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Journal articleWilliams I, Brunton E, Rapeaux A, et al., 2020,
SenseBack-an implantable system for bidirectional neural interfacing
, IEEE Transactions on Biomedical Circuits and Systems, Vol: 14, Pages: 1079-1087, ISSN: 1932-4545Chronic 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.
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Journal articleRapeaux A, Constandinou TG, 2020,
An HFAC block-capable and module-extendable 4-channel stimulator for acute neurophysiology
, Journal of Neural Engineering, Vol: 17, ISSN: 1741-2552Objective. 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
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Conference paperSavolainen OW, Constandinou TG, 2020,
Predicting single-unit activity from local field potentials with LSTMs
, 42nd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 884-887, ISSN: 1557-170XThis paper investigates to what extent Long ShortTerm Memory (LSTM) decoders can use Local Field Potentials (LFPs) to predict Single-Unit Activity (SUA) in Macaque Primary Motor cortex. The motivation is to determine to what degree the LFP signal can be used as a proxy for SUA, for both neuroscience and Brain-Computer Interface (BCI) applications. Firstly, the results suggest that the prediction quality varies significantly by implant location or animal. However, within each implant location / animal, the prediction quality seems to be correlated with the amount of power in certain LFP frequency bands (0-10, 10-20 and 40-50 Hz, standardised LFPs). Secondly, the results suggest that bipolar LFPs are more informative as to SUA than unipolar LFPs. This suggests common mode rejection aids in the elimination of non-local neural information. Thirdly, the best individual bipolar LFPs generally perform better than when using all available unipolar LFPs. This suggests that LFP channel selection may be a simple but effective means of lossy data compression in Wireless Intracortical LFP-based BCIs. Overall, LFPs were moderately predictive of SUA, and improvements can likely be made.
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Conference paperSavolainen OW, Constandinou TG, 2020,
Lossless compression of intracortical extracellular neural recordings using non-adaptive huffman encoding
, 42nd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 4318-4321, ISSN: 1557-170XThis paper investigates the effectiveness of four Huffman-based compression schemes for different intracortical neural signals and sample resolutions. The motivation is to find effective lossless, low-complexity data compression schemes for Wireless Intracortical Brain-Machine Interfaces (WI-BMI). The considered schemes include pre-trained Lone 1st and 2nd order encoding [1], pre-trained Delta encoding, and pre-trained Linear Neural Network Time (LNNT) encoding [2]. Maximum codeword-length limited versions are also considered to protect against overfit to training data. The considered signals are the Extracellular Action Potential signal, the Entire Spiking Activity signal, and the Local Field Potential signal. Sample resolutions of 5 to 13 bits are considered. The result show that overfit-protection dramatically improves compression, especially at higher sample resolutions. Across signals, 2nd order encoding generally performed best at lower sample resolutions, and 1st order, Delta and LNNT encoding performed best at higher sample resolutions. The proposed methods should generalise to other remote sensing applications where the distribution of the sensed data can be estimated a priori.
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Journal articleLiu Y, Urso A, Martins da Ponte R, et al., 2020,
Bidirectional bioelectronic interfaces: system design and circuit implications
, IEEE Solid-State Circuits Magazine, Vol: 12, Pages: 30-46, ISSN: 1943-0582The total economic cost of neurological disorders exceeds £100 billion per annum in the United Kingdom alone, yet pharmaceutical companies continue to cut investments due to failed clinical studies and risk [1]. These challenges motivate an alternative to solely pharmacological treatments. The emerging field of bioelectronics suggests a novel alternative to pharmaceutical intervention that uses electronic hardware to directly stimulate the nervous system with physiologically inspired electrical signals [2]. Given the processing capability of electronics and precise targeting of electrodes, the potential advantages of bioelectronics include specificity in the time, method, and location of treatment, with the ability to iteratively refine and update therapy algorithms in software [3]. A primary disadvantage of the current systems is invasiveness due to surgical implantation of the device.
