Publications

Conference paper

Cavallo FR, Mirza KB, Toumazou C, 2018,

Links Between DNA-Based Diet and Salivary Leptin Hormone Concentration

, IEEE Biomedical Circuits and Systems Conference (BioCAS) - Advanced Systems for Enhancing Human Health, Publisher: IEEE, Pages: 547-550, ISSN: 2163-4025

Conference paper

Haci D, Liu Y, Nikolic K, Demarchi D, Constandinou TG, Georgiou Pet al., 2018,

Thermally controlled lab-on-PCB for biomedical applications

, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 655-658

This 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.

Conference paper

Maslik 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: 491-494

This 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.

Conference paper

Mazza F, Liu Y, Donaldson N, Constandinou TGet 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: 295-298

Recent 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.

Conference paper

De Marcellis A, Di Patrizio Stanchieri G, Palange E, Faccio M, Constandinou TGet 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: 351-354

This 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.

Conference paper

Haci D, Liu Y, Ghoreishizadeh S, Constandinou TGet al., 2018,

Design considerations for ground referencing in multi-module neural implants

, IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 563-566

Implantable 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.

Conference paper

Moly A, Luan S, Zoltan M, Salimpour Y, Anderson W, Constandinou TG, Grand Let 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: 2163-4025

Deep 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.

Conference paper

Feng 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: 363-366

This 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.

Conference paper

Leene L, Constandinou TG, 2018,

Direct digital wavelet synthesis for embedded biomedical microsystems

, IEEE Biomedical Circuits and Systems (BioCAS) Conference 2018, Publisher: IEEE, Pages: 77-80

This 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.

Journal article

Ahmadi N, Constandinou T, Bouganis C, 2018,

Estimation of neuronal firing rate using Bayesian Adaptive Kernel Smoother (BAKS)

, PLoS ONE, Vol: 13, ISSN: 1932-6203

Neurons 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

Conference paper

Szostak 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: IEEE

With 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.

Conference paper

Ahmadi 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: IEEE

Brain 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.

Conference paper

Rapeaux A, Brunton E, Nazarpour K, Constandinou TGet 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: IEEE

High-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.

Journal article

Khwaja M, Kalofonou M, Toumazou C, 2018,

A Deep Autoencoder System for Differentiation of Cancer Types Based on DNA Methylation State

, arXiv preprint arXiv:1810.01243

Journal article

Feng P, Yeon P, Cheng Y, Ghovanloo M, Constandinou TGet al., 2018,

Chip-scale coils for millimeter-sized bio-implants

, IEEE Transactions on Biomedical Circuits and Systems, Vol: 12, Pages: 1088-1099, ISSN: 1932-4545

Next generation implantable neural interfaces are targeting devices with mm-scale form factors that are freely floating and completely wireless. Scalability to more recording (or stimulation) channels will be achieved through distributing multiple devices, instead of the current approach that uses a single centralized implant wired to individual electrodes or arrays. In this way, challenges associated with tethers, micromotion and reliability of wiring is mitigated. This concept is now being applied to both central and peripheral nervous system interfaces. One key requirement, however, is to maximize SAR-constrained achievable wireless power transfer efficiency (PTE) of these inductive links with mm-sized receivers. Chip-scale coil structures for microsystem integration that can provide efficient near-field coupling are investigated. We develop near-optimal geometries for three specific coil structures: “in-CMOS”, “above-CMOS” (planar coil post-fabricated on a substrate) and “around-CMOS” (helical wirewound coil around substrate). We develop analytical and simulation models that have been validated in air and biological tissues by fabrications and experimentally measurements. Specifically, we prototype structures that are constrained to a 4mm x 4mm silicon substrate i.e. the planar in-/above-CMOS coils have outer diameter <4mm, whereas the around-CMOS coil has inner diameter of 4mm. The in-CMOS and above-CMOS coils have metal film thicknesses of 3μm aluminium and 25μm gold, respectively, whereas the around-CMOS coil is fabricated by winding a 25μm gold bonding-wire around the substrate. The measured quality factors (Q) of the mm-scale Rx coils are 10.5 @450.3MHz (in-CMOS), 24.61 @85MHz (above-CMOS), and 26.23 @283MHz (around-CMOS). Also, PTE of 2-coil links based on three types of chip-scale coils is measured in air and tissue environment to demonstrate tissue loss for bio-implants. The SAR-constrained maximum PTE are

