Publications
276 results found
Ghoreishizadeh S, Haci D, Liu Y, et al., 2017, A 4-wire interface SoC for shared multi-implant power transfer and full-duplex communication, IEEE Latin American symposium on Circuits and Systems (LASCAS), Publisher: IEEE, Pages: 49-52, ISSN: 2473-4667
This paper describes a novel system for recovering power and providing full-duplex communication over an AC-coupled 4-wire lead between active implantable devices. The target application requires a single Chest Device be connected to a Brain Implant consisting of multiple identical optrodes that record neural activity and provide closed loop optical stimulation. The interface is integrated within each optrode SoC allowing full-duplex and fully-differential communication based on Manchester encoding. The system features a head-to-chest uplink data rate (1.6 Mbps) that is higher than that of the chest-to-head downlink (100kbps) superimposed on a power carrier. On-chip power management provides an unregulated 5 V DC supply with up to 2.5 mA output current for stimulation, and a regulated 3.3 V with 60 dB PSRR for recording and logic circuits. The circuit has been implemented in a 0.35 μm CMOS technology, occupying 1.4 mm 2 silicon area, and requiring a 62.2 μA average current consumption.
Leene L, Constandinou TG, 2017, A 0.016² 12b ΔΣSAR With 14fJ/conv. for ultra low power biosensor arrays, IEEE Transactions on Circuits and Systems. Part 1: Regular Papers, Vol: 64, Pages: 2655-2665, ISSN: 1549-8328
The instrumentation systems for implantable brain-machine interfaces represent one of the most demanding applications for ultra low-power analogue-to-digital-converters (ADC) to date. To address this challenge, this paper proposes a ΔΣSAR topology for very large sensor arrays that allows an exceptional reduction in silicon footprint by using a continuous time 0-2 MASH topology. This configuration uses a specialized FIR window to decimate the ΔΣ modulator output and reject mismatch errors from the SAR quantizer, which mitigates the overhead from dynamic element matching techniques commonly used to achieve high precision. A fully differential prototype was fabricated using 0.18 μm CMOS to demonstrate 10.8 ENOB precision with a 0.016 mm² silicon footprint. Moreover, a 14 fJ/conv figure-of-merit can be achieved, while resolving signals with the maximum input amplitude of ±1.2,Vpp sampled at 200 kS/s. The ADC topology exhibits a number of promising characteristics for both high speed and ultra low-power systems due to the reduced complexity, switching noise, sampling load, and oversampling ratio, which are critical parameters for many sensor applications.
Luan S, Williams I, De-Carvalho F, et al., 2017, Standalone headstage for neural recording with real-time spike sorting and data logging, BNA Festival of Neuroscience, Publisher: The British Neuroscience Association Ltd
Sundarasaradula Y, Constandinou TG, Thanachayanont A, 2017, A 6-bit, two-step, successive approximation logarithmic ADC for biomedical applications, IEEE International Conference on Electronics, Circuits and Systems (ICECS), Publisher: IEEE, Pages: 25-28
This paper presents the design and realization of a novel low-power 6-bit successive approximation logarithmic ADC for biomedical applications. A two-step successive approximation method is proposed to obtain a piecewise-linear approximation of the desired logarithmic transfer function. The proposed ADC has been designed and simulated using process parameters from a standard 0.35 μm 2P4M CMOS technology with a single 1.8 V power supply voltage. Simulation results show that, at a sampling rate of 25 kS/s, the proposed ADC consumes 4.36 μW to 14.6 μW (proportional to input amplitudes). The proposed ADC achieves 18.6 pJ/conversion-step, maximum INL of 0.45 LSB, an ENOB of 4.97-bits, and SNDR of 31.7 dB with 1 V full-scale input range.
