, but unfortunately face challenges of their own, first and foremost of which is buckling and bending during insertion. This work presents the development of a prototype insertion method, comprising an insertion device and novel probe architecture, that promotes straight insertion without buckling, while simultaneously minimizing the insertion force for multi-microwire electrode probes. When compared against insertion of probes with unsupported free electrodes, the prototype method achieved significantly straighter electrode insertion, resulting in both a smaller distance between electrode recording tips and a greater average insertion depth. While achieving less straight insertion than probes with sucrose coated electrodes, a common technique for promoting reliable insertion without buckling, the tested method was able to maintain significantly lower insertion forces.
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Conference paperAhmadi N, Cavuto ML, Feng P, et al., 2019,
Towards a distributed, chronically-implantable neural interface
, 9th IEEE/EMBS International Conference on Neural Engineering (NER), Publisher: IEEE, Pages: 719-724, ISSN: 1948-3546We present a platform technology encompassing a family of innovations that together aim to tackle key challenges with existing implantable brain machine interfaces. The ENGINI (Empowering Next Generation Implantable Neural Interfaces) platform utilizes a 3-tier network (external processor, cranial transponder, intracortical probes) to inductively couple power to, and communicate data from, a distributed array of freely-floating mm-scale probes. Novel features integrated into each probe include: (1) an array of niobium microwires for observing local field potentials (LFPs) along the cortical column; (2) ultra-low power instrumentation for signal acquisition and data reduction; (3) an autonomous, self-calibrating wireless transceiver for receiving power and transmitting data; and (4) a hermetically-sealed micropackage suitable for chronic use. We are additionally engineering a surgical tool, to facilitate manual and robot-assisted insertion, within a streamlined neurosurgical workflow. Ongoing work is focused on system integration and preclinical testing.
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Conference paperLeene LB, Constandinou TG, 2019,
A 3rd order time domain delta sigma modulator with extended-phase detection
, IEEE International Symposium on Circuits and Systems (IEEE ISCAS), Publisher: IEEE, ISSN: 0271-4302This paper presents a novel analogue to digital converter using an oscillator-based loop filter for high-dynamic range bio-sensing applications. This is the first third-order feedforward ΔΣ modulator that strictly uses time domain integration for quantisation noise shaping. Furthermore we propose a new asynchronous extended-phase detection technique that increases the resolution of the 4 bit phase quantiser by another 5 bits to significantly improve both dynamic range and reduce the noise-shaping requirements. Preliminary simulation results show that this type of loop-filter can virtually prevent integrator saturation and achieves a peak 88 dB SNDR for kHz signals. The proposed system has been implemented using a 180 nm CMOS technology occupying 0.102 mm 2 and consumes 13.7 μW of power to digitise the 15 kHz signal bandwidth using a 2 MHz sampling clock.
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Journal articleTroiani F, Nikolic K, Constandinou TG, 2019,
Correction: Simulating optical coherence tomography for observing nerve activity: a finite difference time domain bi-dimensional model
, PLoS ONE, Vol: 14, ISSN: 1932-6203[This corrects the article DOI: 10.1371/journal.pone.0200392.].
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Conference paperAhmadi N, Constandinou TG, Bouganis C-S, 2019,
Decoding Hand Kinematics from Local Field Potentials Using Long Short-Term Memory (LSTM) Network
, 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER 2019), Publisher: IEEE, Pages: 415-419Local field potential (LFP) has gained increasing interest as an alternativeinput signal for brain-machine interfaces (BMIs) due to its informativefeatures, long-term stability, and low frequency content. However, despitethese interesting properties, LFP-based BMIs have been reported to yield lowdecoding performances compared to spike-based BMIs. In this paper, we propose anew decoder based on long short-term memory (LSTM) network which aims toimprove the decoding performance of LFP-based BMIs. We compare offline decodingperformance of the proposed LSTM decoder to a commonly used Kalman filter (KF)decoder on hand kinematics prediction tasks from multichannel LFPs. We alsobenchmark the performance of LFP-driven LSTM decoder against KF decoder drivenby two types of spike signals: single-unit activity (SUA) and multi-unitactivity (MUA). Our results show that LFP-driven LSTM decoder achievessignificantly better decoding performance than LFP-, SUA-, and MUA-driven KFdecoders. This suggests that LFPs coupled with LSTM decoder could provide highdecoding performance, robust, and low power BMIs.
