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  • Conference paper
    Liu Y, Pereira J, Constandinou TG, 2016,

    Clockless Continuous-Time Neural Spike Sorting: Method, Implementation and Evaluation

    , IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 538-541

    In this paper, we present a new method for neuralspike sorting based on Continuous Time (CT) signal processing.A set of CT based features are proposed and extracted fromCT sampled pulses, and a complete event-driven spike sortingalgorithm that performs classification based on these features isdeveloped. Compared to conventional methods for spike sorting,the hardware implementation of the proposed method does notrequire any synchronisation clock for logic circuits, and thusits power consumption depend solely on the spike activity. Thishas been implemented using a variable quantisation step CTanalogue to digital converter (ADC) with custom digital logicthat is driven by level crossing events. Simulation results usingsynthetic neural data shows a comparable accuracy comparedto template matching (TM) and Principle Components Analysis(PCA) based discrete sampled classification.
  • Conference paper
    Troiani F, Nikolic K, Constandinou TG, 2016,

    Optical Coherence Tomography for detection of compound action potential in Xenopus Laevis sciatic nerve

    , SPIE Photonics West (BIOS)

    Due to optical coherence tomography (OCT) high spatial and temporal resolution, this technique could be used to observe the quick changes in the refractive index that accompany action potential. In this study we explorethe use of time domain Optical Coherence Tomography (TD-OCT) for real time action potential detection in ex vivo Xenopus Laevis sciatic nerve. TD-OCT is the easiest and less expensive OCT technique and, if successful indetecting real time action potential, it could be used for low cost monitoring devices. A theoretical investigation into the order of magnitude of the signals detected by a TD-OCT setup is provided by this work. A lineardependence between the refractive index and the intensity changes is observed and the minimum SNR for which the setup could work is found to be SNR = 2 x10⁴.
  • Conference paper
    Dehkhoda F, Soltan A, Ramezani R, Zhao H, Liu Y, Constandinou TG, Degenaar Pet al., 2015,

    Smart Optrode for Neural Stimulation and Sensing

    , 2015 IEEE Sensors Conference, Publisher: IEEE, Pages: 1-4

    Implantable neuro-prosthetics considerable clinical benefit to a range of neurological conditions. Optogenetics is a particular recent interest which utilizes high radiance light for photo-activation of genetic cells. This can provide improved biocompatibility and neural targeting over electrical stimuli. To date the primary optical delivery method in tissue for optogenetics has been via optic fibre which makes large scale multiplexing difficult. An alternative approach is to incorporate optical micro-emitters directly on implantable probes but this still requires electrical multiplexing. In this work, we demonstrate a fully active optoelectronic probe utilizing industry standard 0.35μm CMOS technology, capable of both light delivery and electrical recording. The incorporation of electronic circuits onto the device further allows us to incorporate smart sensors to determine diagnostic state to explore long term viability during chronic implantation.
  • Conference paper
    Williams I, Luan S, Jackson A, Constandinou TGet al., 2015,

    A scalable 32 channel neural recording and real-time FPGA based spike sorting system

    , IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 187-191

    This demo presents a scalable a 32-channel neuralrecording platform with real-time, on-node spike sorting ca-pability. The hardware consists of: an Intan RHD2132 neuralamplifier; a low power Igloo ® nano FPGA; and an FX3 USB3.0 controller. Graphical User Interfaces for controlling thesystem, displaying real-time data, and template generation witha modified form of WaveClus are demonstrated.
  • Conference paper
    De Marcellis A, Palange E, Liberatore V, Nubile L, Faccio M, Constandinou TGet al., 2015,

    A new modulation technique for high data rate low power UWB wireless optical communication in implantable biotelemetry systems

    , Eurosensors 2015

    We report on the development of a novel modulation technique for UWB wireless optical communication systems for application in a transcutaneous biotelemetry. The solution, based on the generation of short laser pulses, allows for a high data rate link whilst achieving a significant power reduction (energy per bit) compared to the state-of-the-art. These features make this particularly suitable for emerging biomedical applications such as implantable neural/biosensor systems. The relatively simple architecture consists of a transmitter and receiver that can be integrated in a standard CMOS technology in a compact Silicon footprint. These parts include circuits for bias and drive current generation, conditioning and processing, optimised for low-volt age/low-power operation. Preliminary experimental findings validate the new paradigm and show good agreement with expected results. The complete system achieves a BER less than 10-7, with maximum data rate of 125Mbps and estimated total power consumption of less than 3mW.
  • Patent
    Jackson A, Constandinou TG, Eftekhar A, Quiroga RQ, Navajas JAet al., 2015,

