Imperial College London

Dr Timothy Constandinou

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Reader in Neural Microsystems
 
 
 
//

Contact

 

+44 (0)20 7594 0790t.constandinou Website

 
 
//

Assistant

 

Miss Izabela Wojcicka-Grzesiak +44 (0)20 7594 0701

 
//

Location

 

B407Bessemer BuildingSouth Kensington Campus

//

Summary

 

Publications

Publication Type
Year
to

179 results found

Lauteslager T, Tommer M, Lande TS, Constandinou TGet al., 2019, Coherent UWB radar-on-chip for in-body measurement of cardiovascular dynamics, IEEE Transactions on Biomedical Circuits and Systems, ISSN: 1932-4545

Coherent 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.

Journal article

Ahmadi N, Cavuto ML, Feng P, Leene LB, Maslik M, Mazza F, Savolainen O, Szostak KM, Bouganis C-S, Ekanayake J, Jackson A, Constandinou TG, Ahmadi N, Cavuto M, Feng P, Leene L, Maslik M, Mazza F, Savolainen O, Szostak K, Bouganis C, Ekanayake J, Jackson A, Constandinou Tet al., 2019, Towards a distributed, chronically-implantable neural interface, 9th IEEE/EMBS International Conference on Neural Engineering (NER), Publisher: IEEE, Pages: 719-724, ISSN: 1948-3546

We 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.

Conference paper

Troiani 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.].

Journal article

Ahmadi N, Constandinou T, Bouganis C, 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), Pages: 1-5

Local eld potential (LFP) has gained increasing interest as an alternative input signal for brain-machine interfaces (BMIs) due to its informative features, long-term stability, and low frequency content. However, despite these interesting properties, LFP-based BMIs have been reported to yield low decoding performances compared to spike-based BMIs. In this paper, we propose a new decoder based on long short-term memory (LSTM) network which aims to improve the decoding performance of LFP-based BMIs. We compare of ine decoding performance of the proposed LSTM decoder to a commonly used Kalman lter (KF) decoder on hand kinematics prediction tasks from multichannel LFPs. We also benchmark the performance of LFP-driven LSTM decoder against KF decoder driven by two types of spike signals: singleunit activity (SUA) and multi-unit activity (MUA). Our results show that LFP-driven LSTM decoder achieves signi cantly better decoding performance than LFP-, SUA-, and MUAdrivenKF decoders. This suggests that LFPs coupled with LSTM decoder could provide high decoding performance, robust, and low power BMIs.

Conference paper

Leene LB, Letchumanan S, Constandinou TG, 2019, A 68 uW 31 kS/s fully-capacitive noise-shaping SAR ADC with 102 dB SNDR

This paper presents a 17 bit analogue-to-digital converter that incorporatesmismatch and quantisation noise-shaping techniques into an energy-saving 10 bitsuccessive approximation quantiser to increase the dynamic range by another 42dB. We propose a novel fully-capacitive topology which allows for high-speedasynchronous conversion together with a background calibration scheme to reducethe oversampling requirement by 10x compared to prior-art. A 0.18 um CMOStechnology is used to demonstrate preliminary simulation results together withanalytic measures that optimise parameter and topology selection. The proposedsystem is able to achieve a FoMS of 183 dB for a maximum signal bandwidth of15.6 kHz while dissipating 68 uW from a 1.8 V supply. A peak SNDR of 102 dB isdemonstrated for this rate with a 0.201 mm^2 area requirement.

Working paper

Ahmadi N, Constandinou TG, Bouganis C-S, Decoding Hand Kinematics from Local Field Potentials Using Long Short-Term Memory (LSTM) Network, Arxiv preprint

Local 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.

Journal article

Cavuto 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: 1948-3546

Conference paper

Liu Y, Constandinou TG, Georgiou P, 2019, A 32×32 ISFET array with in-pixel digitisation and column-wise TDC for ultra-fast chemical sensing, ISSN: 0271-4310

© 2019 IEEE This 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.

Conference paper

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

Journal article

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

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

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

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.

