Tutorial: a guide to techniques for analysing recordings from the peripheral nervous system.

The nervous system, through a combination of conscious and automatic processes, enables the regulation of the body and its interactions with the environment. The peripheral nervous system is an excellent target for technologies that seek to modulate, restore or enhance these abilities as it carries sensory and motor information that most directly relates to a target organ or function. However, many applications require a combination of both an effective peripheral nerve interface (PNI) and effective signal processing techniques to provide selective and stable recordings. While there are many reviews on the design of PNIs, reviews of data analysis techniques and translational considerations are limited. Thus, this tutorial aims to support new and existing researchers in the understanding of the general guiding principles, and introduces a taxonomy for electrode configurations, techniques and translational models to consider.

The Design of a Low Noise, Multi-Channel Recording System for Use in Implanted Peripheral Nerve Interfaces.

In the development of implantable neural interfaces, the recording of signals from the peripheral nerves is a major challenge. Since the interference from outside the body, other biopotentials, and even random noise can be orders of magnitude larger than the neural signals, a filter network to attenuate the noise and interference is necessary. However, these networks may drastically affect the system performance, especially in recording systems with multiple electrode cuffs (MECs), where a higher number of electrodes leads to complicated circuits. This paper introduces formal analyses of the performance of two commonly used filter networks. To achieve a manageable set of design equations, the state equations of the complete system are simplified. The derived equations help the designer in the task of creating an interface network for specific applications. The noise, crosstalk and common-mode rejection ratio (CMRR) of the recording system are computed as a function of electrode impedance, filter component values and amplifier specifications. The effect of electrode mismatches as an inherent part of any multi-electrode system is also discussed, using measured data taken from a MEC implanted in a sheep. The accuracy of these analyses is then verified by simulations of the complete system. The results indicate good agreement between analytic equations and simulations. This work highlights the critical importance of understanding the effect of interface circuits on the performance of neural recording systems.

Adapting the Finetech-Brindley Sacral Anterior Root Stimulator for Bioelectronic Medicine.

The Finetech-Brindley Sacral Anterior Root Stimulator (SARS) is a low cost and reliable system. The architecture has been used for various bioelectric treatments, including several thousand implanted systems for restoring bladder function following spinal cord injury (SCI). Extending the operational frequency range would expand the capability of the system; enabling, for example, the exploration of eliminating the rhizotomy through an electrical nerve block. The distributed architecture of the SARS system enables stimulation parameters to be adjusted without modifying the implant design or manufacturing. To explore the design degrees-of-freedom, a circuit simulation was created and validated using a modified SARS system that supported stimulation frequencies up to 600 Hz. The simulation was also used to explore high frequency (up to 30kHz) behaviour, and to determine the constraints on charge delivered at the higher rates. A key constraint found was the DC blocking capacitors, designed originally for low frequency operation, not fully discharging within a shortened stimulation period. Within these current implant constraints, we demonstrate the potential capability for higher frequency operation that is consistent with presynaptic stimulation block, and also define targeted circuit improvements for future extension of stimulation capability.

The Effects of Adding Transcutaneous Spinal Cord Stimulation (tSCS) to Sit-To-Stand Training in People with Spinal Cord Injury: A Pilot Study.

Spinal cord stimulation may enable recovery of volitional motor control in people with chronic Spinal Cord Injury (SCI). In this study we explored the effects of adding SCS, applied transcutaneously (tSCS) at vertebral levels T10/11, to a sit-to-stand training intervention in people with motor complete and incomplete SCI. Nine people with chronic SCI (six motor complete; three motor incomplete) participated in an 8-week intervention, incorporating three training sessions per week. Participants received either tSCS combined with sit-to-stand training (STIM) or sit-to-stand training alone (NON-STIM). Outcome measures were carried out before and after the intervention. Seven participants completed the intervention (STIM N = 5; NON-STIM N = 2). Post training, improvements in International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) motor scores were noted in three STIM participants (range 1.0-7.0), with no change in NON-STIM participants. Recovery of volitional lower limb muscle activity and/or movement (with tSCS off) was noted in three STIM participants. Unassisted standing was not achieved in any participant, although standing with minimal assistance was achieved in one STIM participant. This pilot study has shown that the recruitment of participants, intervention and outcome measures were all feasible in this study design. However, some modifications are recommended for a larger trial.

The Neural Engine: A Reprogrammable Low Power Platform for Closed-Loop Optogenetics.