    System for a Brain-Computer Interface
  • Conference paper
    Rapeaux A, Nikolic K, Williams I, Eftekhar A, Constandinou TGet al., 2015,

    Fiber size-selective stimulation using action potential filtering for a peripheral nerve interface: A simulation study

    , 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Pages: 3411-3414

    Functional electrical stimulation is a powerfultool for restoration of function after nerve injury. Howeverselectivity of stimulation remains an issue. This paper presentsan alternative stimulation technique to obtain fiber size-selectivestimulation of nerves using FDA-approved electrode implants.The technique was simulated for the ventral roots ofXenopus Laevis, motivated by an application in bladder control. Thetechnique relies on applying a high frequency alternatingcurrent to filter out action potentials in larger fibers, resultingin selective stimulation of the smaller fibers. Results predict thatthe technique can distinguish fibers with only a 2 µm differencein diameter (for nerves not exceeding 2 mm in diameter). Thestudy investigates the behaviour of electrically blocked nervesin detail. Model imperfections and simplifications yielded someartefacts in the results, as well as unexpected nerve behaviourwhich is tentatively explained.
  • Conference paper
    Woods S, Constandinou TG, 2015,

    A novel holding mechanism for next generation active wireless capsule endoscopy

    , 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Publisher: IEEE, Pages: 1181-1185

    This paper proposes that next generation wirelesscapsule endoscopy (WCE) technology will feature active me-chanical components (i.e. actuated) as opposed to current sys-tems that are predominantly passive (e.g. for imaging purposes).Future systems will integrate microsystems that use micro-actuators to, for example, perform micro-surgery, take tissuesamples, deliver medication, etc. In this paper we detail a novel,ultra-compact integrated mechanism for resisting peristalsisand describe how this can be fabricated in Nylon 6 usingCNC milling. The holding action is achieved by extendingan “anchor” spanning an effective 60.4 mm circumference, fora 11.0 mm diameter WCE. This function is achieved by amechanism that occupies only 347.0 mm3volume, includingmechanics and actuator. This shows how exploiting conventionalmanufacturing processes can result in a radical change in thecapabilities of WCE systems and empower the next generationof active devices.
  • Journal article
    Woods S, Constandinou TG, 2015,

    Engineering Micro Mechanical Systems for the Next Generation Wireless Capsule Endoscopy

    , BioMed Research International, Vol: 2015, ISSN: 2314-6141

    Wireless capsule endoscopy (WCE) enables the detection and diagnosis of in ammatory bowel diseases such as Crohn's disease and ulcerative colitis. However treatment of these pathologies through the administering of therapy can only be achieved through conventional means. This paper describes the next generation wireless capsule endoscopy which has increased functionality to allow for targeted drug delivery in the small intestinal tract. A prototype microrobot fabricated in Nylon 6 is presented which is capable of resisting natural peristaltic pressure through the deployment of an integrated holding mechanism and delivering targeted therapy. The holding action is achieved by extending an \anchor" spanning an effective 60.4mm circumference, for a 11.0mm diameterWCE. This function is achieved by a mechanism that occupies only 347.0mm3 volume, including mechanics and actuator. A micro-positioning mechanism is described which utilises a single micromotor to radially position then deploy a needle 1.5mm outside the microrobot's body for the purpose of delivering a 1 ml dose of medication to a targeted site. An analysis of the mechanics required to drive the holding mechanism is presented and an overview of micro-actuators and the state of the art in WCE is discussed. The novel mechanisms offer increased functionality to WCE. It is envisaged that this increased ability to perform targeted therapy will empower the next generation of WCE to help diagnose and treat pathologies of the GI tract.
  • Conference paper
    Faliagkas K, Leene L, Constandinou TG, 2015,

    A Novel Neural Recording System Utilising Continuous Time Energy Based Compression