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Conference paperAhmadi N, Cavuto ML, Feng P, et al., 2019,
Towards a Distributed, Chronically-Implantable Neural Interface.
, Publisher: IEEE, Pages: 719-724 -
Conference paperMoly A, Luan S, Zoltan M, et al., 2018,
Embedded phase-amplitude coupling based closed-loop platform for Parkinson's Disease
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 527-530, ISSN: 2163-4025Deep Brain Stimulation (DBS) is a widely used clin-ical therapeutic modality to treat Parkinsons disease refractorysymptoms and complications of levodopa therapy. Currentlyavailable DBS systems use continuous, open-loop stimulationstrategies. It might be redundant and we could extend the batterylife otherwise. Recently, robust electrophysiological signaturesof Parkinsons disease have been characterized in motor cortexof patients undergoing DBS surgery. Reductions in the beta-gamma Phase-Amplitude coupling (PAC) correlated with symp-tom improvement, and the therapeutic effects of DBS itself. Weaim to develop a miniature, implantable and adaptive system,which only stimulates the neural target, when triggered by theoutput of the appropriate PAC algorithm. As a first step, in thispaper we compare published PAC algorithms by using humandata intra-operatively recorded from Parkinsonian patients. Wethen introduce IIR masking for later achieving fast and low-power FPGA implementation of PAC mapping for intra-operativestudies. Our closed-loop application is expected to consumesignificantly less power than current DBS systems, thereforewe can increase the battery life, without compromising clinicalbenefits.
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Conference paperDe Marcellis A, Di Patrizio Stanchieri G, Palange E, et al., 2018,
An ultra-wideband-inspired system-on-chip for an optical bidirectional transcutaneous biotelemetry
, IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 351-354This paper describes an integrated communicationsystem, implementing a UWB-inspired pulsed coding technique,for an optical transcutaneous biotelemetry. The system consistsof both a transmitter and a receiver facilitating a bidirectionallink. The transmitter includes a digital data coding circuit and iscapable of generating sub-nanosecond current pulses and directlydriving an off-chip semiconductor laser diode including all biasand drive circuits. The receiver includes an integrated compactPN-junction photodiode together with signal conditioning, de-tection and digital data decoding circuits to enable a high bitrate, energy efficient communication. The proposed solution hasbeen implemented in a commercially available 0.35μm CMOStechnology provided by AMS. The circuit core occupies a compactsilicon footprint of less than 0.13 mm2(only 113 transistors and1 resistor). Post-layout simulations have validated the overallsystem operation demonstrating the ability to operate at bit ratesup to 500 Mbps with pulse widths of 300 ps with a total powerefficiency (transmitter + receiver) lower than 74 pJ/bit. Thismakes the system ideally suited for demanding applications thatrequire high bit rates at extremely low energy levels. One suchapplication is implantable brain machine interfaces requiringhigh uplink bitrates to transmit recorded data externally througha transcutaneous communication channel.
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Conference paperMaslik M, Lande TS, Constandinou TG, 2018,
A clockless method of flicker noise suppression in continuous-time acquisition of biosignals
, IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 491-494This paper presents a novel chopping method allow-ing suppression of 1/f flicker noise in continuous-time acquisitionsystems without the need for a fixed-frequency clock, stochasti-cally deriving the chopping signal from the input and henceachieving completely signal-dependent power consumption. Themethod is analysed, its basis of operation explained and a proof-of-concept implementation presented alongside simulated resultsdemonstrating an increase in achieved SNR of more than 8 dBduring acquisition of ECG, EAP and EEG signals.