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Journal articleDe Marcellis A, Di Patrizio Stanchieri G, Faccio M, et al., 2020,
A 300 Mbps 37 pJ/bit pulsed optical biotelemetry
, IEEE Transactions on Biomedical Circuits and Systems, Vol: 14, Pages: 441-451, ISSN: 1932-4545This article reports an implantable transcutaneous telemetry for a brain machine interface that uses a novel optical communication system to achieve a highly energy-efficient link. Based on an pulse-based coding scheme, the system uses sub-nanosecond laser pulses to achieve data rates up to 300 Mbps with relatively low power levels when compared to other methods of wireless communication. This has been implemented using a combination of discrete components (semiconductor laser and driver, fast-response Si photodiode and interface) integrated at board level together with reconfigurable logic (encoder, decoder and processing circuits implemented using Xilinx KCU105 board with Kintex UltraScale FPGA). Experimental validation has been performed using a tissue sample that achieves representative level of attenuation/scattering (porcine skin) in the optical path. Results reveal that the system can operate at data rates up to 300 Mbps with a bit error rate (BER) of less than 10 −10 , and an energy efficiency of 37 pJ/bit. This can communicate, for example, 1,024 channels of broadband neural data sampled at 18 kHz, 16-bit with only 11 mW power consumption.
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Journal articleWang G, Constandinou TG, Tang K-T, 2020,
Editorial
, IEEE Transactions on Biomedical Circuits and Systems, Vol: 14, Pages: 1-1, ISSN: 1932-4545 -
Conference paperCavuto M, Hallam R, Rapeaux A, et al., 2019,
Live demonstration: a public engagement platform for invasive neural interfaces
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-1Neural 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.
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Conference paperFeng P, Maslik M, Constandinou T, 2019,
EM-lens enhanced power transfer and multi-node data transmission for implantable medical devices
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4This paper presents a robust EM-lens-enhancedwireless power transmission system and a novel multiple-nodedata communication method for distributed implantable medicaldevices. The proposed techniques can solve the common issuescaused by multiple implanted devices, such as low power transferefficiency through biological tissues, uneven delivered powerfor distributed devices and interference between simultaneouswireless power and data transmission. A prototype system hasbeen manufactured with discrete components on FR4 substrateas a proof of concept. The EM-Lens-enhanced inductive linkscan expand the power coverage of transmitting (Tx) coil from9 mm×5 mm to 14 mm×13 mm, and double the recovered DCvoltage from 1.8 V to 3.2 V at 12.5 mm distance. Data commu-nication is achieved by novel low-power back-scattering CDMAscheme. This permits transmission of data from several nodesall operating with the same carrier frequency simultaneouslyreflecting the power carriers to the primary side. In this paper,we demonstrate simultaneous communication between two nodesat 125 kbps with 1.05 mW power consumption.
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Conference paperHsieh B, Harding E, Wisden W, et al., 2019,
A miniature neural recording device to investigate sleep and temperature regulation in mice
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4Sleep is an important and ubiquitous process that,despite decades of research, a large part of its underlyingbiological circuity still remain elusive. To conduct research inthis field, many devices capable of recording neural signalssuch as LFP and EEG have been developed. However, most ofthese devices are unsuitable for sleep studies in mice, the mostcommonly used animals, due to their size and weight. Thus, thispaper presents a novel 4 channel, compact ( 2.1cm by 1.7cm )and lightweight ( 3.6g ) neural-logging device that can recordfor 3 days on just two 0.6g zinc air 312 batteries. Instead ofthe typical solution of using multiple platforms, the presenteddevice integrates high resolution EEG, EMG and temperaturerecordings into one platform. The onboard BLE module allowsthe device to be controlled wirelessly as well as stream data in realtime, enabling researchers to check the progress of the recordingwith minimal animal disturbance. The device demonstrates itsability to accurately record EEG and temperature data throughthe long 24 hour in-vivo recordings conducted. The obtainedEEG data could be easily sleep scored and the temperaturesvalues were all within expected physiological range.
