Imperial College London

DrAdrienRapeaux

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Research Associate
 
 
 
//

Contact

 

adrien.rapeaux13 Website

 
 
//

Location

 

B422Bessemer BuildingSouth Kensington Campus

//

Summary

 

Publications

Publication Type
Year
to

23 results found

Rapeaux A, Syed O, Cuttaz E, Chapman C, Green R, Constandinou Tet al., 2022, Preparation of rat sciatic nerve for ex vivo neurophysiology, Jove-Journal of Visualized Experiments, Vol: 185, Pages: 1-14, ISSN: 1940-087X

Ex vivo preparations enable the study of many neurophysiological processes in isolation from the rest of the body while preserving local tissue structure. This work describes the preparation of rat sciatic nerves for ex vivo neurophysiology, including buffer preparation, animal procedures, equipment setup and neurophysiological recording. This work provides an overview of the different types of experiments possible with this method. The outlined method aims to provide 6 h of stimulation and recording on extracted peripheral nerve tissue in tightly controlled conditions for optimal consistency in results. Results obtained using this method are A-fibre compound action potentials (CAP) with peak-to-peak amplitudes in the millivolt range over the entire duration of the experiment. CAP amplitudes and shapes are consistent and reliable, making them useful to test and compare new electrodes to existing models, or the effects of interventions on the tissue, such as the use of chemicals, surgical alterations, or neuromodulatory stimulation techniques. Both conventional commercially available cuff electrodes with platinum-iridium contacts and custom-made conductive elastomer electrodes were tested and gave similar results in terms of nerve stimulus strength-duration response.

Journal article

Teversham J, Wong SS, Hsieh B, Rapeaux A, Troiani F, Savolainen O, Zhang Z, Maslik M, Constandinou TGet al., 2022, Development of an Ultra Low-Cost SSVEP-based BCI Device for Real-Time On-Device Decoding

<jats:title>Abstract</jats:title><jats:p>This study details the development of a novel, approx. £20 electroencephalogram (EEG)-based brain-computer interface (BCI) intended to offer a financially and operationally accessible device that can be deployed on a mass scale to facilitate education and public engagement in the domain of EEG sensing and neurotechnologies. Real-time decoding of steady-state visual evoked potentials (SSVEPs) is achieved using variations of the widely-used canonical correlation analysis (CCA) algorithm: multi-set CCA and generalised CCA. All BCI functionality is executed on board an inexpensive ESP32 microcontroller. SSVEP decoding accuracy of 95.56 ± 3.74% with an ITR of 102 bits/min was achieved with modest calibration.</jats:p>

Journal article

Rapeaux AB, Constandinou TG, 2021, Implantable brain machine interfaces: first-in-human studies, technology challenges and trends, CURRENT OPINION IN BIOTECHNOLOGY, Vol: 72, Pages: 102-111, ISSN: 0958-1669

Journal article

Chen Z, Bannon A, Rapeaux A, Constandinou TGet al., 2021, Towards robust, unobtrusive sensing of respiration using UWB impulse Radar for the care of people living with dementia, 10th International IEEE-EMBS Conference on Neural Engineering (NER), Publisher: IEEE, Pages: 866-871, ISSN: 1948-3546

The unobtrusive monitoring of vital signals and behaviour can be used to gather intelligence to support the care of people living with dementia. This can provide insights into the person's wellbeing and the neurogenerative process, as well as enable them to continue to live safely at home, thereby improving their quality of life. Within this context, this study investigated the deployability of non-contact respiration rate (RR) measurement based on an Ultra-Wideband (UWB) radar System-on-Chip (SoC). An algorithm was developed to simultaneously and continuously extract the respiration signal, together with the confidence level of the respiration signal and the target position, without needing any prior calibration. The radar-measured RR results were compared to the RR results obtained from a ground truth measure based on the breathing sound, and the error rates were within 8% with a mean value of 2.5%. The target localisation results match to the radar-to-chest distances with a mean error rate of 5.8%. The tested measurement range was up to 5m. The results suggest that the algorithm could perform sufficiently well in non-contact stationary respiration rate detection.

