Measurement of the performance of nerve cuff electrodes for recording

Computational models of compound nerve action potentials: Efficient filter-based methods to quantify effects of tissue conductivities, conduction distance, and nerve fiber parameters

BACKGROUND

Peripheral nerve recordings can enhance the efficacy of neurostimulation therapies by providing a feedback signal to adjust stimulation settings for greater efficacy or reduced side effects. Computational models can accelerate the development of interfaces with high signal-to-noise ratio and selective recording. However, validation and tuning of model outputs against in vivo recordings remains computationally prohibitive due to the large number of fibers in a nerve.

METHODS

We designed and implemented highly efficient modeling methods for simulating electrically evoked compound nerve action potential (CNAP) signals. The method simulated a subset of fiber diameters present in the nerve using NEURON, interpolated action potential templates across fiber diameters, and filtered the templates with a weighting function derived from fiber-specific conduction velocity and electromagnetic reciprocity outputs of a volume conductor model. We applied the methods to simulate CNAPs from rat cervical vagus nerve.

RESULTS

Brute force simulation of a rat vagal CNAP with all 1,759 myelinated and 13,283 unmyelinated fibers in NEURON required 286 and 15,860 CPU hours, respectively, while filtering interpolated templates required 30 and 38 seconds on a desktop computer while maintaining accuracy. Modeled CNAP amplitude could vary by over two orders of magnitude depending on tissue conductivities and cuff opening within experimentally relevant ranges. Conduction distance and fiber diameter distribution also strongly influenced the modeled CNAP amplitude, shape, and latency. Modeled and in vivo signals had comparable shape, amplitude, and latency for myelinated fibers but not for unmyelinated fibers.

CONCLUSIONS

Highly efficient methods of modeling neural recordings quantified the large impact that tissue properties, conduction distance, and nerve fiber parameters have on CNAPs. These methods expand the computational accessibility of neural recording models, enable efficient model tuning for validation, and facilitate the design of novel recording interfaces for neurostimulation feedback and understanding physiological systems.

Assessment of the Factors Influencing the Recording Performance of Circumneural Electrodes

The quality of recorded peripheral nerve signals is decisive for their application in therapies. The electroneurogram can be recorded via implantable circumeural electrodes that are wrapped around the peripheral nerve. The shape and amplitude of the signal recorded by the electrode are influenced by the design and contact configuration of the electrode. In this paper, the impact of the number of contacts, contact size and electrical insulation to the outside is investigated to predict the single fiber action potential based on the measured impedance data.

Printable microscale interfaces for long-term peripheral nerve mapping and precision control

The nascent field of bioelectronic medicine seeks to decode and modulate peripheral nervous system signals to obtain therapeutic control of targeted end organs and effectors. Current approaches rely heavily on electrode-based devices, but size scalability, material and microfabrication challenges, limited surgical accessibility, and the biomechanically dynamic implantation environment are significant impediments to developing and deploying peripheral interfacing technologies. Here, we present a microscale implantable device - the nanoclip - for chronic interfacing with fine peripheral nerves in small animal models that begins to meet these constraints. We demonstrate the capability to make stable, high signal-to-noise ratio recordings of behaviorally-linked nerve activity over multi-week timescales. In addition, we show that multi-channel, current-steering-based stimulation within the confines of the small device can achieve multi-dimensional control of a small nerve. These results highlight the potential of new microscale design and fabrication techniques for realizing viable devices for long-term peripheral interfacing.

Interfacing with the nervous system: a review of current bioelectric technologies

The aim of this study is to discuss the state of the art with regard to established or promising bioelectric therapies meant to alter or control neurologic function. We present recent reports on bioelectric technologies that interface with the nervous system at three potential sites-(1) the end organ, (2) the peripheral nervous system, and (3) the central nervous system-while exploring practical and clinical considerations. A literature search was executed on PubMed, IEEE, and Web of Science databases. A review of the current literature was conducted to examine functional and histomorphological effects of neuroprosthetic interfaces with a focus on end-organ, peripheral, and central nervous system interfaces. Innovations in bioelectric technologies are providing increasing selectivity in stimulating distinct nerve fiber populations in order to activate discrete muscles. Significant advances in electrode array design focus on increasing selectivity, stability, and functionality of implantable neuroprosthetics. The application of neuroprosthetics to paretic nerves or even directly stimulating or recording from the central nervous system holds great potential in advancing the field of nerve and tissue bioelectric engineering and contributing to clinical care. Although current physiotherapeutic and surgical treatments seek to restore function, structure, or comfort, they bear significant limitations in enabling cosmetic or functional recovery. Instead, the introduction of bioelectric technology may play a role in the restoration of function in patients with neurologic deficits.