Brain-machine Interfaces (BMI) hold great potential for treating neurological disorders such as epilepsy. Technological progress is allowing for a shift from open-loop, pacemaker-class, intervention towards fully closed-loop neural control systems. Low power programmable processing systems are therefore required which can operate within the thermal window of 2° C for medical implants and maintain long battery life. In this work, we have developed a low power neural engine with an optimized set of algorithms which can operate under a power cycling domain. We have integrated our system with a custom-designed brain implant chip and demonstrated the operational applicability to the closed-loop modulating neural activities in in-vitro and in-vivo brain tissues: the local field potentials can be modulated at required central frequency ranges. Also, both a freely-moving non-human primate (24-hour) and a rodent (1-hour) in-vivo experiments were performed to show system reliable recording performance. The overall system consumes only 2.93 mA during operation with a biological recording frequency 50 Hz sampling rate (the lifespan is approximately 56 hours). A library of algorithms has been implemented in terms of detection, suppression and optical intervention to allow for exploratory applications in different neurological disorders. Thermal experiments demonstrated that operation creates minimal heating as well as battery performance exceeding 24 hours on a freely moving rodent. Therefore, this technology shows great capabilities for both neuroscience in-vitro/in-vivo applications and medical implantable processing units.

The effects of FES cycling combined with virtual reality racing biofeedback on voluntary function after incomplete SCI: a pilot study.

BACKGROUND: Functional Electrical Stimulation (FES) cycling can benefit health and may lead to neuroplastic changes following incomplete spinal cord injury (SCI). Our theory is that greater neurological recovery occurs when electrical stimulation of peripheral nerves is combined with voluntary effort. In this pilot study, we investigated the effects of a one-month training programme using a novel device, the iCycle, in which voluntary effort is encouraged by virtual reality biofeedback during FES cycling. METHODS: Eleven participants (C1-T12) with incomplete SCI (5 sub-acute; 6 chronic) were recruited and completed 12-sessions of iCycle training. Function was assessed before and after training using the bilateral International Standards for Neurological Classification of SCI (ISNC-SCI) motor score, Oxford power grading, Modified Ashworth Score, Spinal Cord Independence Measure, the Walking Index for Spinal Cord Injury and 10 m-walk test. Power output (PO) was measured during all training sessions. RESULTS: Two of the 6 participants with chronic injuries, and 4 of the 5 participants with sub-acute injuries, showed improvements in ISNC-SCI motor score > 8 points. Median (IQR) improvements were 3.5 (6.8) points for participants with a chronic SCI, and 8.0 (6.0) points for those with sub-acute SCI. Improvements were unrelated to other measured variables (age, time since injury, baseline ISNC-SCI motor score, baseline voluntary PO, time spent training and stimulation amplitude; p > 0.05 for all variables). Five out of 11 participants showed moderate improvements in voluntary cycling PO, which did not correlate with changes in ISNC-SCI motor score. Improvement in PO during cycling was positively correlated with baseline voluntary PO (R2 = 0.50; p < 0.05), but was unrelated to all other variables (p > 0.05). The iCycle was not suitable for participants who were too weak to generate a detectable voluntary torque or whose effort resulted in a negative torque. CONCLUSIONS: Improved ISNC-SCI motor scores in chronic participants may be attributable to the iCycle training. In sub-acute participants, early spontaneous recovery and changes due to iCycle training could not be distinguished. The iCycle is an innovative progression from existing FES cycling systems, and positive results should be verified in an adequately powered controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03834324. Registered 06 February 2019 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03834324. Protocol V03, dated 06.08.2015.

An ASIC for Recording and Stimulation in Stacked Microchannel Neural Interfaces.

This paper presents an active microchannel neural interface (MNI) using seven stacked application specific integrated circuits (ASICs). The approach provides a solution to the present problem of interconnect density in three-dimensional (3-D) MNIs. The 4 mm2 ASIC is implemented in 0.35 µm high-voltage CMOS technology. Each ASIC is the base for seven microchannels each with three electrodes in a pseudo-tripolar arrangement. Multiplexing allows stimulating or recording from any one of 49 channels, across seven ASICs. Connections to the ASICs are made with a five-line parallel bus. Current controlled biphasic stimulation from 5 to 500 µA has been demonstrated with switching between channels and ASICs. The high-voltage technology gives a compliance of 40 V for stimulation, appropriate for the high impedances within microchannels. High frequency biphasic stimulation, up to 40 kHz is achieved, suitable for reversible high frequency nerve blockades. Recording has been demonstrated with mV level signals; common-mode inputs are differentially distorted and limit the CMRR to 40 dB. The ASIC has been used in vitro in conjunction with an oversize (2 mm diameter) microchannel in phosphate buffered saline, demonstrating attenuation of interference from outside the microchannel and tripolar recording of signals from within the microchannel. By using five-lines for 49 active microchannels the device overcomes limitations when connecting many electrodes in a 3-D miniaturized nerve interface.