Conference paper

Bannon A, Rapeaux A, Constandinou TG, 2021, Tiresias: A low-cost networked UWB radar system for in-home monitoring of dementia patients, 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), Pages: 7068-7072, ISSN: 1557-170X

Journal article

Del Bono F, Rapeaux A, Demarchi D, Constandinou TGet al., 2021, Translating node of Ranvier currents to extraneural electrical fields: a flexible FEM modeling approach, 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), Pages: 4268-4272, ISSN: 1557-170X

Journal article

Chen Z, Alan B, Rapeaux A, Constandinou Tet al., 2020, Towards robust, unobtrusive sensing of respiration using ultra-wideband impulse radar for the care of people living with dementia

<jats:p>The unobtrusive monitoring of vital signals and behaviour can be used to gather intelligence to support the care of people living with dementia. This can provide insights into the persons wellbeing and the neurogenerative process, as well as enable them to continue to live safely at home, thereby improving their quality of life. Within this context, this study investigated the deployability of non-contact respiration rate (RR) measurement based on an Ultra-Wideband (UWB) radar System-on-Chip (SoC). An algorithm was developed to simultaneously and continuously extract the respiration signal, together with the confidence level of the respiration signal and the target position, without needing any prior calibration. The radar-measured RR results were compared to the RR results obtained from a ground truth measure based on the breathing sound, and the error rates were within 8% with a mean value of 2.4%. The target localisation results match to the radarto-chest distances with a mean error rate of 5.4%. The tested measurement range was up to 5m. The results suggest that the algorithm could perform sufficiently well in non-contact stationary respiration rate detection.</jats:p>

Journal article

Rapeaux A, 2020, Enhancing Selectivity of Minimally Invasive Peripheral Nerve Interfaces using Combined Stimulation and High Frequency Block: from Design to Application

The discovery of the excitable property of nerves was a fundamental step forward in our knowledge of the nervous system and our ability to interact with it. As the injection of charge into tissue can drive its artificial activation, devices have been conceived that can serve healthcare by substituting the input or output of the peripheral nervous system when damage or disease has rendered it inaccessible or its action pathological. Applications are far-ranging and transformational as can be attested by the success of neuroprosthetics such as the cochlear implant. However, the body's immune response to invasive implants have prevented the use of more selective interfaces, leading to therapy side-effects and off-target activation. The inherent tradeoff between the selectivity and invasiveness of neural interfaces, and the consequences thereof, is still a defining problem for the field. More recently, continued research into how nervous tissue responds to stimulation has led to the discovery of High Frequency Alternating Current (HFAC) block as a stimulation method with inhibitory effects for nerve conduction. While leveraging the structure of the peripheral nervous system, this neuromodulation technique could be a key component in efforts to improve the selectivity-invasiveness tradeoff and provide more effective neuroprosthetic therapy while retaining the safety and reliability of minimally invasive neural interfaces. This thesis describes work investigating the use of HFAC block to improve the selectivity of peripheral nerve interfaces, towards applications such as bladder control or vagus nerve stimulation where selective peripheral nerve interfaces cannot be used, and yet there is an unmet need for more selectivity from stimulation-based therapy. An overview of the underlyingneuroanatomy and electrophysiology of the peripheral nervous system combined with a review of existing electrode interfaces and electrochemistry will serve to inform the problem space. Origina

Thesis dissertation

Williams I, Brunton E, Rapeaux A, Liu Y, Luan S, Nazarpour K, Constandinou TGet al., 2020, SenseBack-an implantable system for bidirectional neural interfacing, IEEE Transactions on Biomedical Circuits and Systems, Vol: 14, Pages: 1079-1087, ISSN: 1932-4545