Model-based Bayesian signal extraction algorithm for peripheral nerves

OBJECTIVE

Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time.

APPROACH

To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms.

MAIN RESULTS

The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity.

SIGNIFICANCE

HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of controlling a prosthetic limb.

A phantom axon setup for validating models of action potential recordings

Electrode designs and strategies for electroneurogram recordings are often tested first by computer simulations and then by animal models, but they are rarely implanted for long-term evaluation in humans. The models show that the amplitude of the potential at the surface of an axon is higher in front of the nodes of Ranvier than at the internodes; however, this has not been investigated through in vivo measurements. An original experimental method is presented to emulate a single fiber action potential in an infinite conductive volume, allowing the potential of an axon to be recorded at both the nodes of Ranvier and the internodes, for a wide range of electrode-to-fiber radial distances. The paper particularly investigates the differences in the action potential amplitude along the longitudinal axis of an axon. At a short radial distance, the action potential amplitude measured in front of a node of Ranvier is two times larger than in the middle of two nodes. Moreover, farther from the phantom axon, the measured action potential amplitude is almost constant along the longitudinal axis. The results of this new method confirm the computer simulations, with a correlation of 97.6 %.

Innovations in prosthetic interfaces for the upper extremity

Advancements in modern robotic technology have led to the development of highly sophisticated upper extremity prosthetic limbs. High-fidelity volitional control of these devices is dependent on the critical interface between the patient and the mechanical prosthesis. Recent innovations in prosthetic interfaces have focused on several control strategies. Targeted muscle reinnervation is currently the most immediately applicable prosthetic control strategy and is particularly indicated in proximal upper extremity amputations. Investigation into various brain interfaces has allowed acquisition of neuroelectric signals directly or indirectly from the central nervous system for prosthetic control. Peripheral nerve interfaces permit signal transduction from both motor and sensory nerves with a higher degree of selectivity. This article reviews the current developments in each of these interface systems and discusses the potential of these approaches to facilitate motor control and sensory feedback in upper extremity neuroprosthetic devices.

Transverse versus longitudinal tripolar configuration for selective stimulation with multipolar cuff electrodes

The ability to stimulate subareas of a nerve selectively is highly desirable, since it has the potential of simplifying surgery to implanting one cuff on a large nerve instead of many cuffs on smaller nerves or muscles, or alternatively can improve function where surgical access to the smaller nerves is limited. In this paper, stimulation was performed with a four-channel multipolar cuff electrode implanted on the sciatic nerve of nine rabbits to compare the extensively researched longitudinal tripolar configuration with the transverse tripolar configuration, which has received less interest. The performance of these configurations was evaluated in terms of selectivity in recruitment of the three branches of the sciatic nerve. The results showed that the transverse configuration was able to selectively activate the sciatic nerve branches to a functionally relevant level in more cases than the longitudinal configuration (20/27 versus 11/27 branches) and overall achieved a higher mean selectivity [0.79 ± 0.13 versus 0.61 ± 0.09 (mean ± standard deviation)]. The transverse configuration was most successful at recruiting the small cutaneous and medium-sized peroneal branches, and less successful at recruiting the large tibial nerve.

Tripolar-cuff deviation from ideal model: Assessment by bioelectric field simulations and saline-bath experiments

Ideally, interference in neural measurements due to signals from nearby muscles can be completely eliminated with the use of tripolar cuffs, in combination with appropriate amplifier configurations, such as the quasi-tripole (QT) and the true-tripole (TT). The operation of these amplifiers, is based on the theoretical property of the nerve cuff to produce a linear relationship of potential versus distance along its length, internally, when external potentials appear between its ends. Thus, in principle, electroneurogram (ENG) recordings from an ideal tripolar cuff would be free from electromyogram (EMG) interference generated by nearby muscles. However, in practice the cuff exhibits non-ideal behaviour leading to "cuff imbalance". The main focus of this paper is to investigate the causes of cuff imbalance, to demonstrate that it should be incorporated as a main parameter in the theoretical ENG-recording cuff electrode model. In addition to cuff asymmetry and tissue growth, the proximity of the interference source to the cuff is shown to result in cuff imbalance. The influence of proximity imbalance on the performance of the QT and TT amplifiers is also considered. Proximity imbalance is studied using bioelectric field simulations and saline-bath experiments. Variation is observed with both distance (40 mm and 70 mm was examined) and orientation (0-180 degrees), with the latter causing a more severe effect especially when the source dipole and the cuff are vertical to each other. The simulations and measurements are in close agreement. Tissue growth imbalance and asymmetry imbalance are also investigated in vitro. Finally, the signal-to-interference ratio (SIR; ENG/EMG) of the QT and TT amplifiers is examined in the presence of cuff imbalance. It is shown that proximity imbalance results in their SIR to peak only at certain cuff orientation values. This important finding offers an insight as to why in practice ENG recordings using these amplifiers have been widely reported to be degraded by EMG interference.