Killing the goose.

The regulatory framework for implanted medical devices is preventing severely impaired people from benefitting from rehabilitation research. Consequently, research effort is wasted and we are unable to use implants to reduce the costs of healthcare. The framework should be altered so that it is economically possible to get new devices for small patient groups into widespread use.

A New Method for Neural Spike Alignment: The Centroid Filter.

Recordings made directly from the nervous system are a key tool in experimental electrophysiology and the development of bioelectronic medicines. Analysis of these recordings involves the identification of signals from individual neurons, a process known as spike sorting. A critical and limiting feature of spike sorting is the need to align individual spikes in time. However, electrophysiological recordings are made in extremely noisy environments that seriously limit the performance of the spike-alignment process. We present a new centroid-based method and demonstrate its effectiveness using deterministic models of nerve signals. We show that spike alignment in the presence of noise is possible with a 30 dB reduction in minimum SNR compared with the conventional methods. We present a mathematical analysis of the centroid method, characterizing its fundamental operation and performance. Furthermore, we show that the centroid method lends itself particularly well to hardware realization, and we present results from a low-power implementation that operates on an FPGA, consuming ten times less power than conventional techniques - an important property for implanted devices. Our centroid method enables the accurate alignment of spikes in sub-0 dB SNR recordings and has the potential to enable the analysis of spikes in a wider range of environments than has been previously possible. Our method thus has the potential to influence significantly the design of electrophysiological recording systems in the future.

An Integrated Passive Phase-Shift Keying Modulator for Biomedical Implants With Power Telemetry Over a Single Inductive Link.

This paper presents a passive phase-shift keying (PPSK) modulator for uplink data transmission for biomedical implants with simultaneous power and data transmission over a single 13.56 MHz inductive link. The PPSK modulator provides a data rate up to 1.35 Mbps with a modulation index between 3% and 38% for a variation of the coupling coefficient between 0.05 and 0.26. This modulation scheme is particularly suited for biomedical implants that have high power demand and low coupling coefficients. The PPSK modulator operates in conjunction with on-off-keying downlink communication. The same inductive link is used to provide up to 100 mW of power to a multi-channel stimulator. The majority of the system on the implant side was implemented as an application specific integrated circuit (ASIC), fabricated in 0.6- [Formula: see text] high voltage CMOS technology. The theory of PPSK modulation, simulated and measured performance evaluation, and comparison with other state-of-the-art impedance modulation techniques is presented. The measured bit error rate around critical coupling at 1.35 Mbps is below 6 ×10-8.

Four-Wire Interface ASIC for a Multi-Implant Link.

This paper describes an on-chip interface for recovering power and providing full-duplex communication over an AC-coupled 4-wire lead between active implantable devices. The target application requires two modules to be implanted in the brain (cortex) and upper chest; connected via a subcutaneous lead. The brain implant consists of multiple identical "optrodes" that facilitate a bidirectional neural interface (electrical recording and optical stimulation), and the chest implant contains the power source (battery) and processor module. The proposed interface is integrated within each optrode ASIC allowing full-duplex and fully-differential communication based on Manchester encoding. The system features a head-to-chest uplink data rate (up to 1.6 Mbps) that is higher than that of the chest-to-head downlink (100 kbps), which is superimposed on a power carrier. On-chip power management provides an unregulated 5-V dc supply with up to 2.5-mA output current for stimulation, and two regulated voltages (3.3 and 3 V) with 60-dB power supply rejection ratio for recording and logic circuits. The 4-wire ASIC has been implemented in a 0.35-[Formula: see text] CMOS technology, occup-ying a 1.5-mm2 silicon area, and consumes a quiescent current of [Formula: see text]. The system allows power transmission with measured efficiency of up to 66% from the chest to the brain implant. The downlink and uplink communication are successfully tested in a system with two optrodes and through a 4-wire implantable lead.

An implantable ENG detector with in-system velocity selective recording (VSR) capability.