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Conference paperLeene L, Constandinou TG, 2018,
Direct digital wavelet synthesis for embedded biomedical microsystems
, IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 77-80This paper presents a compact direct digital waveletsynthesizer for extracting phase and amplitude data from corticalrecordings using a feed-forward recurrent digital oscillator.These measurements are essential for accurately decoding local-field-potentials in selected frequency bands. Current systemsextensively to rely large digital cores to efficiently performFourier or wavelet transforms which is not viable for manyimplants. The proposed system dynamically controls oscillation togenerate frequency selective quadrature wavelets instead of usingmemory intensive sinusoid/cordic look-up-tables while retainingrobust digital operation. A MachXO3LF Lattice FPGA is used topresent the results for a 16 bit implementation. This configurationrequires 401 registers combined with 283 logic elements andalso accommodates real-time reconfigurability to allow ultra-low-power sensors to perform spectroscopy with high-fidelity.
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Conference paperFeng P, Constandinou TG, 2018,
Robust wireless power transfer to multiple mm-scale freely-positioned Neural implants
, IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 363-366This paper presents a novel wireless power transfer(WPT) scheme that consists of a two-tier hierarchy of near-field inductively coupled links to provide efficient power transferefficiency (PTE) and uniform energy distribution for mm-scalefree-positioned neural implants. The top tier facilitates a tran-scutaneous link from a scalp-worn (cm-scale) primary coil toa subcutaneous array of smaller, parallel-connected secondarycoils. These are then wired through the skull to a correspondingset of parallel connected primary coils in the lower tier, placedepidurally. These then inductively couple to freely positioned(mm-scale) secondary coils within each subdural implant. Thisarchitecture has three key advantages: (1) the opportunity toachieve efficient energy transfer by utilising two short-distanceinductive links; (2) good uniformity of the transdural powerdistribution through the multiple (redundant) coils; and (3) areduced risk of infection by maintaining the dura protecting theblood-brain barrier. The functionality of this approach has beenverified and optimized through HFSS simulations, to demonstratethe robustness against positional and angular misalignment. Theaverage 11.9% PTE and 26.6% power distribution deviation(PDD) for horizontally positioned Rx coil and average 2.6% PTEand 62.8% power distribution deviation for the vertical Rx coilhave been achieved.
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Conference paperLauteslager T, Tommer M, Lande TS, et al., 2018,
Cross-body UWB radar sensing of arterial pulse propagation and ventricular Dynamics
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 165-168Single-chip UWB radar systems have enormous potential for the development of portable, low-cost and easy-to-use devices for monitoring the cardiovascular system. Using body coupled antennas, electromagnetic energy can be directed into the body to measure arterial pulsation and cardiac motion, and estimate arterial stiffness as well as blood pressure. In the current study we validate that heart rate signals, obtained using multiple UWB radar-on-chip modules and body coupled antennas, do indeed originate from arterial pulsation. Through ECG-aligned averaging, pulse arrival time at a number of locations in the body could be measured with high precision, and arterial pulse propagation through the femoral and carotid artery was demonstrated. In addition, cardiac dynamics were measured from the chest. Onset and offset of ventricular systole were clearly distinguishable, as well as onset of atrial systole. Although further validation is required, these results show that UWB radar-on-chip is highly suitable for monitoring of vascular health as well as the heart's mechanical functioning.
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Conference paperHaci D, Liu Y, Ghoreishizadeh S, et al., 2018,
Design considerations for ground referencing in multi-module neural implants
, IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 563-566Implantable neural interfaces have evolved in thepast decades from stimulation-only devices to closed-loop record-ing and stimulation systems, allowing both for more targetedtherapeutic techniques and more advanced prosthetic implants.Emerging applications require multi-module active implantabledevices with intrabody power and data transmission. Thisdistributed approach poses a new set of challenges relatedto inter-module connectivity, functional reliability and patientsafety. This paper addresses the ground referencing challenge inactive multi-implant systems, with a particular focus on neuralrecording devices. Three different grounding schemes (passive,drive, and sense) are presented and evaluated in terms of bothrecording reliability and patient safety. Considerations on thepractical implementation of body potential referencing circuitryare finally discussed, with a detailed analysis of their impact onthe recording performance.