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Conference paperDe Marcellis A, Stanchieri GDP, Palange E, et al., 2019,
A 0.35μm CMOS UWB-inspired bidirectional communication system-on-chip for transcutaneous optical biotelemetry links
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4In this paper we report on the fabrication, implementation and experimental characterization of an integrated bidirectional communication System-on-Chip (SoC) for transcutaneous bidirectional optical biotelemetry links. The proposed architecture implements a UWB-inspired pulsed coding technique and contains a transmitter and a receiver to achieve a simultaneous bidirectional link. The transmitter generates sub-nanosecond current pulses to directly drive off-chip pulsed vertical cavity semiconductor lasers by means of a digital data coding subsystem and all the needed bias and driving circuits. On the other hand, the receiver manages off-chip fast Si photodiodes and includes signal conditioning, detection and digital data decoding circuits to support high bit rate and energy efficient communication links. The entire solution designed at transistor level has been fabricated in AMS 0.35µm standard CMOS technology into a compact silicon footprint lower than 0.13mm2 employing only 113 transistors and 1 resistor. A specific PCB has been developed together with a suitable test bench implemented on Xilinx Virtex-6 XC6VLX240T FPGA board to properly evaluate the performances and the main characteristics of the ASIC. Furthermore, a 6 GHz, 20 GS/s LeCroy WaveMaster 8600A digital oscilloscope has been employed to investigate the system time response. Preliminary experimental results validated the correct functionality of the overall integrated system demonstrating also its capability to operate, also in a bidirectional mode, at bit rates up to 250 Mbps with pulse widths up to 1.2ns and a minimum total power efficiency of about 160 pJ/bit in the conditions for which the transmitter and the receiver work simultaneously onto the same chip. These results make the developed solution suitable for high performances bidirectional optical biotelemetry links to be applied, e.g., to implantable neural recording/stimulation transcutaneous platforms that generally require communication
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Conference paperHaci D, Mifsud A, Liu Y, et al., 2019,
In-body wireline interfacing platform for multi-module implantable microsystems
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4The recent evolution of implantable medical devicesfrom single-unit stimulators to modern implantable microsys-tems, has driven the need for distributed technologies, in whichboth the implant system and functions are partitioned across mul-tiple active devices. This multi-module approach is made possiblethanks to novel network architectures, allowing for in-body powerand data communications to be performed using implantableleads. This paper discusses the challenges in implementing suchinterfacing system and presents a platform based on one centralimplant (CI) and multiple peripheral implants (PIs) using a cus-tom 4WiCS communication protocol. This is implemented in PCBtechnology and tested to demonstrate intrabody communicationcapabilities and power transfer within the network. Measuredresults show CI-to-PI power delivery achieves 70%efficiency inexpected load condition, while establishing full-duplex data linkwith up to 4 PIs simultaneously.
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Conference paperWong S, Ekanayake J, Liu Y, et al., 2019,
An impedance probing system for real-time intra-operative brain tumour tissue discrimination
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4The ability to perform realtime diagnostics of tissueintraoperatively can greatly enhance the precision and effective-ness of the underlying surgery, for example, in tumour resection.To achieve this however would require a miniature tool ableto performin situ, in-vivocharacterisation for distinguishingbetween different types of tissues. In this work, we exploredthe feasibility and requirements of implementing a portableimpedance characterisation system for brain tumour detection.We proposed and implemented a novel system based on PCB-based instrumentation using a square four-electrode microendo-scopic probe. The system uses a digital-to-analogue converterto generate a multi-tone sinusoid waveform, and a floating bi-directional voltage-to-current converter to output the differentialstimulation current to one pair of electrodes. The other pairof electrodes are connected to the sensing circuit based on aninstrumentation amplifier. The recorded data is pre-processed bythe micro-controller and then analysed on a host computer. Toevaluate the system, tetrapolar impedances have been recordedfrom a number of different electrode configurations to sense pre-defined resistance values. The overall system consumes 143 mAcurrent, achieve 0.1% linearity and 15μV noise level, with amaximum signal bandwidth of 100 kHz. Initial experimentalresults on tissue were carried out on a piece of rib-eye steak.Electrical impedance maps (EIM) and contour plots were thenreconstructed to represent the impedance value in different tissue region.