Chronic in-vivo neurophysiology experiments require highly miniaturized, remotely powered multi-channel neural interfaces which are currently lacking in power or flexibility post implantation. In this article, to resolve this problem we present the SenseBack system, a post-implantation reprogrammable wireless 32-channel bidirectional neural interfacing that can enable chronic peripheral electrophysiology experiments in freely behaving small animals. The large number of channels for a peripheral neural interface, coupled with fully implantable hardware and complete software flexibility enable complex in-vivo studies where the system can adapt to evolving study needs as they arise. In complementary ex-vivo and in-vivo preparations, we demonstrate that this system can record neural signals and perform high-voltage, bipolar stimulation on any channel. In addition, we demonstrate transcutaneous power delivery and Bluetooth 5 data communication with a PC. The SenseBack system is capable of stimulation on any channel with ±20 V of compliance and up to 315 μA of current, and highly configurable recording with per-channel adjustable gain and filtering with 8 sets of 10-bit ADCs to sample data at 20 kHz for each channel. To the best of our knowledge this is the first such implantable research platform offering this level of performance and flexibility post-implantation (including complete reprogramming even after encapsulation) for small animal electrophysiology. Here we present initial acute trials, demonstrations and progress towards a system that we expect to enable a wide range of electrophysiology experiments in freely behaving animals.

Journal article

Rapeaux A, Constandinou TG, 2020, An HFAC block-capable and module-extendable 4-channel stimulator for acute neurophysiology, Journal of Neural Engineering, Vol: 17, ISSN: 1741-2552

Objective. This paper describes the design, testing and use of a novel multichannel block-capable stimulator for acute neurophysiology experiments to study highly selective neural interfacing techniques. This paper demonstrates the stimulator's ability to excite and inhibit nerve activity in the rat sciatic nerve model concurrently using monophasic and biphasic nerve stimulation as well as high-frequency alternating current (HFAC). Approach. The proposed stimulator uses a Howland Current Pump circuit as the main analogue stimulator element. 4 current output channels with a common return path were implemented on printed circuit board using Commercial Off-The-Shelf components. Programmable operation is carried out by an ARM Cortex-M4 Microcontroller on the Freescale freedom development platform (K64F). Main results. This stimulator design achieves ± 10 mA of output current with ± 15 V of compliance and less than 6 µA of resolution using a quad-channel 12-bit external DAC, for four independently driven channels. This allows the stimulator to carry out both excitatory and inhibitory (HFAC block) stimulation. DC Output impedance is above 1 M Ω. Overall cost for materials i.e. PCB boards and electronic components is less than USD 450 or GBP 350 and device size is approximately 9 cm × 6 cm × 5 cm. Significance. Experimental neurophysiology often requires significant investment in bulky equipment for specific stimulation requirements, especially when using HFAC block. Different stimulators have limited means of communicating with each other, making protocols more complicated. This device provides an effective solution for multi-channel stimulation and block of nerves, enabling studies on selective neural interfacing in acute scenarios with an affordable, portable and space-saving design for the laboratory. The stimulator can be further upgraded with additional modules to extend functionality while maintaining straightforward programming

Journal article

Rapeaux A, Constandinou T, 2020, A block-capable and module-extendable 4-channel stimulator for acute neurophysiology, Publisher: bioRxiv

Objective: This paper describes the design, testing and use of a novel multichannel block-capable stimulator for acute neurophysiology experiments to study highly selective neural interfacing techniques. This paper demonstrates the stimulator's ability to excite and inhibit nerve activity in the rat sciatic nerve model concurrently using monophasic and biphasic nerve stimulation as well as high-frequency alternating current (HFAC). Approach: The proposed stimulator uses a Howland Current Pump circuit as the main analogue stimulator element. 4 current output channels with a common return path were implemented on printed circuit board using Commercial Off-The-Shelf components. Programmable operation is carried out by an ARM Cortex-M4 Microcontroller on the Freescale freedom development platform (K64F). Main Results: This stimulator design achieves +-10 mA of output current with +-15V of compliance and less than 6 uA of resolution using a quad-channel 12-bit external DAC, for four independently driven channels. This allows the stimulator to carry out both excitatory and inhibitory (HFAC block) stimulation. DC Output impedance is above 1 Mohm. Overall cost is less than USD 450 or GBP 350 and device size is approximately 9 cm x 6 cm x 5 cm. Significance: Experimental neurophysiology often requires significant investment in bulky equipment for specific stimulation requirements, especially when using HFAC block. Different stimulators have limited means of communicating with each other, making protocols more complicated. This device provides an effective solution for multi-channel stimulation and block of nerves, enabling studies on selective neural interfacing in acute scenarios with an affordable, portable and space-saving design for the laboratory. The stimulator can be further upgraded with additional modules to extend functionality while maintaining straightforward programming and integration of functions with one controller.