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

Lauteslager T, Tommer M, Lande TS, Constandinou TGet al., 2018, Cross-body UWB radar sensing of arterial pulse propagation and ventricular Dynamics, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 165-168

Single-chip UWB radar systems have enormouspotential for the development of portable, low-cost and easy-to-use devices for monitoring the cardiovascular system. Usingbody coupled antennas, electromagnetic energy can be directedinto the body to measure arterial pulsation and cardiac motion,and estimate arterial stiffness as well as blood pressure. Inthe current study we validate that heart rate signals, obtainedusing multiple UWB radar-on-chip modules and body coupledantennas, do indeed originate from arterial pulsation. ThroughECG-aligned averaging, pulse arrival time at a number oflocations in the body could be measured with high precision,and arterial pulse propagation through the femoral and carotidartery was demonstrated. In addition, cardiac dynamics weremeasured from the chest. Onset and offset of ventricular systolewere clearly distinguishable, as well as onset of atrial systole.Although further validation is required, these results show thatUWB radar-on-chip is highly suitable for monitoring of vascularhealth as well as the heart’s mechanical functioning.

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

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

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

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.

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

Troiani F, Nikolic K, Constandinou TG, 2018, Simulating optical coherence tomography for observing nerve activity: a finite difference time domain bi-dimensional model, PLoS ONE, Vol: 13, Pages: 1-14, ISSN: 1932-6203

We present a finite difference time domain (FDTD) model for computation of A line scans in time domain optical coherence tomography (OCT). The OCT output signal is created using two different simulations for the reference and sample arms, with a successive computation of the interference signal with external software. In this paper we present the model applied to two different samples: a glass rod filled with water-sucrose solution at different concentrations and a peripheral nerve. This work aims to understand to what extent time domain OCT can be used for non-invasive, direct optical monitoring of peripheral nerve activity.

Journal article

Ramezani R, Liu Y, Dehkhoda F, Soltan A, Haci D, Zhao H, Hazra A, Cunningham M, Firfilionis D, Jackson A, Constandinou TG, Degenaar Pet al., 2018, On-probe neural interface ASIC for combined electrical recording and optogenetic stimulation, IEEE Transactions on Biomedical Circuits and Systems, Vol: 12, Pages: 576-588, ISSN: 1932-4545

Neuromodulation technologies are progressing from pacemaking and sensory operations to full closed-loop control. In particular, optogenetics—the genetic modification of light sensitivity into neural tissue allows for simultaneous optical stimulation and electronic recording. This paper presents a neural interface application-specified integrated circuit (ASIC) for intelligent optoelectronic probes. The architecture is designed to enable simultaneous optical neural stimulation and electronic recording. It provides four low noise (2.08 μVrms) recording channels optimized for recording local field potentials (LFPs) (0.1–300 Hz bandwidth, ± 5 mV range, sampled 10-bit@4 kHz), which are more stable for chronic applications. For stimulation, it provides six independently addressable optical driver circuits, which can provide both intensity (8-bit resolution across a 1.1 mA range) and pulse-width modulation for high-radiance light emitting diodes (LEDs). The system includes a fully digital interface using a serial peripheral interface (SPI) protocol to allow for use with embedded controllers. The SPI interface is embedded within a finite state machine (FSM), which implements a command interpreter that can send out LFP data whilst receiving instructions to control LED emission. The circuit has been implemented in a commercially available 0.35 μm CMOS technology occupying a 1.95 mm × 1.10 mm footprint for mounting onto the head of a silicon probe. Measured results are given for a variety of bench-top, in vitro and in vivo experiments, quantifying system performance and also demonstrating concurrent recording and stimulation within relevant experimental models.

Journal article

Maslik M, Liu Y, Lande TS, Constandinou TGet al., 2018, Continuous-time acquisition of biosignals using a charge-based ADC topology, IEEE Transactions on Biomedical Circuits and Systems, Vol: 12, Pages: 471-482, ISSN: 1932-4545