Leene L, Constandinou TG, 2017, A 0.45V continuous time-domain filter using asynchronous oscillator structures, IEEE International Conference on Electronics, Circuits and Systems (ICECS), Publisher: IEEE, Pages: 49-52
This paper presents a novel oscillator based filter structure for processing time-domain signals with linear dynamics that extensively uses digital logic by construction. Such a mixed signal topology is a key component for allowing efficient processing of asynchronous time encoded signals that does not necessitate external clocking. A miniaturized primitive is introduced as analogue time-domain memory that can be modelled, synthesized, and incorporated in closed loop mixed signal accelerators to realize more complex linear or non-linear computational systems. This is contextualized by demonstrating a compact low power filter operating at 0.45 V in 65 nm CMOS. Simulation results are presented showing an excess of 50 dB dynamic range with a FOM of 7fJ/pole which promises an order of magnitude improvement on state-of-the-art filters in nanometre CMOS.
Luan S, Liu Y, Williams I, et al., 2017, An Event-Driven SoC for Neural Recording, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 404-407
This paper presents a novel 64-channel ultra-low power/low noise neural recording System-on-Chip (SoC) featuring a highly reconfigurable Analogue Front-End (AFE) and block-selectable data-driven output. This allows a tunable bandwidth/sampling rate for extracting Local Field Potentials (LFPs)and/or Extracellular Action Potentials (EAPs). Realtime spike detection utilises a dual polarity simple threshold to enable an event driven output for neural spikes (16-sample window). The 64-channels are organised into 16 sets of 4-channel recording blocks, with each block having a dedicated 10-bit SAR ADC that is time division multiplexed among the 4 channels. Eachchannel can be individually powered down and configured for bandwidth, gain and detection threshold. The output can thus combine continuous-streaming and event-driven data packets with the system configured as SPI slave. The SoC is implemented in a commercially-available 0.35u m CMOS technology occupying a silicon area of 19.1mm^2 (0.3mm^2 gross per channel) and requiring 32uW/channel power consumption (AFE only).
Williams I, Rapeaux A, Liu Y, et al., 2017, A 32-channel bidirectional neural/EMG interface with on-chip spike detection for sensorimotor feedback, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 528-531
This paper presents a novel 32-channel bidirectional neural interface, capable of high voltage stimulation and low power, low-noise neural recording. Current-controlled biphasic pulses are output with a voltage compliance of 9.25V, user configurable amplitude (max. 315 uA) & phase duration (max. 2 ms). The low-voltage recording amplifiers consume 23 uW per channel with programmable gain between 225 - 4725. Signals are10-bit sampled at 16 kHz. Data rates are reduced by granular control of active recording channels, spike detection and event-driven communication, and repeatable multi-pulse stimulation configurations.
Leene L, Constandinou TG, 2017, A 2.7uW/Mips, 0.88GOPS/mm^2 Distributed Processor for Implantable Brain Machine Interfaces, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 360-363
This paper presents a scalable architecture in 0.18u m CMOS for implantable brain machine interfaces (BMI) that enables micro controller flexibility for data analysis at the sensor interface. By introducing more generic computational capabilities the system is capable of high level adaptive function to potentially improve the long term efficacy of invasive implants. This topology features a compact ultra low power distributedprocessor that supports 64-channel neural recording system on chip (SOC) with a computational efficiency of 2.7uW/MIPS with a total chip area of 1.37mm2. This configuration executes 1024 instructions on each core at 20MHz to consolidate full spectrum high precision recordings from 4 analogue channels for filtering, spike detection, and feature extraction in the digital domain.
Lauteslager T, Tommer M, Kjelgard KG, et al., 2017, Intracranial Heart Rate Detection Using UWB Radar, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 119-122
Microwave imaging is a promising technique for noninvasive imaging of brain activity. A multistatic array of body coupled antennas and single chip pulsed ultra-wideband radars should be capable of detecting local changes in cerebral blood volume, a known indicator for neural activity. As an initialverification that small changes in the cerebrovascular system can indeed be measured inside the skull, we recorded the heart rate intracranially using a single radar module and two body coupled antennas. The obtained heart rate was found to correspond to ECG measurements. To confirm that the measured signal was indeed from within the skull, we performed simulations to predict the time-of-flight of radar pulses passing through differentanatomical structures of the head. Simulated time-of-flight through the brain corresponded to the measured delay of heart rate modulation in the radar signal. The detection of intracranial heart rate using microwave techniques has not previously been reported, and serves as a first proof that functional neuroimaging using radar could lie within reach.