Model-based evaluation of the short-circuited tripolar cuff configuration

Recordings of neural information for use as feedback in functional electrical stimulation are often contaminated with interfering signals from muscles and from stimulus pulses. The cuff electrode used for the neural recording can be optimized to improve the S/I ratio. In this work, we evaluate a model of both the nerve signal and the interfering signals recorded by a cuff, and subsequently use this model to study the signal to interference ratio of different cuff designs and to evaluate a recently introduced short-circuited tripolar cuff configuration. The results of the model showed good agreement with results from measurements in rabbits and confirmed the superior performance of the short-circuited tripolar configuration as compared with the traditionally used tripolar configuration.

Hardware-in-the-loop simulation and analysis of magnetic recording of nerve activity

The focus of the reported research was on examination of properties of a special toroidal arrangement for magnetic recording of nerve activity. Toroidal high permeability coil placed around a nerve trunk can be used to record voltage induced by magnetic field generated by ionic nerve currents associated with propagating action potentials. The properties were examined in hardware-in-the-loop simulations that were used to identify the input-output relationship of the recording arrangement in case of different simulated intra-axonal current amplitudes and conduction velocities. Based on the recorded data, a nonlinear dynamical model (Wiener model) of the recording arrangement was identified, and subsequently used for predicting the voltage waveform expected in actual magnetic recording. This waveform was also used to estimate the potential of the method with the respect to obtainable signal quality (signal-to-noise (S/N) ratios). The manuscript also contains new theoretical results for sensitivity of toroidal and electroneurographic recording arrangements to different disturbances like, for example, EMG pickup. It can be concluded that high S/N ratios, short length, and superior disturbance rejection of the toroidal magnetic recording arrangement can make magnetic recording an attractive alternative to acute and chronic electroneurographic recording techniques.

On Cuff Imbalance and Tripolar ENG Amplifier Configurations

Electroneurogram (ENG) recording techniques benefit from the use of tripolar cuffs because they assist in reducing interference from sources outside the cuff. However, in practice the performance of ENG amplifier configurations, such as the quasi-tripole and the true-tripole, has been widely reported to be degraded due to the departure of the tripolar cuff from ideal behavior. This paper establishes the presence of cuff imbalance and investigates its relationship to cuff asymmetry, cuff end-effects and interference source proximity. The paper also presents a comparison of the aforementioned amplifier configurations with a new alternative, termed the adaptive-tripole, developed to automatically compensate for cuff imbalance. The output signal-to-interference ratio of the three amplifier configurations were compared in vivo for two interference signals (stimulus artifact and M-wave) superimposed on compound action potentials. The experiments showed (for the first time) that the two interference signals result in different cuff imbalance values. Nevertheless, even with two distinct cuff imbalances present, the adaptive-tripole performed better than the other two systems in 61.9% of the trials.

Artefact reduction with alternative cuff configurations

In nerve cuff electrode recordings of neural signals, the pick-up of interfering signals can be reduced by choosing appropriate cuff configurations. In the traditionally used tripolar configuration, short circuiting of the end electrodes is expected to reduce the field inside the cuff from interfering signals. A model study suggests that moving the end electrodes toward the center of the cuff reduces the pick-up of interfering signals. In this paper, these properties are studied in more detail using a rabbit model. In addition, a new cuff configuration is suggested, which has an additional set of short circuited end electrodes. The total improvement of signal-to-noise ratio in the new configuration as compared with the traditionally used tripolar configuration was 73% for muscle signals and 127% for the stimulus pulse.

Signal strength versus cuff length in nerve cuff electrode recordings

When a nerve cuff electrode is used for the recording of signals from peripheral nerves, cuff dimensions have to be chosen. Traditionally, the peak-to-peak amplitude of the single-fiber action potential (SFAP) is optimized through the choice of cuff diameter and cuff length. In this paper, the dependency of the root-mean-square (RMS) value of the nerve signal on the cuff dimensions was studied and compared with the peak-to-peak value of the SFAP. A simple approximation for signal optimization by cuff dimensioning is suggested. The results were obtained from modeled SFAPs and from the electroneurogram (ENG) created by superimposed SFAPs, obtained from an inhomogeneous volume conductor model. The results show that the RMS value of the nerve signal is considerably more sensitive to the cuff length than the SFAP peak-to-peak amplitude, and that the RMS of the ENG is a linear function of the fiber diameter.