    , IEEE International Symposium on Circuits & Systems (ISCAS), Publisher: IEEE, Pages: 3000-3003

    This work presents a new data compression methodthat uses an energy operator to exploit the correlated energy inneural recording features in order to achieve adaptive sampling.This approach enhances conventional data converter topologieswith the power saving of asynchronous systems while maintaininglow complexity & high efficiency. The proposed scheme enablesthe transmission of 0:7kS/s, while preserving the features of thesignal with an accuracy of 95%. It is also shown that the operationof the system is not susceptible to noise, even for signals with 1dBSNR. The whole system consumes 3:94mWwith an estimated areaof 0:093mm2.
  • Patent
    Reed S, Georgiou P, Constandinou TG, 2015,

    Method and Apparatus for Sensing a Property of a Fluid

    , 8,986,525 B2

    A device for sensing a property of a fluid comprising a first substrate having formed thereon a sensor configured in use to come into contact with a fluid in order to sense a property of the fluid, and a wireless transmitter for transmitting data over a wireless data link and a second substrate having formed thereon a wireless receiver for receiving data transmitted over said wireless link by said wireless transmitter. The first substrate is fixed to or within said second substrate. Additionally or alternatively, the device comprises a first substrate defining one or more microfluidic structures for receiving a fluid to be sensed and a second substrate comprising or having attached thereto a multiplicity of fluid sensors, the number of sensors being greater than the number of microfluidic structures. The second substrate is in contact with the first substrate such that at least one of the sensors is aligned with the or each microfluidic structure so as to provide an active sensor for the or each structure, and such that one or more of the sensors is or are not aligned with any microfluidic structure and is or are thereby redundant.
  • Conference paper
    Demarchou E, Georgiou J, Nicolaou N, Constandinou TGet al., 2014,

    Anesthetic-induced changes in EEG activity: a graph theoretical approach

    , IEEE Biomedical Circuits and Systems (BioCAS) Conference, Pages: 45-48

    The dynamic brain networks forming during wakefulness and anesthetic-induced unconsciousness are investigated using time-delayed correlation and graph theoretical measures. Electrical brain activity (EEG) from 10 patients under propofol anesthesia during routine surgery is characterized using the shortest path length, λ, and clustering, c, extracted from time delayed correlation. An increase in λ and c during anesthesiareveals disruption of long-range connections and emergence of more localized neighborhoods. These changes were not a result of volume conduction, as were based on time-delayed correlation. Our observations are in line with theories of anesthetic action and support the use of graph theoretic measures to study emerging brain networks during wakefulness and anesthesia.
  • Journal article
    Paraskevopoulou SE, Wu D, Eftekhar A, Constandinou TGet al., 2014,

    Hierarchical Adaptive Means (HAM) Clustering for Hardware-Efficient, Unsupervised and Real-time Spike Sorting.

    , Journal of Neuroscience Methods, Vol: 235, Pages: 145-156, ISSN: 1872-678X

    This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation.
  • Journal article
    Luan S, Williams I, Constandinou TG, Nikolic Ket al., 2014,

    Neuromodulation: present and emerging methods

    , Frontiers of Neuroengineering, Vol: 7, ISSN: 1662-6443

    Neuromodulation has wide ranging potential applications in replacing impaired neural function (prosthetics), as a novel form of medical treatment (therapy), and as a tool for investigating neurons and neural function (research). Voltage and current controlled electrical neural stimulation (ENS) are methods that have already been widely applied in both neuroscience and clinical practice for neuroprosthetics. However, there are numerous alternative methods of stimulating or inhibiting neurons. This paper reviews the state-of-the-art in ENS as well as alternative neuromodulation techniques - presenting the operational concepts, technical implementation and limitations - in order to inform system design choices.
  • Journal article
    Williams I, Constandinou TG, 2014,

    Computationally Efficient Modelling of Proprioceptive Signals in the Upper Limb for Prostheses: a Simulation Study

    , Frontiers in Neuroscience, Vol: 8, Pages: 1-13

    Accurate models of proprioceptive neural patterns could one day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimisation) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modelling. This paper uses and proposes a number of approximations and optimisations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed.
  • Journal article
    Eftekhar A, Juffali W, El-Imad J, Constandinou TG, Toumazou Cet al., 2014,