Frehlick Z, Williams I, Constandinou TG, 2017, Improving Neural Spike Sorting Performance Using Template Enhancement, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 524-527
This paper presents a novel method for improving the performance of template matching in neural spike sorting for similar shaped spikes, without increasing computational complexity. Mean templates for similar shaped spikes are enhanced to emphasise distinguishing features. Template optimisation is based on the variance of sample distributions. Improved spike sorting performance is demonstrated on simulated neural recordings with two and three neuron spike shapes. The method is designed for implementation on a Next Generation Neural Interface (NGNI) device at Imperial College London.
De Marcellis A, Palange E, Nubile L, et al., 2016, A pulsed coding technique based on optical UWB modulation for high data rate low power wireless implantable biotelemetry, Electronics, Vol: 5, Pages: 1-10, ISSN: 2079-9292
This paper reports on a pulsed coding technique based on optical Ultra-wideband (UWB)modulation for wireless implantable biotelemetry systems allowing for high data rate link whilstenabling significant power reduction compared to the state-of-the-art. This optical data codingapproach is suitable for emerging biomedical applications like transcutaneous neural wirelesscommunication systems. The overall architecture implementing this optical modulation techniqueemploys sub-nanosecond pulsed laser as the data transmitter and small sensitive area photodiode asthe data receiver. Moreover, it includes coding and decoding digital systems, biasing and drivinganalogue circuits for laser pulse generation and photodiode signal conditioning. The complete systemhas been implemented on Field-Programmable Gate Array (FPGA) and prototype Printed CircuitBoard (PCB) with discrete off-the-shelf components. By inserting a diffuser between the transmitterand the receiver to emulate skin/tissue, the system is capable to achieve a 128 Mbps data rate with abit error rate less than 10 9 and an estimated total power consumption of about 5 mW correspondingto a power efficiency of 35.9 pJ/bit. These results could allow, for example, the transmission of an800-channel neural recording interface sampled at 16 kHz with 10-bit resolution.
De Marcellis A, Palange E, Faccio M, et al., 2016, A new optical UWB modulation technique for 250Mbps wireless link in implantable biotelemetry systems, Eurosensors, Publisher: Elsevier: Creative Commons Attribution Non-Commercial No-Derivatives License, Pages: 1676-1680, ISSN: 1877-7058
We propose a new UWB modulation technique for wireless optical communications in transcutaneous biotelemetry. The solution, based on the generation of sub-nanoseconds laser pulses, allows for a high data rate link whilst achieving a significant power reduction (energy per bit) compared to the state-ofthe- 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 (lower than 1mm^2 in a 0.18μm technology). These parts, optimised for low-voltage/low-power operation, include coding and decoding digital systems, biasing and driving analogue circuits for laser pulse generation and photodiode signal conditioning. Experimental findings with prototype PCBs have validated the new paradigm showing the system capabilities to achieve a BER less than 10^-9 with data rate up to 250Mbps and estimated total power consumption lower than 5mW.
Zhao H, Dehkhoda F, Ramezani R, et al., 2016, A CMOS-Based Neural Implantable Optrode for Optogenetic Stimulation and Electrical Recording, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 286-289
This paper presents a novel integrated optrode for simultaneous optical stimulation and electrical recording for closed -loop optogenetic neuro-prosthetic applications. The design has been implemented in a commercially available 0.35μm CMOS process. The system includes circuits for controlling the optical stimulations; recording local field potentials (LFPs); and onboard diagnostics. The neural interface has two clusters of stimulation and recording sites. Each stimulation site has a bonding point for connecting a micro light emitting diode (μLED) to deliver light to the targeted area of brain tissue. Each recording site is designed to be post-processed with electrode materials to provide monitoring ofneural activity. On-chip diagnostic sensing has been included to provide real-time diagnostics for post-implantation and during normal operation.
