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Conference paperWong S, Ekanayake J, Liu Y, et al., 2019,
An impedance probing system for real-time intra-operative brain tumour tissue discrimination
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4The ability to perform realtime diagnostics of tissueintraoperatively can greatly enhance the precision and effective-ness of the underlying surgery, for example, in tumour resection.To achieve this however would require a miniature tool ableto performin situ, in-vivocharacterisation for distinguishingbetween different types of tissues. In this work, we exploredthe feasibility and requirements of implementing a portableimpedance characterisation system for brain tumour detection.We proposed and implemented a novel system based on PCB-based instrumentation using a square four-electrode microendo-scopic probe. The system uses a digital-to-analogue converterto generate a multi-tone sinusoid waveform, and a floating bi-directional voltage-to-current converter to output the differentialstimulation current to one pair of electrodes. The other pairof electrodes are connected to the sensing circuit based on aninstrumentation amplifier. The recorded data is pre-processed bythe micro-controller and then analysed on a host computer. Toevaluate the system, tetrapolar impedances have been recordedfrom a number of different electrode configurations to sense pre-defined resistance values. The overall system consumes 143 mAcurrent, achieve 0.1% linearity and 15μV noise level, with amaximum signal bandwidth of 100 kHz. Initial experimentalresults on tissue were carried out on a piece of rib-eye steak.Electrical impedance maps (EIM) and contour plots were thenreconstructed to represent the impedance value in different tissue region.
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Conference paperWilliams I, Rapeaux A, Pearson J, et al., 2019,
SenseBack - implant considerations for an implantable neural stimulation and recording device
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4This paper describes a fully implantable and highlycompact neural interface platform for chronic (>6 month) ratand small rodent experiments. It provides 32 channels of highlyflexible neural stimulation and recording with wireless controland data readout, as well as wireless transcutaneous power. Allthe system firmware is fully upgradeable over the air (even afterimplantation) allowing future enhancements such as closed loopoperation or data filtering. This paper focuses on the implantconsiderations – i.e. design and manufacture of the physicalplatform, encapsulation, wireless connections and testing.
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Journal articleLiu Y, Constandinou TG, Georgiou P, 2019,
Ultrafast large-scale chemical sensing with CMOS ISFETs: a level-crossing time-domain approach
, IEEE Transactions on Biomedical Circuits and Systems, Vol: 13, Pages: 1201-1213, ISSN: 1932-4545The introduction of large-scale chemical sensing systems in CMOS which integrate millions of ISFET sensors have allowed applications such as DNA sequencing and fine-pixel chemical imaging systems to be realised. Using CMOS ISFETs provides advantages of digitisation directly at the sensor as well as correcting for non-linearity in its response. However, for this to be beneficial and scale, the readout circuits need to have the minimum possible footprint and power consumption. Within this context, this paper analyses an ISFET based pH-to-time readout using an inverter in the time-domain as a level-crossing detector and presents a 32×32 array with in-pixel digitisation for pH sensing. The inverter-based sensing pixel, controlled by a triangular waveform, converts the pH response into a time-domain signal whilst also compensating for sensor offset and thus resulting in an increase in dynamic range. The sensor pixels interface to a 15-bit asynchronous column-wise time-to-digital converter (TDC), enabling fast asynchronous conversion whilst using minimal silicon area. Parallel outputs of 32 TDC interfaces are serialised to achieve fast data throughput. This system is implemented in a standard 0.18um CMOS technology, with a pixel size of 26μm×26μm and a TDC area of 26μm×180μm. Measured results demonstrate the system is able to sense reliably with an average pH sensitivity of 30mVpH, whilst being able to compensate for sensor offset by up to ±7V. A resolution of 0.013pH is achieved and noise measurements show an integrated noise of 0.08pH within 2-500Hz and SFDR of 42.6dB. Total power consumption is 11.286mW.
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Journal articleChew DJ, Constandinou TG, Gupta I, et al., 2019,
Bioelectronic medicines: past, present and future. Highlights from The Society for Medicines Research Symposium
, Drugs of the Future, Vol: 44, Pages: 895-902, ISSN: 0377-8282On October 1, 2019, the Society for Medicines Research (SMR) held its first symposium on "Bioelectronic medicines, past, present and future" at the Royal Academy of Engineering in London. The meeting was attended by 145 participants and was supported by Galvani Bioelectronics, IEEE-CAS Society, IEEE-Brain Initiative, BIOS, Heraeus, CorTec and the IT'IS Foundation.
