ORCID Profile
0000-0003-2630-7011
Current Organisations
University of Technology Sydney
,
Cuvos
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Electrical and Electronic Engineering | Microelectronics and Integrated Circuits | Integrated Circuits | Performing Arts and Creative Writing | Biosensor Technologies | Creative Arts, Media and Communication Curriculum and Pedagogy | Communications Technologies Not Elsewhere Classified | Sensory Processes, Perception and Performance | Music Composition | Nanoscale Characterisation | Nanoelectronics
ANZSRC Socio-Economic Objective (SEO)
Expanding Knowledge in Engineering | Teaching and Instruction Technologies | Expanding Knowledge through Studies of the Creative Arts and Writing | Integrated Circuits and Devices | Music | Integrated circuits and devices | Expanding Knowledge in Technology |
Related Links
Publications
A Reconfigurable Mixed-signal Implementation of a Neuromorphic ADC
Publisher: arXiv
Date: 2015
A 9-independent-leads ECG system from 10 electrodes: A practice preserving WCT-less true unipolar ECG system
Publisher: IEEE
Date: 10-2015
A comparison of interval methods in symbolic circuit analysis applications
Publisher: Australian Mathematical Publishing Association, Inc.
Date: 16-01-2012
A compact aVLSI conductance-based silicon neuron
Publisher: arXiv
Date: 2015
On the fluid-structure interaction in the cochlea
Publisher: Acoustical Society of America (ASA)
Date: 07-2014
DOI: 10.1121/1.4883382
Abstract: The cochlea is known to be a nonlinear system that shows strong fluid-structure coupling. In this work, the monolithic state space approach to cochlear modeling [Rapson et al., J. Acoust. Soc. Am. 131, 3925–3952 (2012)] is used to study the inherent nature of this coupling. Mathematical derivations requiring minimal, widely accepted assumptions about cochlear anatomy provide a clear description of the coupling. In particular, the coupling forces between neighboring cochlear partition segments are demonstrated, with implications for theories of cochlear operation that discount the traveling wave hypothesis. The derivations also reaffirm the importance of selecting a physiologically accurate value for the partition mass in any simulation. Numerical results show that considering the fluid properties in isolation can give a misleading impression of the fluid-structure coupling. Linearization of a nonlinear partition model allows the relationship between the linear and nonlinear fluid-structure interaction to be described. Furthermore, the effect of different classes of nonlinearities on the numerical complexity of a cochlear model is assessed. Cochlear models that assume outer hair cells are able to detect pressure will require implicit solver strategies, should the pressure sensitivity be demonstrated. Classical cochlear models in general do not require implicit solver strategies.
A W-Band SPDT Switch With 15-dBm P1dB in 55-nm Bulk CMOS
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Electronically programmable test points for on-chip analog/digital measurements
Publisher: IEEE
Date: 05-2013
A novel method for non-invasive respiration monitoring
Publisher: IEEE
Date: 08-2015
Silicon Cochlea Building Blocks
Publisher: Wiley
Date: 26-12-2014
Electrodeless FSR Linear Envelope Signal for Muscle Contraction Measurement
Publisher: IEEE
Date: 11-2019
Instantaneous VO2 from a wearable device
Publisher: Elsevier BV
Date: 02-2018
DOI: 10.1016/J.MEDENGPHY.2017.12.008
Abstract: We present a method for calculating instantaneous oxygen uptake (VO2) through the use of a non-invasive and non-obtrusive (i.e. without a face mask) wearable device, together with its clinical evaluation against a standard technique based upon expired gas calorimetry. This method can be integrated with existing wearable devices, we implemented it in the "Device for Reliable Energy Expenditure Monitoring" (DREEM). The DREEM comprises a single lead electrocardiogram (ECG) device combined with a tri-axial accelerometer and is worn around the waist. Our clinical evaluation tests the developed method against a gold standard for VO2, expired gas calorimetry, using an ethically approved protocol comprising active exercise and sedentary periods. The study was performed on 42 participants from a wide s le population including healthy people, athletes and an at-risk health group including persons affected by obesity. We developed an algorithm combining heart rate (HR) and the integral of absolute acceleration (IAA), with results showing a correlation of r = 0.93 for instantaneous VO2, and r = 0.97 for 3 min mean VO2, this is a considerably improved estimation of VO2 in comparison to methods utilising HR and IAA independently.