Lauteslager T, Nicolaou N, Lande TS, et al., 2016, Functional neuroimaging Using UWB Impulse Radar: a Feasibility Study, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 406-409
Microwave imaging is a promising new modalityfor studying brain function. In the current paper we assess thefeasibility of using a single chip implementation of an ultra-wideband impulse radar for developing a portable and low-costfunctional neuroimaging device. A numerical model is used topredict the level of attenuation that will occur when detectinga volume of blood in the cerebral cortex. A phantom liquid ismade, to study the radar’s performance at different attenuationlevels. Although the radar is currently capable of detecting apoint reflector in a phantom liquid with submillimeter accuracyand high temporal resolution, object detection at the desired levelof attenuation remains a challenge.
Ramezani R, Dehkhoda F, Soltan A, et al., 2016, An optrode with built-in self-diagnostic and fracture sensor for cortical brain stimulation, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 392-395
This paper proposes a self-diagnostic subsystem for a new generation of brain implants with active electronics. The primary objective of such probes is to deliver optical pulses to optogenetic tissue and record the subsequent activity, but lifetime is currently unknown. Our proposed circuits aim to increase the safety of implanting active electronic probes into human brain tissue. Therefore, prolonging the lifetime of the implant and reducing the risks to the patient. The self-diagnostic circuit will examine the optical emitter against any abnormality or malfunctioning. The fracture sensor examinesthe optrode against any rapture or insertion breakage. The optrode including our diagnostic subsystem and fracture sensor has been designed and successfully simulated at 350nm AMS technology node and sent for manufacture.
Nicolaou N, Constandinou TG, 2016, Phase-Amplitude Coupling during propofol-induced sedation: an exploratory approach, FENS Forum of Neuroscience, Publisher: FENS
Luan S, Williams I, de Carvalho F, et al., 2016, Next Generation Neural Interfaces for low-power multichannel spike sorting, FENS Forum of Neuroscience, Publisher: FENS
Nicolaou N, Constandinou TG, 2016, A nonlinear causality estimator based on Non-Parametric Multiplicative Regression, Frontiers in Neuroinformatics, Vol: 10, ISSN: 1662-5196
Causal prediction has become a popular tool for neuroscience applications, as it allows the study of relationships between different brain areas during rest, cognitive tasks or brain disorders. We propose a nonparametric approach for the estimation of nonlinear causal prediction for multivariate time series. In the proposed estimator, C-NPMR, Autoregressive modelling is replaced by Nonparametric Multiplicative Regression (NPMR). NPMR quantifies interactions between a response variable (effect) and a set of predictor variables (cause); here, we modified NPMR for model prediction. We also demonstrate how a particular measure, the sensitivity Q, could be used to reveal the structure of the underlying causal relationships. We apply C-NPMR on artificial data with known ground truth (5 datasets), as well as physiological data (2 datasets). C-NPMR correctly identifies both linear and nonlinear causal connections that are present in the artificial data, as well as physiologically relevant connectivity in the real data, and does not seem to be affected by filtering. The Sensitivity measure also provides useful information about the latent connectivity.The proposed estimator addresses many of the limitations of linear Granger causality and other nonlinear causality estimators. C-NPMR is compared with pairwise and conditional Granger causality (linear) and Kernel-Granger causality (nonlinear). The proposed estimator can be applied to pairwise or multivariate estimations without any modifications to the main method. Its nonpametric nature, its ability to capture nonlinear relationships and its robustness to filtering make it appealing for a number of applications.
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.