Detection and classification of electroneurogram (ENG) signals in the peripheral nervous system can be achieved by velocity selective recording (VSR) using multi-electrode arrays. This paper describes an implantable VSR-based ENG recording system representing a significant development in the field since it is the first system of its type that can record naturally evoked ENG and be interfaced wirelessly using a low data rate transcutaneous link. The system consists of two CMOS ASICs one of which is placed close to the multi-electrode cuff array (MEC), whilst the other is mounted close to the wireless link. The digital ASIC provides the signal processing required to detect selectively ENG signals based on velocity. The design makes use of an original architecture that is suitable for implantation and reduces the required data rate for transmission to units placed outside the body. Complete measured electrical data from samples of the ASICs are presented that show that the system has the capability to record signals of amplitude as low as 0.5 µV, which is adequate for the recording of naturally evoked ENG. In addition, measurements of electrically evoked ENG from the explanted sciatic nerves of Xenopus Laevis frogs are presented.

Microchannel neural interface manufacture by stacking silicone and metal foil laminae.

OBJECTIVE: Microchannel neural interfaces (MNIs) overcome problems with recording from peripheral nerves by amplifying signals independent of node of Ranvier position. Selective recording and stimulation using an MNI requires good insulation between microchannels and a high electrode density. We propose that stacking microchannel laminae will improve selectivity over single layer MNI designs due to the increase in electrode number and an improvement in microchannel sealing. APPROACH: This paper describes a manufacturing method for creating MNIs which overcomes limitations on electrode connectivity and microchannel sealing. Laser cut silicone-metal foil laminae were stacked using plasma bonding to create an array of microchannels containing tripolar electrodes. Electrodes were DC etched and electrode impedance and cyclic voltammetry were tested. MAIN RESULTS: MNIs with 100 µm and 200 µm diameter microchannels were manufactured. High electrode density MNIs are achievable with electrodes present in every microchannel. Electrode impedances of 27.2 ± 19.8 kΩ at 1 kHz were achieved. Following two months of implantation in Lewis rat sciatic nerve, micro-fascicles were observed regenerating through the MNI microchannels. SIGNIFICANCE: Selective MNIs with the peripheral nervous system may allow upper limb amputees to control prostheses intuitively.

Flexible active electrode arrays with ASICs that fit inside the rat's spinal canal.

Epidural spinal cord electrical stimulation (ESCS) has been used as a means to facilitate locomotor recovery in spinal cord injured humans. Electrode arrays, instead of conventional pairs of electrodes, are necessary to investigate the effect of ESCS at different sites. These usually require a large number of implanted wires, which could lead to infections. This paper presents the design, fabrication and evaluation of a novel flexible active array for ESCS in rats. Three small (1.7 mm(2)) and thin (100 µm) application specific integrated circuits (ASICs) are embedded in the polydimethylsiloxane-based implant. This arrangement limits the number of communication tracks to three, while ensuring maximum testing versatility by providing independent access to all 12 electrodes in any configuration. Laser-patterned platinum-iridium foil forms the implant's conductive tracks and electrodes. Double rivet bonds were employed for the dice microassembly. The active electrode array can deliver current pulses (up to 1 mA, 100 pulses per second) and supports interleaved stimulation with independent control of the stimulus parameters for each pulse. The stimulation timing and pulse duration are very versatile. The array was electrically characterized through impedance spectroscopy and voltage transient recordings. A prototype was tested for long term mechanical reliability when subjected to continuous bending. The results revealed no track or bond failure. To the best of the authors' knowledge, this is the first time that flexible active electrode arrays with embedded electronics suitable for implantation inside the rat's spinal canal have been proposed, developed and tested in vitro.

An Implantable Versatile Electrode-Driving ASIC for Chronic Epidural Stimulation in Rats.

This paper presents the design and testing of an electrode driving application specific integrated circuit (ASIC) intended for epidural spinal cord electrical stimulation in rats. The ASIC can deliver up to 1 mA fully programmable monophasic or biphasic stimulus current pulses, to 13 electrodes selected in any possible configuration. It also supports interleaved stimulation. Communication is achieved via only 3 wires. The current source and the control of the stimulation timing were kept off-chip to reduce the heat dissipation close to the spinal cord. The ASIC was designed in a 0.18- µm high voltage CMOS process. Its output voltage compliance can be up to 25 V. It features a small core area (<;0.36 mm(2)) and consumes a maximum of 114 µW during a full stimulation cycle. The layout of the ASIC was developed to be suitable for integration on the epidural electrode array, and two different versions were fabricated and electrically tested. Results from both versions were almost indistinguishable. The performance of the system was verified for different loads and stimulation parameters. Its suitability to drive a passive epidural 12-electrode array in saline has also been demonstrated.

A CMOS smart temperature and humidity sensor with combined readout.