Delay learning architectures for memory and classification
Publisher: Elsevier BV
Date: 08-2014
Energy-efficient ferroelectric field-effect transistor-based oscillators for neuromorphic system design
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2020
Turn Down that Noise: Synaptic Encoding of Afferent SNR in a Single Spiking Neuron
Publisher: arXiv
Date: 2014
A Trainable Neuromorphic Integrated Circuit that Exploits Device Mismatch
Publisher: arXiv
Date: 2015
Automatic tuning of digitally-controllable positive-feedback OTAs in continuous-time sigma–delta modulators
Publisher: Springer Science and Business Media LLC
Date: 30-07-2016
A reconfigurable dual-output buck-boost switched-capacitor converter using adaptive gain and discrete frequency scaling control
Publisher: Elsevier BV
Date: 03-2018
The novel SCR-based ESD protection device with high holding voltage
Publisher: IEEE
Date: 05-2009
Integrated circuits towards reducing e-waste: Future design directions
Publisher: IEEE
Date: 06-2010
Emergence of competitive control in a memristor-based neuromorphic circuit
Publisher: IEEE
Date: 06-0011
Delay Learning Architectures for Memory and Classification
Publisher: arXiv
Date: 2013
An analysis of matching in the Tau cell log-domain filter
Publisher: IEEE
Date: 2006
FPGA implementation of the CAR Model of the cochlea
Publisher: IEEE
Date: 06-2014
Neuromorphic Silicon Neuron Circuits
Publisher: Frontiers Media SA
Date: 2011
An FPGA Implementation of a Polychronous Spiking Neural Network with Delay Adaptation
Publisher: Frontiers Media SA
Date: 2013
Towards a Low-Power, Minimally-Invasive Nerve Regeneration
Publisher: IEEE
Date: 11-2019
Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation
Publisher: MDPI AG
Date: 22-10-2019
DOI: 10.3390/S19204596
Abstract: Upper limb utation is a condition that significantly restricts the utees from performing their daily activities. The myoelectric prosthesis, using signals from residual stump muscles, is aimed at restoring the function of such lost limbs seamlessly. Unfortunately, the acquisition and use of such myosignals are cumbersome and complicated. Furthermore, once acquired, it usually requires heavy computational power to turn it into a user control signal. Its transition to a practical prosthesis solution is still being challenged by various factors particularly those related to the fact that each utee has different mobility, muscle contraction forces, limb positional variations and electrode placements. Thus, a solution that can adapt or otherwise tailor itself to each in idual is required for maximum utility across utees. Modified machine learning schemes for pattern recognition have the potential to significantly reduce the factors (movement of users and contraction of the muscle) affecting the traditional electromyography (EMG)-pattern recognition methods. Although recent developments of intelligent pattern recognition techniques could discriminate multiple degrees of freedom with high-level accuracy, their efficiency level was less accessible and revealed in real-world ( utee) applications. This review paper examined the suitability of upper limb prosthesis (ULP) inventions in the healthcare sector from their technical control perspective. More focus was given to the review of real-world applications and the use of pattern recognition control on utees. We first reviewed the overall structure of pattern recognition schemes for myo-control prosthetic systems and then discussed their real-time use on utee upper limbs. Finally, we concluded the paper with a discussion of the existing challenges and future research recommendations.
Investigating the implications of outer hair cell connectivity using a silicon cochlea
Publisher: IEEE
Date: 05-2010
DELTRON: Neuromorphic architectures for delay based learning
Publisher: IEEE
Date: 12-2012
Proceedings of the 11th Engineering Mathematics and Applications Conference
Publisher: Australian Mathematical Publishing Association, Inc.
