Stimulus artifact removal using a software-based two-stage peak detection algorithm

An Adaptive Spatial Filtering Method for Multi-Channel EMG Artifact Removal During Functional Electrical Stimulation With Time-Variant Parameters

Removing the stimulation artifacts evoked by the functional electrical stimulation (FES) in electromyogram (EMG) signals is a challenge. Previous researches on stimulation artifact removal have focused on FES modulation with time-constant parameters, which has limitations when there are time-variant parameters. Therefore, considering the synchronism of muscle activation induced by FES and the asynchronism of muscle activation induced by proprioceptive nerves, we proposed a novel adaptive spatial filtering method called G-S-G. It entails fusing the Gram-Schmidt orthogonalization (G-S) and Grubbs criterion (G) algorithms to remove the FES-evoked stimulation artifacts in multi-channel EMG signals. To verify this method, we constructed a series of simulation data by fusing the FES signal with time-variant parameters and the voluntary EMG (vEMG) signal, and applied the G-S-G method to remove any FES artifacts from the simulation data. After that, we calculated the root mean square (RMS) value for both preprocessed simulation data and the vEMG data, and then compared them. The simulation results showed that the G-S-G method was robust and effective at removing FES artifacts in simulated EMG signals, and the correlation coefficient between the preprocessed EMG data and the recorded vEMG data yielded a good performance, up to 0.87. Furthermore, we applied the proposed method to the experimental EMG data with FES-evoked stimulation artifact, and also achieved good performance with both the time-constant and time-variant parameters. This study provides a new and accessible approach to resolving the problem of removing FES-evoked stimulation artifacts.

Neurostimulation artifact removal for implantable sensors improves signal clarity and decoding of motor volition

As the demand for prosthetic limbs with reliable and multi-functional control increases, recent advances in myoelectric pattern recognition and implanted sensors have proven considerably advantageous. Additionally, sensory feedback from the prosthesis can be achieved via stimulation of the residual nerves, enabling closed-loop control over the prosthesis. However, this stimulation can cause interfering artifacts in the electromyographic (EMG) signals which deteriorate the reliability and function of the prosthesis. Here, we implement two real-time stimulation artifact removal algorithms, Template Subtraction (TS) and ε-Normalized Least Mean Squares (ε-NLMS), and investigate their performance in offline and real-time myoelectric pattern recognition in two transhumeral amputees implanted with nerve cuff and EMG electrodes. We show that both algorithms are capable of significantly improving signal-to-noise ratio (SNR) and offline pattern recognition accuracy of artifact-corrupted EMG signals. Furthermore, both algorithms improved real-time decoding of motor intention during active neurostimulation. Although these outcomes are dependent on the user-specific sensor locations and neurostimulation settings, they nonetheless represent progress toward bi-directional neuromusculoskeletal prostheses capable of multifunction control and simultaneous sensory feedback.

Isolating Transcutaneous Spinal Cord Stimulation Artifact to Identify Motor Response during Walking

The objective of this investigation was to demonstrate the applicability of a custom-developed EMD-Notch filtering algorithm to isolate the scTS-induced artifact from sEMG signals during walking in an individual with motor-incomplete SCI. Overall, the EMD-Notch filtering algorithm provides an effective approach to isolate the scTS artifact, extract the sEMG data, and further study the modulation of the spinal neuronal networks during dynamic activities.Clinical Relevance- This investigation will help with the modification of individualized scTS parameters to achieve task-specific neuromodulatory effects.

A 32-Channel Time-Multiplexed Artifact-Aware Neural Recording System

This paper presents a low-power, low-noise microsystem for the recording of neural local field potentials or intracranial electroencephalographic signals. It features 32 time-multiplexed channels at the electrode interface and offers the possibility to spatially delta encode data to take advantage of the large correlation of signals captured from nearby channels. The circuit also implements a mixed-signal voltage-triggered auto-ranging algorithm which allows to attenuate large interferers in digital domain while preserving neural information. This effectively increases the system dynamic range and avoids the onset of saturation. A prototype, fabricated in a standard 180 nm CMOS process, has been experimentally verified in-vitro with cellular cultures of primary cortical neurons from mice. The system shows an integrated input-referred noise in the 0.5-200 Hz band of 1.4 μV_rms for a spot noise of about 85 nV /√{Hz}. The system draws 1.5 μW per channel from 1.2 V supply and obtains 71 dB + 26 dB dynamic range when the artifact-aware auto-ranging mechanism is enabled, without penalising other critical specifications such as crosstalk between channels or common-mode and power supply rejection ratios.