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Conference paperHaci D, Liu Y, Nikolic K, et al., 2018,
Thermally controlled lab-on-PCB for biomedical applications
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 655-658This paper reports on the implementation andcharacterisation of a thermally controlled device forin vitrobiomedical applications, based on standard Printed Circuit Board(PCB) technology. This is proposed as a low cost alternativeto state-of-the-art microfluidic devices and Lab-on-Chip (LoC)platforms, which we refer to as the thermal Lab-on-PCB concept.In total, six different prototype boards have been manufacturedto implement as many mini-hotplate arrays. 3D multiphysicssoftware simulations show the thermal response of the modelledmini-hotplate boards to electrical current stimulation, highlight-ing their versatile heating capability. A comparison with theresults obtained by the characterisation of the fabricated PCBsdemonstrates the dual temperature sensing/heating property ofthe mini-hotplate, exploitable in a larger range of temperaturewith respect to the typical operating range of LoC devices. Thethermal system is controllable by means of external off-the-shelfcircuitry designed and implemented on a single-channel controlboard prototype.
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Conference paperMazza F, Liu Y, Donaldson N, et al., 2018,
Integrated devices for micro-package integrity monitoring in mm-scale neural implants
, IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 295-298Recent developments in the design of active im-plantable devices have achieved significant advances, for example,an increased number of recording channels, but too oftenpractical clinical applications are restricted by device longevity.It is important however to complement efforts for increased func-tionality with translational work to develop implant technologiesthat are safe and reliable to be hosted inside the human bodyover long periods of time. This paper first examines techniquescurrently used to evaluate micro-package hermeticity and keychallenges, highlighting the need for new,in situinstrumentationthat can monitor the encapsulation status over time. Two novelcircuits are then proposed to tackle the specific issue of moisturepenetration inside a sub-mm, silicon-based package. They bothshare the use of metal tracks on the different layers of the CMOSstack to measure changes in impedance caused by moisturepresent in leak cracks or diffused into the oxide layers.
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Journal articleAhmadi N, Constandinou T, Bouganis C, 2018,
Estimation of neuronal firing rate using Bayesian Adaptive Kernel Smoother (BAKS)
, PLoS ONE, Vol: 13, ISSN: 1932-6203Neurons use sequences of action potentials (spikes) to convey information across neuronal networks. In neurophysiology experiments, information about external stimuli or behavioral tasks has been frequently characterized in term of neuronal firing rate. The firing rate is conventionally estimated by averaging spiking responses across multiple similar experiments (or trials). However, there exist a number of applications in neuroscience research that require firing rate to be estimated on a single trial basis. Estimating firing rate from a single trial is a challenging problem and current state-of-the-art methods do not perform well. To address this issue, we develop a new method for estimating firing rate based on a kernel smoothing technique that considers the bandwidth as a random variable with prior distribution that is adaptively updated under an empirical Bayesian framework. By carefully selecting the prior distribution together with Gaussian kernel function, an analytical expression can be achieved for the kernel bandwidth. We refer to the proposed method as Bayesian Adaptive Kernel Smoother (BAKS). We evaluate the performance of BAKS using synthetic spike train data generated by biologically plausible models: inhomogeneous Gamma (IG) and inhomogeneous inverse Gaussian (IIG). We also apply BAKS to real spike train data from non-human primate (NHP) motor and visual cortex. We benchmark the proposed method against established and previously reported methods. These include: optimized kernel smoother (OKS), variable kernel smoother (VKS), local polynomial fit (Locfit), and Bayesian adaptive regression splines (BARS). Results using both synthetic and real data demonstrate that the proposed method achieves better performance compared to competing methods. This suggests that the proposed method could be useful for understanding the encoding mechanism of neurons in cognitive-related tasks. The proposed method could also potentially improve the performance of brain-mac
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Conference paperSzostak KM, Constandinou TG, 2018,
Hermetic packaging for implantable microsystems: effectiveness of sequentially electroplated AuSn alloy
, 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEEWith modern microtechnology, there is an aggressive miniaturization of smart devices, despite an increasing level of integration and overall complexity. It is therefore becoming increasingly important to be achieve reliable, compact packaging. For implantable medical devices (IMDs), the package must additionally provide a high quality hermetic environmentto protect the device from the human body. For chip-scale devices, AuSn eutectic bonding offers the possibility of forming compact seals that achieve ultra-low permeability. A key feature is this can be achieved at process temperatures of below 350 C, therefore allowing for the integration of sensors and microsystems with CMOS electronics within a single package. Issueshowever such as solder wetting, void formation and controlling composition make formation of high-quality repeatable seals highly challenging. Towards this aim, this paper presents our experimental work characterizing the eutectic stack deposition. We detail our design methods and process flow, share our experiences in controlling electrochemical deposition of AuSnalloy and finally discuss usability of sequential electroplating process for the formation of hermetic eutectic bonds.