Working paper

Williams I, Rapeaux A, Pearson J, Nazarpour K, Brunton E, Luan S, Liu Y, Constandinou Tet al., 2019, SenseBack - implant considerations for an implantable neural stimulation and recording device, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4

This paper describes a fully implantable and highlycompact neural interface platform for chronic (>6 month) ratand small rodent experiments. It provides 32 channels of highlyflexible neural stimulation and recording with wireless controland data readout, as well as wireless transcutaneous power. Allthe system firmware is fully upgradeable over the air (even afterimplantation) allowing future enhancements such as closed loopoperation or data filtering. This paper focuses on the implantconsiderations – i.e. design and manufacture of the physicalplatform, encapsulation, wireless connections and testing.

Conference paper

Cavuto M, Hallam R, Rapeaux A, Maslik M, Troiani F, Constandinou Tet al., 2019, Live demonstration: a public engagement platform for invasive neural interfaces, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-1

Neural interfaces, and more specifically ones ofthe invasive/implantable variety, today are a topic of muchcontroversy, often making the general public uncomfortable andintimidated. We have thus devised a bespoke interactive demoto help people understand brain implants and their need inthe age of wearable devices, with the secondary objective ofintroducing the wireless cortical neural probe that we, at NGNI(Next Generation Neural Interfaces) lab, are developing.

Conference paper

Perra E, Rapeaux A, Nikolic K, 2018, The crucial role of nerve depolarisation in high frequency conduction block in mammalian nerves: simulation study, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Pages: 2214-2217, ISSN: 1557-170X

Neurostimulations which use High Frequency Alternating Current (HFAC) block show great promise for neuromodulatory therapies. Treatments have been developed for various health conditions including obesity and obesity related health risks, and now even stomach cancer treatments are being considered. However the mechanism of the block is still not completely clear, as well as how various neural and electrode parameters affect it. In order to study conduction block during HF stimulation in mammalian axons, we describe a detailed computational model and perform comprehensive simulations. We establish relationships between the blocking frequency and amplitude versus fibre diameter and the distance between the electrode and fibre. We found that only a certain level of depolarisation will universally create a block irrespective of the fibre size, and it is in the range 24-30mV depending on the stimulus frequency. Our study crucially improves our knowledge about this important technique which is rapidly emerging as a commercially available therapy.

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

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, Pages: 1-4

Conference paper

Williams I, Rapeaux A, Luan S, Constandinou TGet al., 2018, Waveform Generator

Patent

Liu Y, Luan S, Williams I, Rapeaux A, Constandinou TGet al., 2017, A 64-Channel Versatile Neural Recording SoC with Activity Dependant Data Throughput, IEEE Transactions on Biomedical Circuits and Systems, Vol: 11, Pages: 1344-1355, ISSN: 1932-4545

Modern microtechnology is enabling the channel count of neural recording integrated circuits to scale exponentially. However, the raw data bandwidth of these systems is increasing proportionately, presenting major challenges in terms of power consumption and data transmission (especially for wireless systems). This paper presents a system that exploits the sparse nature of neural signals to address these challenges and provides a reconfigurable low-bandwidth event-driven output. Specifically, we present a novel 64-channel low noise (2.1μVrms, low power (23μW per analogue channel) neural recording system-on-chip (SoC). This features individually-configurable channels, 10-bit analogue-to-digital conversion, digital filtering, spike detection, and an event-driven output. Each channel's gain, bandwidth & sampling rate settings can be independently configured to extract Local Field Potentials (LFPs) at a low data-rate and/or Action Potentials (APs) at a higher data rate. The sampled data is streamed through an SRAM buffer that supports additional on-chip processing such as digital filtering and spike detection. Real-time spike detection can achieve ~2 orders of magnitude data reduction, by using a dual polarity simple threshold to enable an event driven output for neural spikes (16-sample window). The SoC additionally features a latency-encoded asynchronous output that is critical if used as part of a closed-loop system. This has been specifically developed to complement a separate on-node spike sorting co-processor to provide a real-time (low latency) output. The system has been implemented in a commercially-available 0.35μm CMOS technology occupying a silicon area of 19.1mm² (0.3mm² gross per channel), demonstrating a low power & efficient architecture which could be further optimised by aggressive technology and supply voltage scaling.