A DSP Architecture for Distortion-Free Evoked Compound Action Potential Recovery in Neural Response Telemetry System

This paper presents a digital signal processing (DSP) architecture for real-time and distortion-free recovery of electrically-evoked compound action potentials (ECAPs) from stimulus artifacts and periodic noises in bidirectional neural response telemetry (NRT) system. In this DSP architecture, a low computation-cost bidirectional-filtered coherent averaging (BFCA) method is proposed for programmable linear-phase filtering of ECAPs, which can be easily combined with the alternating-polarity (AP) stimulation method to reject stimulus artifacts overlapped with ECAP responses. Design techniques including the configurable folded infinite-impulse response (IIR) filter and division-free averaging are also presented for efficient hardware implementation. Implemented in 180-nm CMOS process, the proposed DSP architecture consumes 10.03-mm² area and 2.35-mW post-layout simulated power. The efficacy of the DSP architecture in recovering ECAPs from recorded neural data contaminated by overlapped stimulus artifacts and periodic noises is validated in in-vivo electrical nerve stimulations. Experiment results show that compared with the previous coherent averaging technique, the proposed DSP architecture improves the signal-to-noise ratio (SNR) of ECAP responses by 11 dB and achieves a 3.1% waveform distortion that is 17.1× lower.

Peripheral and Central Adaptations After a Median Nerve Neuromobilization Program Completed by Individuals With Carpal Tunnel Syndrome: An Exploratory Mechanistic Study Using Musculoskeletal Ultrasound Imaging and Transcranial Magnetic Stimulation

OBJECTIVE

Neuromobilization exercises are increasingly advocated in the conservative management of individuals with carpal tunnel syndrome (CTS), as they may mitigate CTS-related signs and symptoms via potential peripheral (ie, musculoskeletal) and central (ie, neurophysiological) adaptations. However, the mechanisms underlying these adaptations have not been studied extensively. Hence, this exploratory and mechanistic study aims to evaluate the potential peripheral and central adaptations that may result in individuals with CTS who have completed a neuromobilization program.

METHODS

Fourteen individuals with CTS were evaluated before and 1 week after the completion of a 4-week neuromobilization program that incorporated median nerve sliding exercises. Pain and upper limb functional abilities were assessed using standardized questionnaires. The biological integrity and mechanical properties of the median nerve and the corticospinal excitability were quantified using musculoskeletal ultrasound imaging and transcranial magnetic stimulation, respectively.

RESULTS

Upon completion of the program, participants reported both large and moderate improvements in pain (P ≤ .03) and upper limb functional abilities (P = .02), respectively. The biological integrity and mechanical properties of the median nerve remained unchanged (P ≥ .22), whereas a small significant increase in corticospinal excitability (P = .04) was observed.

CONCLUSION

The proposed neuromobilization program appears promising to improve pain and upper limb functional abilities in individuals with CTS. These improvements may be preferentially mediated via central, rather than peripheral, adaptations. Future studies, especially with a larger sample size, longer intervention duration, and additional measurement times, are needed to strengthen current evidence.

A novel approach for removing micro-stimulation artifacts and reconstruction of broad-band neuronal signals

BACKGROUND

Electrical stimulation is a widely used method in the neurosciences with a variety of application fields. However, stimulation frequently induces large and long-lasting artifacts, which superimpose on the actual neuronal signal. Existing methods were developed for analyzing fast events such as spikes, but are not well suited for the restoration of LFP signals.