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Conference paperWilliams I, Rapeaux A, Pearson J, et al., 2019,
SenseBack - implant considerations for an implantable neural stimulation and recording device
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 1-4This 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.
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Journal articleLiu Y, Constandinou TG, Georgiou P, 2019,
Ultrafast large-scale chemical sensing with CMOS ISFETs: a level-crossing time-domain approach
, IEEE Transactions on Biomedical Circuits and Systems, Vol: 13, Pages: 1201-1213, ISSN: 1932-4545The introduction of large-scale chemical sensing systems in CMOS which integrate millions of ISFET sensors have allowed applications such as DNA sequencing and fine-pixel chemical imaging systems to be realised. Using CMOS ISFETs provides advantages of digitisation directly at the sensor as well as correcting for non-linearity in its response. However, for this to be beneficial and scale, the readout circuits need to have the minimum possible footprint and power consumption. Within this context, this paper analyses an ISFET based pH-to-time readout using an inverter in the time-domain as a level-crossing detector and presents a 32×32 array with in-pixel digitisation for pH sensing. The inverter-based sensing pixel, controlled by a triangular waveform, converts the pH response into a time-domain signal whilst also compensating for sensor offset and thus resulting in an increase in dynamic range. The sensor pixels interface to a 15-bit asynchronous column-wise time-to-digital converter (TDC), enabling fast asynchronous conversion whilst using minimal silicon area. Parallel outputs of 32 TDC interfaces are serialised to achieve fast data throughput. This system is implemented in a standard 0.18um CMOS technology, with a pixel size of 26μm×26μm and a TDC area of 26μm×180μm. Measured results demonstrate the system is able to sense reliably with an average pH sensitivity of 30mVpH, whilst being able to compensate for sensor offset by up to ±7V. A resolution of 0.013pH is achieved and noise measurements show an integrated noise of 0.08pH within 2-500Hz and SFDR of 42.6dB. Total power consumption is 11.286mW.
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Journal articleChew DJ, Constandinou TG, Gupta I, et al., 2019,
Bioelectronic medicines: past, present and future. Highlights from The Society for Medicines Research Symposium
, Drugs of the Future, Vol: 44, Pages: 895-902, ISSN: 0377-8282On October 1, 2019, the Society for Medicines Research (SMR) held its first symposium on "Bioelectronic medicines, past, present and future" at the Royal Academy of Engineering in London. The meeting was attended by 145 participants and was supported by Galvani Bioelectronics, IEEE-CAS Society, IEEE-Brain Initiative, BIOS, Heraeus, CorTec and the IT'IS Foundation.
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Conference paperDe Marcellis A, Stanchieri GDP, Palange E, et al., 2019,
A 0.35 mu m CMOS UWB-inspired bidirectional communication system-on-chip for transcutaneous optical biotelemetry links
, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, ISSN: 2163-4025In this paper we report on the fabrication, implementation and experimental characterization of an integrated bidirectional communication System-on-Chip (SoC) for transcutaneous bidirectional optical biotelemetry links. The proposed architecture implements a UWB-inspired pulsed coding technique and contains a transmitter and a receiver to achieve a simultaneous bidirectional link. The transmitter generates sub- nanosecond current pulses to directly drive offchip pulsed vertical cavity semiconductor lasers by means of a digital data coding subsystem and all the needed bias and driving circuits. The receiver interfaces to off-chip fast Si photodiodes and includes signal conditioning, detection and digital data decoding circuits to support high bit rate and energy efficient communication links. The SoC has been implemented in a commercially-available 0.35 mu m CMOS technology provided by AMS, occupying a compact silicon footprint of less than 0.13 mm2 employing 113 transistors and 1 resistor. This is evaluated using a testbench consisting of a custom PCB and a Xilinx Virtex-6 XC6VLX240T FPGA board. Preliminary experimental results validated the correct functionality of the overall integrated system demonstrating its capability to operate, also in a bidirectional mode, at bit rates up to 250 Mbps with pulse widths down to 1.2 ns and a minimum total power efficiency of about 160 pJ/bit in the conditions for which the transmitter and the receiver work simultaneously on the same chip. This demonstrated performance makes the optical biotelemetry particularly suitable for highly scalable (i.e., high bitrate, low energy per bit) implantable devices such as brain machine interfaces.