Journal article

Rapeaux A, Brunton E, Nazarpour K, Constandinou Tet al., 2017, Recovery Dynamics of the High Frequency Alternating Current Nerve Block

Objective: High-Frequency alternating current (HFAC) nerve block has great potential for neuromodulation-based therapies. However nerve function recovery dynamics after a block is highly understudied. This study aims to characterise the recovery dynamics of neural function after an HFAC block. Approach: Experiments were carried out in-vivo to determine blocking efficacy as a function of blocking signal amplitude and frequency, and recovery times as well as recovery completeness was measured within a 0.7s time scale from the end of block. The sciatic nerve was stimulated at 100 Hz during recovery to reduce error to within ±10 ms for measurements of recovery dynamics. The electromyogram (EMG) signals were measured from gastrocnemius medialis and tibialis anterior during trials as an indicator for nerve function. Main Results: The HFAC block was most reliable around 20 kHz, with block thresholds approximately 5 or 6 mA depending on the animal and muscle. Recovery times ranged from 20 to 430 milliseconds and final values spanned relative outputs from approximately 1 to 0.2. Higher blocking signal frequencies and amplitudes increased recovery time and decreased recovery completeness. Significance: These results confirm that recovery dynamics from block depend on blocking signal frequency and amplitude, which is of particular importance for neuromodulation therapies and for comparing results across studies using different blocking signal parameters.

Working paper

Williams I, Rapeaux A, Liu Y, Luan S, Constandinou TGet 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.

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

Bannon A, Rapeaux A, Constandinou T, Tiresias: A low-cost networked UWB radar system for in-home monitoring of dementia patients

<jats:p>This paper describes Tiresias, a low-cost, unobtrusive networked radar system designed to monitor vulnerable patients in domestic environments and provide high quality behavioural and health data. Dementia is a disease that affects millions worldwide and progressively degrades an individual's ability to care for themselves. Eventually most people living with dementia will need to reside in assisted living facilities as they become unable to care for themselves. Understanding the effects dementia has on ability to self-care and extending the length of time people living with dementia can remain living independently are key goals of dementia research and care. The networked radar system proposed in this paper is designed to provide high quality behavioural and health data from domestic environments. This is achieved using multiple radar sensors networked together with their data outputs integrated and processed to produce high confidence measures of position and movement. It is hoped the data produced by this system will both provide insights into how dementia progresses, and also help monitor vulnerable individuals in their own homes, allowing them to remain independent longer than would otherwise be possible.&lt;br&gt;</jats:p>

Journal article

Bannon A, Rapeaux A, Constandinou T, Tiresias: A low-cost networked UWB radar system for in-home monitoring of dementia patients

<jats:p>This paper describes Tiresias, a low-cost, unobtrusive networked radar system designed to monitor vulnerable patients in domestic environments and provide high quality behavioural and health data. Dementia is a disease that affects millions worldwide and progressively degrades an individual's ability to care for themselves. Eventually most people living with dementia will need to reside in assisted living facilities as they become unable to care for themselves. Understanding the effects dementia has on ability to self-care and extending the length of time people living with dementia can remain living independently are key goals of dementia research and care. The networked radar system proposed in this paper is designed to provide high quality behavioural and health data from domestic environments. This is achieved using multiple radar sensors networked together with their data outputs integrated and processed to produce high confidence measures of position and movement. It is hoped the data produced by this system will both provide insights into how dementia progresses, and also help monitor vulnerable individuals in their own homes, allowing them to remain independent longer than would otherwise be possible.&lt;br&gt;</jats:p>

Journal article

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

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: respub-action=search.html&id=00896187&limit=30&person=true