    Ngram-derived Pattern Recognition for the Detection and Prediction of Epileptic Seizures

    , PLOS One, Vol: 9, Pages: 1-15

    This work presents a new method that combines symbol dynamics methodologies with an Ngram algorithm for the detection and prediction of epileptic seizures. The presented approach specifically applies Ngram-based pattern recognition, after data pre-processing, with similarity metrics, including the Hamming distance and Needlman-Wunsch algorithm, for identifying unique patterns within epochs of time. Pattern counts within each epoch are used as measures to determine seizure detection and prediction markers. Using 623 hours of intracranial electrocorticogram recordings from 21 patients containing a total of 87 seizures, the sensitivity and false prediction/detection rates of this method are quantified. Results are quantified using individual seizures within each case for training of thresholds and prediction time windows. The statistical significance of the predictive power is further investigated. We show that the method presented herein, has significant predictive power in up to 100% of temporal lobe cases, with sensitivities of up to 70–100% and low false predictions (dependant on training procedure). The cases of highest false predictions are found in the frontal origin with 0.31–0.61 false predictions per hour and with significance in 18 out of 21 cases. On average, a prediction sensitivity of 93.81% and false prediction rate of approximately 0.06 false predictions per hour are achieved in the best case scenario. This compares to previous work utilising the same data set that has shown sensitivities of up to 40–50% for a false prediction rate of less than 0.15/hour.
  • Journal article
    Leene LB, Constandinou TG, 2014,

    Ultra-low power design strategy for two-stage amplifier topologies

    , Electronics Letters, Vol: 50, Pages: 583-585, ISSN: 0013-5194

    A novel two-stage amplifier topology and ultra-low power design strategy for two-stage amplifiers that utilises pole zero cancellation to address the additional power requirements for stability are presented. For a 288 nA total bias, the presented amplifier achieves a 1.07 MHz unity gain frequency with a 8560 pF MHz/mA figure of merit.
  • Journal article
    Luan S, Constandinou TG, 2014,

    A Charge-Metering Method for Voltage-Mode Neural Stimulation

    , Journal of Neuroscience Methods, Vol: 224, Pages: 39-47, ISSN: 0165-0270

    Electrical Neural Stimulation is the technique used to modulate neural activity by inducing an instantaneous charge imbalance. This is typically achieved by injecting a constant current and controlling the stimulation time. However, constant voltage stimulation is found to be more energy-efficient although it is challenging to control the amount of charge delivered. This paper presents a novel, fully-integrated circuit for facilitating charge-metering in constant voltage stimulation. It utilises two complementary stimulation paths. Each path includes a small capacitor, a comparator and a counter. They form a mixed-signal integrator that integrates the stimulation current onto the capacitor whilst monitoring its voltage against a threshold using the comparator. The pulses from the comparator are used to increment the counter and reset the capacitor. Therefore, by knowing the value of the capacitor, threshold voltage and output of the counter, the quantity of charge delivered can be calculated. The system has been fabricated in 0.18μm CMOS technology, occupying a total active area of 339μm×110μm. Experimental results were taken using: (1) a resistor-capacitor EEI model and (2) platinum electrodes with ringer solution. The viability of this method in recruiting action potentials has been demonstrated using a cuff electrode with Xenopus Sciatic nerve. For a 10nC target charge delivery, the results of (2) show a charge delivery error of 3.4% and a typical residual charge of 77.19pC without passive charge recycling. The total power consumption is 45μW. The performance is comparable with other publications. Therefore, the proposed stimulation method can be used as a new approach for neural stimulation.
  • Journal article
    Barsakcioglu D, Liu Y, Bhunjun P, Navajas J, Eftekhar A, Jackson A, Quian Quiroga R, Constandinou TGet al., 2014,

    An Analogue Front-End Model for Developing Neural Spike Sorting Systems

    , IEEE Transactions on Biomedical Circuits and Systems, Vol: 8, Pages: 216-227
  • Journal article
    Navajas J, Barsakcioglu D, Eftekhar A, Jackson A, Constandinou TG, Quian Quiroga Ret al., 2014,

    Minimum Requirements for Accurate and Efficient Real-Time On-Chip Spike Sorting

    , Journal of Neuroscience Methods, Pages: 51-64

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