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  • 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
    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, Publisher: IEEE, Pages: 1-4
  • 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, Publisher: IEEE, Pages: 1-4
  • 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, Pages: 1-12, 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

  • 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, Publisher: IEEE, Pages: 1-4
  • 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: 1-4
  • 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: 1-4
  • 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.

  • CONFERENCE PAPER
    Leene L, Constandinou TG, 2018,

    Direct Digital Wavelet Synthesis for Embedded Biomedical Microsystems

    , IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4
  • CONFERENCE PAPER
    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

  • JOURNAL ARTICLE
    Liu Y, Pereira JL, Constandinou TG, 2018,

    Event-driven processing for hardware-efficient neural spike sorting

    , JOURNAL OF NEURAL ENGINEERING, Vol: 15, ISSN: 1741-2560
  • JOURNAL ARTICLE
    Luan S, Williams I, Maslik M, Liu Y, De Carvalho F, Jackson A, Quiroga RQ, Constandinou TGet al., 2018,

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

    , J Neural Eng, Vol: 15

    OBJECTIVE: Longitudinal observation of single unit neural activity from large numbers 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 and storage, and typically require offline 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 h at a time and is robust to power dropouts during battery changes as well as SD card replacement. A 24 h initial recording in a non-human primate M1 showed consistent spike shapes with the expected changes in neural activity during awake behaviour and sleep cycles. SIGNIFICANCE: 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 verifiable outp

  • 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, Publisher: IEEE, Pages: 1-4
  • 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
  • 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, Publisher: IEEE, Pages: 1-4
  • 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: 1-4
  • JOURNAL ARTICLE
    Ramezani R, Liu Y, Dehkhoda F, Soltan A, Haci D, Zhao H, Firfilionis D, Hazra A, Cunningham MO, 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
  • 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.

  • 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.

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