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Conference paperAhmadi N, Constandinou TG, Bouganis C, 2018,
Spike rate estimation using Bayesian Adaptive Kernel Smoother (BAKS) and its application to brain machine interfaces
, 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEEBrain Machine Interfaces (BMIs) mostly utilise spike rate as an input feature for decoding a desired motor output as it conveys a useful measure to the underlying neuronal activity. The spike rate is typically estimated by a using non-overlap binning method that yields a coarse estimate. There exist several methods that can produce a smooth estimate which could potentially improve the decoding performance. However, these methods are relatively computationally heavy for real-time BMIs. To address this issue, we propose a new method for estimating spike rate that is able to yield a smooth estimate and also amenable to real-time BMIs. The proposed method, referred to as Bayesian adaptive kernel smoother (BAKS), employs kernel smoothing technique that considers the bandwidth as a random variable with prior distribution which is adaptively updated through a Bayesian framework. With appropriate selection of prior distribution and kernel function, an analytical expression can be achieved for the kernel bandwidth. We apply BAKS and evaluate its impact on of fline BMI decoding performance using Kalman filter. The results show that overlap BAKS improved the decoding performance up to 3.33% and 12.93% compared to overlap and non-overlapbinning methods, respectively, depending on the window size. This suggests the feasibility and the potential use of BAKS method for real-time BMIs.
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Conference paperRapeaux A, Brunton E, Nazarpour K, et al., 2018,
Preliminary study of time to recovery of rat sciatic nerve from high frequency alternating current nerve block
, 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEEHigh-Frequency alternating current nerve block has great potential for neuromodulation-based therapies. However, no precise measurements have been made of the time needed for nerves to recover from block once the signal has been turned off. This study aims to characterise time to recoveryof the rat sciatic nerve after 30 seconds of block at varying amplitudes and frequencies. Experiments were carried out in-vivo to quantify recovery times and recovery completeness within 0.7s from the end of block. The sciatic nerve was blocked with an alternating square wave signal of amplitudeand frequency ranging from 2 to 9mA and 10 to 50 kHz respectively. To determine the recovery dynamics the nerve was stimulated at 100 Hz after cessation of the blocking stimulus. Electromyogram signals were measured from the gastrocnemius medialis and tibialis anterior muscles during trials as indicators of nerve function. This allowed for nerve recovery to bemeasured with a resolution of 10 ms. This resolution is much greater than previous measurements of nerve recovery in the literature. Times for the nerve to recover to a steady state of activity ranged from 20 to 430 milliseconds and final relative recovery activity at 0.7 seconds spanned 0.2 to 1 approximately. Higher blocking signal amplitudes increased recovery time and decreased recovery completeness. These results suggestthat blocking signal properties affect nerve recovery dynamics, which could help improve neuromodulation therapies and allow more precise comparison of results across studies using different blocking signal parameters.
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