This paper investigates Continuous-Time (CT) signal acquisition as an activity-dependent and non-uniform sampling alternative to conventional fixed-rate digitisation. We demonstrate the applicability to biosignal representation by quantifying the achievable bandwidth saving by non-uniform quantisation to commonly recorded biological signal fragmentsallowing a compression ratio of 5 and 26 when applied to Electrocardiogram (ECG) and Extracellular Action Potential (EAP) signals respectively. We describe several desirable properties of CT sampling including bandwidth reduction, elimination/reduction of quantisation error and describe its impact on aliasing. This is followed by demonstration of a resource-efficient hardware implementation. We propose a novel circuit topology for a charge-based CT Analogue-to-Digital Converter (CT ADC) that has been optimised for the acquisition of neural signals. This has been implemented in a commercially-available 0.35µm CMOS technology occupying a compact footprint of 0.12mm². Silicon verified measurements demonstrate an 8-bit resolution and a 4kHz bandwidth with static power consumption of 3.75µWfrom a 1.5V supply. The dynamic power dissipation is completely activity-dependent, requiring 1.39pJ energy per conversion.

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: 1-21, 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

Journal article

Leene L, Maslik M, Feng P, Szostak K, Mazza F, Constandinou TGet al., 2018, Autonomous SoC for neural local field potential recording in mm-scale wireless implants, IEEE International Symposium on Circuits and Systems, Publisher: IEEE, Pages: 1-5, ISSN: 2379-447X

Next generation brain machine interfaces fundamentally need to improve the information transfer rate and chronic consistency when observing neural activity over a long period of time. Towards this aim, this paper presents a novel System-on-Chip (SoC) for a mm-scale wireless neural recording node that can be implanted in a distributed fashion. The proposed self-regulating architecture allows each implant to operate autonomously and adaptively load the electromagnetic field to extract a precise amount of power for full-system operation. This can allow for a large number of recording sites across multiple implants extending through cortical regions without increased control overhead in the external head-stage. By observing local field potentials (LFPs) only, chronic stability is improved and good coverage is achieved whilst reducing the spatial density of recording sites. The system features a ΔΣ based instrumentation circuit that digitises high fidelity signal features at the sensor interface thereby minimising analogue resource requirements while maintaining exceptional noise efficiency. This has been implemented in a 0.35 μm CMOS technology allowing for wafer-scale post-processing for integration of electrodes, RF coil, electronics and packaging within a 3D structure. The presented configuration will record LFPs from 8 electrodes with a 825 Hz bandwidth and an input referred noise figure of 1.77μVrms. The resulting electronics has a core area of 2.1 mm2 and a power budget of 92 μW

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.

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

Luo JW, Firfilionis D, Ramezani R, Dehkhoda F, Soltan A, Degenaar P, Liu Y, Constandinou Tet al., 2018, Live demonstration: A closed-loop cortical brain implant for optogenetic curing epilepsy

© 2017 IEEE. A closed-loop optogenetic system for curing epilepsy is presented in this work. As it shown at figure 1, the system consists of a cortical brain implant with LEDs and recording electrodes, a customer designed CMOS chip[1][2][3] and a controller. The brain activities are recorded by the implant with recording electronics in a CMOS chip, the signals are processed by the controller, and the results are send back to the CMOS chip for delivering LED stimulation commands.

Conference paper

Mifsud A, Haci D, Ghoreishizadeh SS, Liu Y, Constandinou TGet al., 2018, Adaptive power regulation and data delivery for multi-module implants, Pages: 1-4

© 2017 IEEE. Emerging applications for implantable devices are requiring multi-unit systems with intrabody transmission of power and data through wireline interfaces. This paper proposes a novel method for power delivery within such a configuration that makes use of closed loop dynamic regulation. This is implemented for an implantable application requiring a single master and multiple identical slave devices utilising a parallel-connected 4-wire interface. The power regulation is achieved within the master unit through closed loop monitoring of the current consumption to the wired link. Simultaneous power transfer and full-duplex data communication is achieved by superimposing the power carrier and downlink data over two wires and uplink data over a second pair of wires. Measured results using a fully isolated (AC coupled) 4-wire lead, demonstrate this implementation can transmit up to 120 mW of power at 6 V (at the slave device, after eliminating any losses). The master device has a maximum efficiency of 80 % including a dominant dynamic power loss. A 6 V constant supply at the slave device is recovered 1.5 ms after a step of 22 mA.

Conference paper

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: respub-action=search.html&id=00203525&limit=30&person=true