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Conference paperHan Y, Lauteslager T, Lande TS, et al., 2019,
UWB radar for non-contact heart rate variability monitoring and mental state classification.
, Annual Meeting of the IEEE Engineering in Medicine and Biology Society, Pages: 6578-6582, ISSN: 1557-170XHeart rate variability (HRV), as measured by ultra-wideband (UWB) radar, enables contactless monitoring of physiological functioning in the human body. In the current study, we verified the reliability of HRV extraction from radar data, under limited transmitter power. In addition, we conducted a feasibility study of mental state classification from HRV data, measured using radar. Specifically, arctangent demodulation with calibration and low rank approximation have been used for radar signal pre-processing. An adaptive continuous wavelet filter and moving average filter were utilized for HRV extraction. For the mental state classification task, performance of support vector machine, k-nearest neighbors and random forest classifiers have been compared. The developed system has been validated on human participants, with 10 participants for HRV extraction, and three participants for the proof-of-concept mental state classification study. The results of HRV extraction demonstrate the reliability of time-domain parameter extraction from radar data. However, frequency-domain HRV parameters proved to be unreliable under low SNR. The best average overall mental state classification accuracy achieved was 82.34%, which has important implications for the feasibility of mental health monitoring using UWB radar.
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Journal articleLauteslager T, Tommer M, Lande TS, et al., 2019,
Coherent UWB radar-on-chip for in-body measurement of cardiovascular dynamics
, IEEE Transactions on Biomedical Circuits and Systems, Vol: 13, Pages: 814-824, ISSN: 1932-4545Coherent ultra-wideband (UWB) radar-on-chip technology shows great promise for developing portable and low-cost medical imaging and monitoring devices. Particularly monitoring the mechanical functioning of the cardiovascular system is of interest, due to the ability of radar systems to track sub-mm motion inside the body at a high speed. For imaging applications, UWB radar systems are required, but there are still significant challenges with in-body sensing using low-power microwave equipment and wideband signals. Recently it was shown for the first time, on a single subject, that the arterial pulse wave can be measured at various locations in the body, using coherent UWB radar-on-chip technology. The current work provides more substantial evidence, in the form of new measurements and improved methods, to demonstrate that cardiovascular dynamics can be measured using radar-on-chip. Results across four participants were found to be robust and repeatable. Cardiovascular signals were recorded using radar-on-chip systems and electrocardiography (ECG). Through ECG-aligned averaging, the arterial pulse wave could be measured at a number of locations in the body. Pulse arrival time could be determined with high precision, and blood pressure pulse wave propagation through different arteries was demonstrated. In addition, cardiac dynamics were measured from the chest. This work serves as a first step in developing a portable and low-cost device for long-term monitoring of the cardiovascular system, and provides the fundamentals necessary for developing UWB radar-on-chip imaging systems.
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Conference paperAhmadi N, Constandinou TG, Bouganis C-S, 2019,
End-to-End Hand Kinematic Decoding from LFPs Using Temporal Convolutional Network
, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 1-4, ISSN: 2163-4025In recent years, local field potentials (LFPs) haveemerged as a promising alternative input signal for brain-machine interfaces (BMIs). Several studies have demonstratedthat LFP-based BMIs could provide long-term recording stabilityand comparable decoding performance to their spike counter-parts. Despite the compelling results, however, most LFP-basedBMIs still make use of hand-crafted features which can betime-consuming and suboptimal. In this paper, we propose anend-to-end system approach based on temporal convolutionalnetwork (TCN) to automatically extract features and decodekinematics of hand movements directly from raw LFP signals.We benchmark its decoding performance against traditionalapproach incorporating long short-term memory (LSTM) de-coders driven by hand-crafted LFP features. Experimental re-sults demonstrate significant performance improvement of theproposed approach compared to the traditional approach. Thissuggests the suitability of TCN-based end-to-end system and itspotential for providng stable and high decoding performanceLFP-based BMIs.
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