Date: 17-06-2014
An Online Learning Algorithm for Neuromorphic Hardware Implementation
Publisher: arXiv
Date: 2015
A compact aVLSI conductance-based silicon neuron
Publisher: IEEE
Date: 05-2015
A log-domain implementation of the Izhikevich neuron model
Publisher: IEEE
Date: 05-2010
A compact reconfigurable mixed-signal implementation of synaptic plasticity in spiking neurons
Publisher: IEEE
Date: 06-2014
A neuromorphic hardware architecture using the Neural Engineering Framework for pattern recognition
Publisher: arXiv
Date: 2015
A 0.04 mm2 Buck-Boost DC-DC Converter for Biomedical Implants Using Adaptive Gain and Discrete Frequency Scaling Control
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2016
A Spiking Neural Network Based Auto-encoder for Anomaly Detection in Streaming Data
Publisher: IEEE
Date: 12-2020
A log-domain implementation of the Mihalas-Niebur neuron model
Publisher: IEEE
Date: 05-2010
Concept design for a 1-lead wearable/implantable ECG front-end: Power management
Publisher: MDPI AG
Date: 19-11-2015
DOI: 10.3390/S151129297
An analogue VLSI implementation of polychronous spiking neural networks
Publisher: IEEE
Date: 12-2011
Subthreshold operation of Nauta's operational transconductance amplifier
Publisher: IEEE
Date: 06-2015
Embedded implementation of a random feature detecting network for real-time classification of time-of-flight SPAD array recordings
Publisher: SPIE
Date: 02-05-2019
DOI: 10.1117/12.2517875
A method for measuring switching frequency using complex asynchronous logic circuits
Publisher: IEEE
Date: 12-2012
A Statistical Design Approach for a Digitally Programmable Mismatch-Tolerant High-Speed Nauta Structure Differential OTA in 65-nm CMOS
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2016
Fully Open-Access Passive Dry Electrodes BIOADC: Open-Electroencephalography (EEG) Re-Invented
Publisher: MDPI AG
Date: 13-02-2019
DOI: 10.3390/S19040772
Abstract: The Open-electroencephalography (EEG) framework is a popular platform to enable EEG measurements and general purposes Brain Computer Interface experimentations. However, the current platform is limited by the number of available channels and electrode compatibility. In this paper we present a fully configurable platform with up to 32 EEG channels and compatibility with virtually any kind of passive electrodes including textile, rubber and contactless electrodes. Together with the full hardware details, results and performance on a single volunteer participant (limited to alpha wave elicitation), we present the brain computer interface (BCI)2000 EEG source driver together with source code as well as the compiled (.exe). In addition, all the necessary device firmware, gerbers and bill of materials for the full reproducibility of the presented hardware is included. Furthermore, the end user can vary the dry-electrode reference circuitry, circuit bandwidth as well as s le rate to adapt the device to other generalized biopotential measurements. Although, not implemented in the tested prototype, the Biomedical Analogue to Digital Converter BIOADC naturally supports SPI communication for an additional 32 channels including the gain controller. In the appendix we describe the necessary modification to the presented hardware to enable this function.