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Conference paperDe Marcellis A, Stanchieri GDP, Palange E, et al., 2019,
A 0.35 mu m CMOS UWB-inspired bidirectional communication system-on-chip for transcutaneous optical biotelemetry links
, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, ISSN: 2163-4025In this paper we report on the fabrication, implementation and experimental characterization of an integrated bidirectional communication System-on-Chip (SoC) for transcutaneous bidirectional optical biotelemetry links. The proposed architecture implements a UWB-inspired pulsed coding technique and contains a transmitter and a receiver to achieve a simultaneous bidirectional link. The transmitter generates sub- nanosecond current pulses to directly drive offchip pulsed vertical cavity semiconductor lasers by means of a digital data coding subsystem and all the needed bias and driving circuits. The receiver interfaces to off-chip fast Si photodiodes and includes signal conditioning, detection and digital data decoding circuits to support high bit rate and energy efficient communication links. The SoC has been implemented in a commercially-available 0.35 mu m CMOS technology provided by AMS, occupying a compact silicon footprint of less than 0.13 mm2 employing 113 transistors and 1 resistor. This is evaluated using a testbench consisting of a custom PCB and a Xilinx Virtex-6 XC6VLX240T FPGA board. Preliminary experimental results validated the correct functionality of the overall integrated system demonstrating its capability to operate, also in a bidirectional mode, at bit rates up to 250 Mbps with pulse widths down to 1.2 ns and a minimum total power efficiency of about 160 pJ/bit in the conditions for which the transmitter and the receiver work simultaneously on the same chip. This demonstrated performance makes the optical biotelemetry particularly suitable for highly scalable (i.e., high bitrate, low energy per bit) implantable devices such as brain machine interfaces.
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Conference paperHan Y, Lauteslager T, Lande TS, et al., 2019,
UWB radar for non-contact heart rate variability monitoring and mental state classification.
, Annual Meeting of the IEEE Engineering in Medicine and Biology Society, Pages: 6578-6582, ISSN: 1557-170XHeart rate variability (HRV), as measured by ultra-wideband (UWB) radar, enables contactless monitoring of physiological functioning in the human body. In the current study, we verified the reliability of HRV extraction from radar data, under limited transmitter power. In addition, we conducted a feasibility study of mental state classification from HRV data, measured using radar. Specifically, arctangent demodulation with calibration and low rank approximation have been used for radar signal pre-processing. An adaptive continuous wavelet filter and moving average filter were utilized for HRV extraction. For the mental state classification task, performance of support vector machine, k-nearest neighbors and random forest classifiers have been compared. The developed system has been validated on human participants, with 10 participants for HRV extraction, and three participants for the proof-of-concept mental state classification study. The results of HRV extraction demonstrate the reliability of time-domain parameter extraction from radar data. However, frequency-domain HRV parameters proved to be unreliable under low SNR. The best average overall mental state classification accuracy achieved was 82.34%, which has important implications for the feasibility of mental health monitoring using UWB radar.
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Journal articleLauteslager T, Tommer M, Lande TS, et al., 2019,
Coherent UWB radar-on-chip for in-body measurement of cardiovascular dynamics
, IEEE Transactions on Biomedical Circuits and Systems, Vol: 13, Pages: 814-824, ISSN: 1932-4545Coherent ultra-wideband (UWB) radar-on-chip technology shows great promise for developing portable and low-cost medical imaging and monitoring devices. Particularly monitoring the mechanical functioning of the cardiovascular system is of interest, due to the ability of radar systems to track sub-mm motion inside the body at a high speed. For imaging applications, UWB radar systems are required, but there are still significant challenges with in-body sensing using low-power microwave equipment and wideband signals. Recently it was shown for the first time, on a single subject, that the arterial pulse wave can be measured at various locations in the body, using coherent UWB radar-on-chip technology. The current work provides more substantial evidence, in the form of new measurements and improved methods, to demonstrate that cardiovascular dynamics can be measured using radar-on-chip. Results across four participants were found to be robust and repeatable. Cardiovascular signals were recorded using radar-on-chip systems and electrocardiography (ECG). Through ECG-aligned averaging, the arterial pulse wave could be measured at a number of locations in the body. Pulse arrival time could be determined with high precision, and blood pressure pulse wave propagation through different arteries was demonstrated. In addition, cardiac dynamics were measured from the chest. This work serves as a first step in developing a portable and low-cost device for long-term monitoring of the cardiovascular system, and provides the fundamentals necessary for developing UWB radar-on-chip imaging systems.
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Conference paperAhmadi N, Constandinou TG, Bouganis C-S, 2019,
End-to-End Hand Kinematic Decoding from LFPs Using Temporal Convolutional Network
, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 1-4, ISSN: 2163-4025In recent years, local field potentials (LFPs) haveemerged as a promising alternative input signal for brain-machine interfaces (BMIs). Several studies have demonstratedthat LFP-based BMIs could provide long-term recording stabilityand comparable decoding performance to their spike counter-parts. Despite the compelling results, however, most LFP-basedBMIs still make use of hand-crafted features which can betime-consuming and suboptimal. In this paper, we propose anend-to-end system approach based on temporal convolutionalnetwork (TCN) to automatically extract features and decodekinematics of hand movements directly from raw LFP signals.We benchmark its decoding performance against traditionalapproach incorporating long short-term memory (LSTM) de-coders driven by hand-crafted LFP features. Experimental re-sults demonstrate significant performance improvement of theproposed approach compared to the traditional approach. Thissuggests the suitability of TCN-based end-to-end system and itspotential for providng stable and high decoding performanceLFP-based BMIs.
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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 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 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 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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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 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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