A fully-integrated complementary metal-oxide semiconductor (CMOS) sensor for combined temperature and humidity measurements is presented. The main purpose of the device is to monitor the hermeticity of micro-packages for implanted integrated circuits and to ensure their safe operation by monitoring the operating temperature and humidity on-chip. The smart sensor has two modes of operation, in which either the temperature or humidity is converted into a digital code representing a frequency ratio between two oscillators. This ratio is determined by the ratios of the timing capacitances and bias currents in both oscillators. The reference oscillator is biased by a current whose temperature dependency is complementary to the proportional to absolute temperature (PTAT) current. For the temperature measurement, this results in an exceptional normalized sensitivity of about 0.77%/°C at the accepted expense of reduced linearity. The humidity sensor is a capacitor, whose value varies linearly with relative humidity (RH) with a normalized sensitivity of 0.055%/% RH. For comparison, two versions of the humidity sensor with an area of either 0.2 mm2 or 1.2 mm2 were fabricated in a commercial 0.18 µm CMOS process. The on-chip readout electronics operate from a 5 V power supply and consume a current of approximately 85 µA.

Improved Signal Processing Methods for Velocity Selective Neural Recording Using Multi-Electrode Cuffs.

This paper describes an improved system for obtaining velocity spectral information from electroneurogram recordings using multi-electrode cuffs (MECs). The starting point for this study is some recently published work that considers the limitations of conventional linear signal processing methods (`delay-and-add') with and without additive noise. By contrast to earlier linear methods, the present paper adopts a fundamentally non-linear velocity classification approach based on a type of artificial neural network (ANN). The new method provides a unified approach to the solution of the two main problems of the earlier delay-and-add technique, i.e., a damaging decline in both velocity selectivity and velocity resolution at high velocities. The new method can operate in real-time, is shown to be robust in the presence of noise and also to be relatively insensitive to the form of the action potential waveforms being classified.

An enhancement to velocity selective discrimination of neural recordings: extraction of neuronal firing rates.

This paper describes improvements to the theory of velocity selective recording (VSR) of neural signals. Action potentials are classified and differentiated based on their conduction velocities which can be calculated from concurrent neural recordings taking at different locations on a nerve. Existing work has focussed primarily on electrically evoked compound action potentials (CAPs) where only a single evoked response per velocity is recorded. This paper extends the theory of VSR to naturally occurring neural signals recorded from rat and attempts to identify the level of activity (firing rates) within particular velocity ranges.

Fibre-selective discrimination of physiological ENG using velocity selective recording: report on pilot rat experiments.

This paper presents results from a pilot experiment in which the technique of velocity selective recording (VSR) was used to identify naturally occurring electroneurogram (ENG) signals within the intact nerve of a rat. Signals were acquired using a set of electrodes placed along the length of the nerve, formed from simple wire hooks. This basic form of recording has already been applied in-vivo to the analysis of electrically excited compound action potentials (CAPs) in both pig and frog, however, this method has never before been used to identify naturally occurring neural signals. Results in this paper highlight challenges which must be overcome in order for the transition to be made from electrically evoked potentials to naturally occurring signals.

Fibre-selective recording from the peripheral nerves of frogs using a multi-electrode cuff.

OBJECTIVE: We investigate the ability of the method of velocity selective recording (VSR) to determine the fibre types that contribute to a compound action potential (CAP) propagating along a peripheral nerve. Real-time identification of the active fibre types by determining the direction of action potential propagation (afferent or efferent) and velocity might allow future neural prostheses to make better use of biological sensor signals and provide a new and simple tool for use in fundamental neuroscience. APPROACH: Fibre activity was recorded from explanted Xenopus Laevis frog sciatic nerve using a single multi-electrode cuff that records whole nerve activity with 11 equidistant ring-shaped electrodes. The recorded signals were amplified, delayed against each other with variable delay times, added and band-pass filtered. Finally, the resulting amplitudes were measured. MAIN RESULT: Our experiments showed that electrically evoked frog CAP was dominated by two fibre populations, propagating at around 20 and 40 m/s, respectively. The velocity selectivity, i.e. the ability of the system to discriminate between individual populations was increased by applying band-pass filtering. The method extracted an entire velocity spectrum from a 10 ms CAP recording sample in real time. SIGNIFICANCE: Unlike the techniques introduced in the 1970s and subsequently, VSR requires only a single nerve cuff and does not require averaging to provide velocity spectral information. This makes it potentially suitable for the generation of highly-selective real-time control-signals for future neural prostheses. In our study, electrically evoked CAPs were analysed and it remains to be proven whether the method can reliably classify physiological nerve traffic.