Silicon Modeling of the Mihalaş–Niebur Neuron
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2011
A reconfigurable buck-boost switched capacitor converter with adaptive gain and discrete frequency scaling control
Publisher: IEEE
Date: 12-2012
Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels
Publisher: Frontiers Media SA
Date: 25-11-2014
A silicon model of the inner hair cell
Publisher: IEEE
Date: 12-2011
A 2-D cochlea with Hopf oscillators
Publisher: IEEE
Date: 11-2007
A cell impedance sensor based on a silicon cochlea
Publisher: IEEE
Date: 11-2009
A CMOS switched capacitor implementation of the Mihalas-Niebur neuron
Publisher: IEEE
Date: 11-2009
A resistive DAC for a multi-stage sigma-delta modulator DAC with dynamic element matching
Publisher: Springer Science and Business Media LLC
Date: 25-06-2018
Nauta OTA in a second-order continuous-time delta-sigma modulator
Publisher: IEEE
Date: 08-2014
A low power neural recording amplifier with programmable gain and bandwidth
Publisher: IEEE
Date: 05-2012
Synthesis of neural networks for spatio-temporal spike pattern recognition and processing
Publisher: Frontiers Media SA
Date: 2013
Opportunities for Electroceuticals in Epilepsy
Publisher: Elsevier BV
Date: 10-2019
DOI: 10.1016/J.TIPS.2019.08.001
Abstract: Epilepsy is a neurological disorder that affects ∼1% of the world population. Nearly 30% of epilepsy patients suffer from pharmacoresistant epilepsy that cannot be treated with antiepileptic drugs. Depending on seizure type, a erse range of therapies are available, including surgery, vagus nerve stimulation, and deep brain stimulation. We review the sensing and stimulation technologies most used in neurological disorders, and provide a vision of minimally invasive electroceuticals to enable accurate forecasting of epileptic seizures and therapy. The use of such systems could potentially help patients to prevent injuries and, in combination with an intervention mechanism, could provide a method of suppressing seizures in epileptic patients.
The effect of source resistance on the linearity of Nauta structure OTA
Publisher: IEEE
Date: 08-2017
Small signal model and analog performance analysis of negative capacitance FETs
Publisher: Elsevier BV
Date: 12-2021
Rotationally invariant vision recognition with neuromorphic transformation and learning networks
Publisher: IEEE
Date: 06-2014
Efficient FPGA Implementations of Pair and Triplet-Based STDP for Neuromorphic Architectures
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Bayesian estimation and inference using stochastic electronics
Publisher: Frontiers Media SA
Date: 18-03-2016
Unsupervised Feature Vector Clustering Using Temporally Coded Spiking Networks
Publisher: IEEE
Date: 18-06-2023
Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Live demonstration: The self-tuned regenerative electromechanical parametric amplifier
Publisher: IEEE
Date: 05-2010
Invasion of the alveolar-capillary barrier byAspergillusspp.: therapeutic and diagnostic implications for immunocompromised patients with invasive pulmonary aspergillosis
Publisher: Oxford University Press (OUP)
Date: 2009
DOI: 10.1080/13693780802510232
Abstract: Aspergillus spp. are leading causes of morbidity and mortality in immunocompromised patients. This review provides an overview of host defenses, the mechanisms by which the alveolar-capillary barrier is breeched by Aspergillus, and the implications for diagnosis and treatment of patients with invasive pulmonary aspergillosis.
A 0.3mm2 10-b 100MS/s pipelined ADC using Nauta structure op-amps in 180nm CMOS
Publisher: IEEE
Date: 05-2013
A Stochastic Approach to STDP
Publisher: IEEE
Date: 05-2016
Analysis and design considerations of systematic nonlinearity for sigma-delta current-steering DAC
Publisher: IEEE
Date: 04-2013
The Self-Tuned Regenerative Electromechanical Parametric Amplifier: A Model for Active Amplification in the Cochlea
Publisher: IEEE
Date: 05-2010
The Synaptic Kernel Adaptation Network
Publisher: IEEE
Date: 06-2014
A Biologically Inspired Sound Localisation System Using a Silicon Cochlea Pair
Publisher: MDPI AG
Date: 08-02-2021
DOI: 10.3390/APP11041519
Abstract: We present a biologically inspired sound localisation system for reverberant environments using the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC) cochlear model. The system exploits a CAR-FAC pair to pre-process binaural signals that travel through the inherent delay line of the cascade structures, as each filter acts as a delay unit. Following the filtering, each cochlear channel is cross-correlated with all the channels of the other cochlea using a quantised instantaneous correlation function to form a 2-D instantaneous correlation matrix (correlogram). The correlogram contains both interaural time difference and spectral information. The generated correlograms are analysed using a regression neural network for localisation. We investigate the effect of the CAR-FAC nonlinearity on the system performance by comparing it with a CAR only version. To verify that the CAR/CAR-FAC and the quantised instantaneous correlation provide a suitable basis with which to perform sound localisation tasks, a linear regression, an extreme learning machine, and a convolutional neural network are trained to learn the azimuthal angle of the sound source from the correlogram. The system is evaluated using speech data recorded in a reverberant environment. We compare the performance of the linear CAR and nonlinear CAR-FAC models with current sound localisation systems as well as with human performance.