Elia M, Leene L, Constandinou TG, 2016, Continuous-Time Micropower Interface for Neural Recording Applications, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 534-637
This paper presents a novel amplifier architectureintended for low power neural recording applications. By usingcontinuous-time signal representation, the proposed topologypredominantly leverages digital topologies taking advantage ofefficient techniques used in time domain systems. This includeshigher order feedback dynamics that allow direct analoguesignal quantization and near ideal integrator structures for noiseshaping. The system implemented in 0.18 μ m standard CMOSdemonstrates the capability for low noise instrumentation witha bandwidth of 6 kHz and highly linear full dynamic range.Simulation results indicate 1.145 μW budget from 0.5 V supplyvoltage with an input referred thermal noise of 7.7 μVrms.
Barsakcioglu DY, Constandinou TG, 2016, A 32-Channel MCU-Based Feature Extraction and Classification for Scalable on-Node Spike Sorting, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 1310-1313
This paper describes a new hardware-efficientmethod and implementation for neural spike sorting basedon selection of a channel-specific near-optimal subset of fea-tures given a larger predefined set. For each channel, real-time classification is achieved using a simple decision matrixthat considers the features that provide the highest separabilitydetermined through off-line training. A 32-channel system for on-line feature extraction and classification has been implementedin an ARM Cortex-M0+ processor. Measured results of thehardware platform consumes 268 W per channel during spikesorting (includes detection). The proposed method provides atleast x10 reduction in computational requirements compared toliterature, while achieving an average classification error of lessthan 10% across wide range of datasets and noise levels.
Woods S, Constandinou TG, 2016, A compact targeted drug delivery mechanism for a next generation wireless capsule endoscope, Journal of Micro-Bio Robotics, Vol: 11, Pages: 19-34, ISSN: 2194-6426
This paper reports a novel medication release and delivery mechanism as part of a next generation wireless capsule endoscope (WCE) for targeted drug delivery. This subsystem occupies a volume of only 17.9mm3 for the purpose of delivering a 1 ml payload to a target site of interest in the small intestinal tract. An in-depth analysis of the method employed to release and deliver the medication is described and a series of experiments is presented which validates the drug delivery system. The results show that a variable pitch conical compression spring manufactured from stainless steel can deliver 0.59 N when it is fully compressed and that this would be sufficient force to deliver the onboard medication.
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.
Guven O, Eftekhar A, Kindt W, et al., 2016, Computationally-efficient realtime interpolation algorithm for non-uniform sampled biosignals, Healthcare Technology Letters, Vol: 3, Pages: 105-110, ISSN: 2053-3713
This letter presents a novel, computationally-efficient interpolation method that has been optimised for use in ECG baseline drift removal. In our previous work 3 isoelectric baseline points per heart beat are detected, and here utilised as interpolation points. As an extension from linear interpolation, our algorithm segments the interpolation interval and utilises different piecewise linear equations. Thus the algorithm produces a linear curvature that is computationally efficient while avoiding overshoots on nonuniform samples. The proposed algorithm is tested using sinusoids with different fundamental frequencies from 0.05Hz to 0.7Hz and also validated with real baseline wander data acquired from the MIT-BIH Noise Stress Database. The synthetic data results show an RMS error of 0.9μV (mean), 0.63μV (median) and 0.6μV (std. dev.) per heart beat on a 1mVp-p 0.1Hz sinusoid. On real data we obtain an RMS error of 10.9μV (mean), 8.5μV (median) and 9.0μV (std. dev.) per heart beat. Cubic spline interpolation and linear interpolation on the other hand shows 10.7μV, 11.6μV (mean), 7.8μV, 8.9μV(median) and 9.8μV, 9.3μV (std. dev.) per heart beat respectively.
Dehkhoda F, Soltan A, Ramezani R, et 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.
Williams I, Luan S, Jackson A, et 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.
De Marcellis A, Palange E, Liberatore V, et 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.
Jackson A, Constandinou TG, Eftekhar A, et al., 2015, System for a Brain-Computer Interface
Rapeaux A, Nikolic K, Williams I, et 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.
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.
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