Journal article

Ma D, Rodriguez-Manzano J, Lopez SDM, Kalofonou M, Georgiou P, Toumazou Cet al., 2018,

Adapting ISFETs for Epigenetics: An Overview

, IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, Vol: 12, Pages: 1186-1201, ISSN: 1932-4545

Journal article

Leene L, Constandinou TG, 2018,

A 0.006mm² 1.2μW analogue-to-time converter for asynchronous bio-sensors

, IEEE Journal of Solid-State Circuits, Vol: 53, Pages: 2604-2613, ISSN: 0018-9200

This work presents a low-power analogue-to-time converter (ATC) for integrated bio-sensors. The proposed circuit facilitates the direct conversion of electrode biopotential recordings into time-encoded digital pulses with high efficiency without prior signal amplification. This approach reduces the circuit complexity for multi-channel instrumentation systems and allows asynchronous digital control to maximise the potential powersavings during sensor inactivity. A prototype fabricated using a 65nm CMOS technology is demonstrated with measured characteristics. Experimental results show an input-referred noise figure of 3.8μ Vrms for a 11kHz signal bandwidth while dissipating 1.2μ W from a 0.5V supply and occupying 60 ×80μ m² silicon area. This compact configuration is enabled by the proposed asynchronous readout that shapes the mismatch componentsarising from the multi-bit quantiser and the use of capacitive feedback.

Patent

Ghoreishizadeh S, Constandinou TG, 2018,

On-chip Random ID Generation

Conference paper

Hernandez B, Herrero P, Rawson TM, Moore LSP, Toumazou C, Holmes AH, Georgiou Pet al., 2018,

Enhancing antimicrobial surveillance: an automated, dynamic and interactive approach

, 18th International Congress on Infectious Disease, Publisher: Elsevier, Pages: 122-122, ISSN: 1201-9712

Journal article

Luan S, Williams I, Maslik M, Liu Y, De Carvalho F, Jackson A, Quian Quiroga R, Constandinou Tet al., 2018,

Compact standalone platform for neural recording with real-time spike sorting and data logging

, Journal of Neural Engineering, Vol: 15, Pages: 1-13, ISSN: 1741-2552

Objective. Longitudinal observation of single unit neural activity from largenumbers of cortical neurons in awake and mobile animals is often a vital step in studying neural network behaviour and towards the prospect of building effective Brain Machine Interfaces (BMIs). These recordings generate enormous amounts of data for transmission & storage, and typically require o ine processing to tease out the behaviour of individual neurons. Our aim was to create a compact system capable of: 1) reducing the data bandwidth by circa 2 to 3 orders of magnitude (greatly improving battery lifetime and enabling low power wireless transmission in future versions); 2) producing real-time, low-latency, spike sorted data; and 3) long term untethered operation. Approach. We have developed a headstage that operates in two phases. In the short training phase a computer is attached and classic spike sorting is performed to generate templates. In the second phase the system is untethered and performs template matching to create an event driven spike output that is logged to a micro-SD card. To enable validation the system is capable of logging the high bandwidth raw neural signal data as well as the spike sorted data. Main results. The system can successfully record 32 channels of raw neural signal data and/or spike sorted events for well over 24 hours at a time and is robust to power dropouts during battery changes as well as SD card replacement. A 24-hour initial recording in a nonhuman primate M1 showed consistent spike shapes with the expected changes in neural activity during awake behaviour and sleep cycles. Signi cance The presented platform allows neural activity to be unobtrusively monitored and processed in real-time in freely behaving untethered animals { revealing insights that are not attainable through scheduled recording sessions. This system achieves the lowest power per channel to date and provides a robust, low-latency, low-bandwidth and veri able output suitable f

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Links Between DNA-Based Diet and Salivary Leptin Hormone Concentration

A Deep Autoencoder System for Differentiation of Cancer Types Based on DNA Methylation State

On-chip Random ID Generation

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