Reusable Power Supply ICs for E-Waste Reduction in Mobile Consumer Electronics
Publisher: Global Science and Technology Forum
Date: 25-10-2010
A new biomarker for closed-loop deep brain stimulation in the subthalamic nucleus for patients with Parkinson's disease
Publisher: IEEE
Date: 10-2014
Live demonstration: FPGA implementation of the CAR model of the cochlea
Publisher: IEEE
Date: 06-2014
A Stochastic Approach to STDP
Publisher: arXiv
Date: 2016
Proceedings of the Engineering Mathematics and Applications Conference
Publisher: Australian Mathematical Publishing Association, Inc.
Date: 23-01-2012
A new biomarker for subthalamic deep brain stimulation for patients with advanced Parkinson’s disease—a pilot study
Publisher: IOP Publishing
Date: 15-10-2015
DOI: 10.1088/1741-2560/12/6/066013
Abstract: Deep brain stimulation (DBS) has become the standard treatment for advanced stages of Parkinson's disease (PD) and other motor disorders. Although the surgical procedure has improved in accuracy over the years thanks to imaging and microelectrode recordings, the underlying principles that render DBS effective are still debated today. The aim of this paper is to present initial findings around a new biomarker that is capable of assessing the efficacy of DBS treatment for PD which could be used both as a research tool, as well as in the context of a closed-loop stimulator. We have used a novel multi-channel stimulator and recording device capable of measuring the response of nervous tissue to stimulation very close to the stimulus site with minimal latency, rejecting most of the stimulus artefact usually found with commercial devices. We have recorded and analyzed the responses obtained intraoperatively in two patients undergoing DBS surgery in the subthalamic nucleus (STN) for advanced PD. We have identified a biomarker in the responses of the STN to DBS. The responses can be analyzed in two parts, an initial evoked compound action potential arising directly after the stimulus onset, and late responses (LRs), taking the form of positive peaks, that follow the initial response. We have observed a morphological change in the LRs coinciding with a decrease in the rigidity of the patients. These initial results could lead to a better characterization of the DBS therapy, and the design of adaptive DBS algorithms that could significantly improve existing therapies and help us gain insights into the functioning of the basal ganglia and DBS.
Microelectronic 3D Imaging and Neuromorphic Recognition for Autonomous UAVs
Publisher: Springer Netherlands
Date: 2020
A 2-D silicon cochlea with an improved automatic quality factor control-loop
Publisher: IEEE
Date: 05-2008
Self-tuned regenerative amplification and the Hopf bifurcation
Publisher: IEEE
Date: 05-2008
A Silicon Neuron-based Bio-Front-End for Ultra Low Power Bio-Monitoring at the Edge
Publisher: IEEE
Date: 12-2020
Design strategy for enhanced output impedance current-steering DAC in sigma-delta converters
Publisher: IEEE
Date: 08-2013
Live Demonstration: Unsupervised Character Recognition with a FPGA Neuromorphic System
Publisher: IEEE
Date: 05-2018
CAR-Lite: A Multi-Rate Cochlea Model on FPGA
Publisher: IEEE
Date: 2018
An FPGA design framework for large-scale spiking neural networks
Publisher: IEEE
Date: 06-2014
A 1.2V 2-bit phase interpolator for 65nm CMOS
Publisher: IEEE
Date: 05-2012
A generalised conductance-based silicon neuron for large-scale spiking neural networks
Publisher: IEEE
Date: 06-2014
A digital to transconductance converter for nauta structure op-amps in 65nm CMOS
Publisher: IEEE
Date: 08-2014
Making a Spiking Net Work: Robust brain-like unsupervised machine learning
Publisher: arXiv
Date: 2022
Techniques for measuring energy expenditure with portable devices
Publisher: IEEE
Date: 04-2013
Event-Based Processing of Single Photon Avalanche Diode Sensors
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-07-2020
Live Demo: Affine arithmetic concept based Symbolic Circuit Analyser
Publisher: IEEE
Date: 05-2010
A 90-GHz Asymmetrical Single-Pole Double-Throw Switch With >19.5-dBm 1-dB Compression Point in Transmission Mode Using 55-nm Bulk CMOS Technology
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2021
A compact neural core for digital implementation of the Neural Engineering Framework
Publisher: IEEE
Date: 10-2014
Measuring the impedance of a tethered bilayer membrane biosensor
Publisher: IEEE
Date: 2008
Symbolic analysis of the Tau Cell log-domain filter using affine MOSFET models
Publisher: IEEE
Date: 12-2010
Silicon Implementation of the Generalized Integrate-and-Fire Neuron Model
Publisher: IEEE
Date: 12-2011
Investigation of event-based surfaces for high-speed detection, unsupervised feature extraction, and object recognition
Publisher: Frontiers Media SA
Date: 17-01-2019
The Ripple Pond: Enabling Spiking Networks to See
Publisher: arXiv
Date: 2013
Ultra compact and linear 4-bit digital-to-analog converter in 22nm FDSOI technology
Publisher: IEEE
Date: 28-05-2022
Hybrid dual-mode low voltage dropout regulator with infinite impulse response digital filters
Publisher: IEEE
Date: 02-2016
The ripple pond: Enabling spiking networks to see
Publisher: Frontiers Media SA
Date: 2013
A FPGA implementation of the CAR-FAC cochlear model
Publisher: Frontiers Media SA
Date: 10-04-2018
Compact and Energy Efficient Neuron With Tunable Spiking Frequency in 22-nm FDSOI
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 28-07-2021
DOI: 10.36227/TECHRXIV.15042639
Abstract: In this paper, we present an integrated and fire neuron designed in a 22-nm FDSOI technology. In this novel design, we deploy the back-gate terminal of FDSOI technology for a tunable design. For the first time, we show analytically and with pre- and post-layout simulations a neuron with tunable spiking frequency using the back-gate voltage of FDSOI technology. The neuron circuit is designed in the sub- hreshold region and dissipates an ultra-low energy per spike of the order of Femto Joules per spike. With the layout area of only 30 um2, this is the smallest neuron circuit reported to date. /
Open platform, eight-channel, portable bio-potential and activity data logger for wearable medical device development
Publisher: Institution of Engineering and Technology (IET)
Date: 10-2015
DOI: 10.1049/EL.2015.2764
A statistical design approach using fixed and variable width transconductors for positive-feedback gain-enhancement OTAs
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2017
Frequency behaviour of FEFET-based ultra-low-power coupled oscillator neurons
Publisher: IEEE
Date: 10-2020
The best of both worlds
Publisher: Springer Science and Business Media LLC
Date: 11-03-2021
Compact and Energy Efficient Neuron With Tunable Spiking Frequency in 22-nm FDSOI
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
An improved aVLSI axon with programmable delay using spike timing dependent delay plasticity
Publisher: IEEE
Date: 05-2013
Neuromorphic Cytometry: Implementation on cell counting and size estimation
Publisher: Cold Spring Harbor Laboratory
Date: 07-07-2023
DOI: 10.1101/2023.07.06.548044
Abstract: Flow cytometry is a widespread and high-throughput technology that can measure the features of cells and can be combined with fluorescence analysis for additional phenotypical characterisations but only provide low-dimensional output and spatial resolution. Imaging flow cytometry is another technology that offers rich spatial information, allowing more profound insight into single-cell analysis. However, offering such high-resolution, full-frame feedback can compromise speed and has become a significant trade-off challenge to tackle during development. In addition, the current dynamic range offered by conventional photosensors can only capture limited fluorescence signals, exacerbating the difficulties in elevating performance speed. Neuromorphic photo-sensing architecture focuses on the events of interest via in idual-firing pixels to reduce data redundancy and provide low latency in data processing. With the inherent high dynamic range, this architecture has the potential to drastically elevate the performance in throughput by incorporating motion-activated spatial resolution. Herein, we presented an early demonstration of neuromorphic cytometry with the implementation of object counting and size estimation to measure 8 μ m and 15 μ m polystyrene-based microparticles and human monocytic cell line (THP-1). In this work, our platform has achieved highly consistent outputs with a widely adopted flow cytometer (CytoFLEX) in detecting the total number and size of the microparticles. Although the current platform cannot deliver multiparametric measurements on cells, future endeavours will include further functionalities and increase the measurement parameters (granularity, cell condition, fluorescence analysis) to enrich cell interpretation.
Event-based Processing of Single Photon Avalanche Diode Sensors
Publisher: arXiv
Date: 2020
Stochastic electronics: A neuro-inspired design paradigm for integrated circuits
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2014
Compact and Energy Efficient Neuron With Tunable Spiking Frequency in 22-nm FDSOI
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 28-07-2021
DOI: 10.36227/TECHRXIV.15042639.V1
Abstract: In this paper, we present an integrated and fire neuron designed in a 22-nm FDSOI technology. In this novel design, we deploy the back-gate terminal of FDSOI technology for a tunable design. For the first time, we show analytically and with pre- and post-layout simulations a neuron with tunable spiking frequency using the back-gate voltage of FDSOI technology. The neuron circuit is designed in the sub- hreshold region and dissipates an ultra-low energy per spike of the order of Femto Joules per spike. With the layout area of only 30 um2, this is the smallest neuron circuit reported to date. /
A modified MOSFET small-signal model based on affine arithmetic concepts
Publisher: IEEE
Date: 11-2009
A neuromorphic hardware framework based on population coding
Publisher: IEEE
Date: 07-2015
A reconfigurable buck-boost switched capacitor converter architecture for multiple, distributed on-chip load applications
Publisher: IEEE
Date: 06-2014
Unsupervised Character Recognition with a Simplified FPGA Neuromorphic System
Publisher: IEEE
Date: 05-2018
Investigation of event-based memory surfaces for high-speed tracking, unsupervised feature extraction and object recognition
Publisher: arXiv
Date: 2016
Turn Down That Noise: Synaptic Encoding of Afferent SNR in a Single Spiking Neuron.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2015
Synthesis of neural networks for spatio-temporal spike pattern recognition and processing
Publisher: arXiv
Date: 2013
An aVLSI programmable axonal delay circuit with spike timing dependent delay adaptation
Publisher: IEEE
Date: 05-2012
Calibration of the Nauta structure differential OTA
Publisher: IEEE
Date: 11-2014
A synchronous buck-boost converter on a Silicon-On-Sapphire 0.5µm process
Publisher: IEEE
Date: 12-2012
Silicon Models of the Auditory Pathway
Publisher: Springer US
Date: 2010
Circuit performance analysis of analog RF LNA designed with negative capacitance FET
Publisher: IEEE
Date: 28-11-2021
A Basilar Membrane Resonator for an Active 2-D Cochlea
Publisher: IEEE
Date: 05-2007
Wearable Bluetooth Triage Healthcare Monitoring System
Publisher: MDPI AG
Date: 15-11-2021
DOI: 10.3390/S21227586
Abstract: Triage is the first interaction between a patient and a nurse aramedic. This assessment, usually performed at Emergency departments, is a highly dynamic process and there are international grading systems that according to the patient condition initiate the patient journey. Triage requires an initial rapid assessment followed by routine checks of the patients’ vitals, including respiratory rate, temperature, and pulse rate. Ideally, these checks should be performed continuously and remotely to reduce the workload on triage nurses optimizing tools and monitoring systems can be introduced and include a wearable patient monitoring system that is not at the expense of the patient’s comfort and can be remotely monitored through wireless connectivity. In this study, we assessed the suitability of a small ceramic piezoelectric disk submerged in a skin-safe silicone dome that enhances contact with skin, to detect wirelessly both respiration and cardiac events at several positions on the human body. For the purposes of this evaluation, we fitted the sensor with a respiratory belt as well as a single lead ECG, all acquired simultaneously. To complete Triage parameter collection, we also included a medical-grade contact thermometer. Performances of cardiac and respiratory events detection were assessed. The instantaneous heart and respiratory rates provided by the proposed sensor, the ECG and the respiratory belt were compared via statistical analyses. In all considered sensor positions, very high performances were achieved for the detection of both cardiac and respiratory events, except for the wrist, which provided lower performances for respiratory rates. These promising yet preliminary results suggest the proposed wireless sensor could be used as a wearable, hands-free monitoring device for triage assessment within emergency departments. Further tests are foreseen to assess sensor performances in real operating environments.
A mixed-signal implementation of a polychronous spiking neural network with delay adaptation
Publisher: Frontiers Media SA
Date: 18-03-2014
A reconfigurable mixed-signal implementation of a neuromorphic ADC
Publisher: IEEE
Date: 10-2015
An Analogue Neuromorphic Co-Processor That Utilizes Device Mismatch for Learning Applications
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2018
Understanding the mathematics of hearing using electronic circuits
Publisher: Australian Mathematical Publishing Association, Inc.
Date: 17-06-2010
Racing to Learn: Statistical Inference and Learning in a Single Spiking Neuron with Adaptive Kernels
Publisher: arXiv
Date: 2014
A Low Power Trainable Neuromorphic Integrated Circuit That Is Tolerant to Device Mismatch
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2016
A switched capacitor implementation of the generalized linear integrate-and-fire neuron
Publisher: IEEE
Date: 05-2009
An Active 2-D Silicon Cochlea
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2008
Neuromorphic Object Tracking Architecture, Based on Compound Eyes, and Implementation on FPGA
Publisher: IEEE
Date: 08-2018
Teaching Mathematics with Music: A Pilot Study
Publisher: IEEE
Date: 12-2019
A neuromorphic cross-correlation chip
Publisher: IEEE
Date: 05-2011
A Machine Hearing System for Binaural Sound Localization based on Instantaneous Correlation
Publisher: IEEE
Date: 2018
Analogue VLSI implementations of two dimensional, nonlinear, active cochlea models
Publisher: IEEE
Date: 2008
A binaural sound localization system using deep convolutional neural networks
Publisher: IEEE
Date: 05-2019
Neuromorphic Cytometry: Implementation on cell counting and size estimation
Publisher: IOP Publishing
Date: 20-10-0020
Related Organisations
Related Funding Activities
Linkage Projects - Grant ID: LP180100697
Start Date: 10-2019
End Date: 10-2024
Amount: $335,250.00
Funder: Australian Research Council
View Funded ActivityDiscovery Projects - Grant ID: DP0986025
Start Date: 2009
End Date: 02-2013
Amount: $305,000.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP100200275
Start Date: 07-2010
End Date: 07-2015
Amount: $160,014.00
Funder: Australian Research Council
View Funded ActivityDiscovery Projects - Grant ID: DP180100504
Start Date: 06-2018
End Date: 05-2021
Amount: $402,984.00
Funder: Australian Research Council
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