NEW METHOD

We developed a method that extracts artifact components while also leaving the LFP components of the neuronal signal intact. We based it on an exponential fit of the average artifact shape, which is subsequently adapted to the individual artifacts amplitude and then subtracted. Importantly, we used for fitting of the individual artifact only a short initial time window, in which the artifact is dominating the superimposition with the neuronal signal. Using this short period ensures that LFP components are not part of the fit, which leaves them unaffected by the subsequent artifact removal.

RESULTS

By using the method presented here, we could diminish the substantial distortions of neuronal signals caused by electrical stimulation to levels that were statistically indistinguishable from the original data. Furthermore, the effect of stimulation on the phases of γ- and β- oscillations was reduced by 85 and 75 %, respectively.

COMPARISON WITH EXISTING METHODS

This approach avoids signal loss as caused by methods cutting out artifacts and minimizes the distortion of the signal's temporal structure as compared to other approaches.

CONCLUSION

The method presented here allows for a successful reconstruction of broad-band signals.

A Method for Suppressing Electrical Stimulation Artifacts from Electromyography

When surface electromyography (EMG) signal is used in a real-time functional electrical stimulation (FES) system for feedback control, the artifact from electrical stimulation is a key challenge for EMG signal processing. To address this challenge, this study proposes a novel method to suppress stimulation artifacts in the EMG-driven closed-loop FES system. The proposed method is inspired by an experimental study that compares artifacts generated by electrical stimulations with different current intensities. It is found that (1) spikes of stimulation artifacts are susceptible to the current intensity and (2) tailing components are similar under different current intensities. Based on these observations, the proposed method combines the blanking and template subtracting strategies for suppressing stimulation artifact. The length of blanking window for suppressing the stimulation spike is adaptively determined by a spike detection algorithm and the first-order derivative analysis of signal. An autoregressive model is used to estimate the tailing part of stimulation artifact, which is an adaptive template for subtracting the artifact. The proposed method is evaluated on both semi-synthetic and experimental datasets. Verified on the semi-synthetic dataset, the proposed method achieves better performance than the classic blanking method. Validated on the experimental dataset, the proposed method substantially decreases the power of stimulation artifact in the EMG. These results indicate that the proposed method can effectively suppress the stimulation artifact while retains the useful EMG signal for an EMG-driven FES system.

Electrophysiology equipment for reliable study of kHz electrical stimulation

Characterizing the cellular targets of kHz (1-10 kHz) electrical stimulation remains a pressing topic in neuromodulation because expanding interest in clinical application of kHz stimulation has surpassed mechanistic understanding. The presumed cellular targets of brain stimulation do not respond to kHz frequencies according to conventional electrophysiology theory. Specifically, the low-pass characteristics of cell membranes are predicted to render kHz stimulation inert, especially given the use of limited-duty-cycle biphasic pulses. Precisely because kHz frequencies are considered supra-physiological, conventional instruments designed for neurophysiological studies such as stimulators, amplifiers and recording microelectrodes do not operate reliably at these high rates. Moreover, for pulsed waveforms, the signal frequency content is well above the pulse repetition rate. Thus, the very tools used to characterize the effects of kHz electrical stimulation may themselves be confounding factors. We illustrate custom equipment design that supports reliable electrophysiological recording during kHz-rate stimulation. Given the increased importance of kHz stimulation in clinical domains and compelling possibilities that mechanisms of actions may reflect yet undiscovered neurophysiological phenomena, attention to suitable performance of electrophysiological equipment is pivotal.

Recovery of early neural spikes from stimulation electrodes using a DC-coupled low gain high resolution data acquisition system

BACKGROUND

Neural responses to electrical stimulation provide valuable information to probe and study the network function. Especially, recording neural responses from the stimulated site provides improved neural interfacing method. However, it is difficult to measure short-delayed responses at the stimulated electrode due to the saturation of the amplifier after stimulation which is called "stimulus artifact". Despite the advances in handling stimulation artifacts, it is still very challenging to deal with the artifacts if one tries to stimulate and record from the same electrode.

NEW METHOD

In this paper, we developed a system consisting of 24 bit ADC and low gain DC-amplifier which allows us to record the entire responses including saturation-free stimulus artifact and neural responses with excellent resolution.

RESULTS

Our approach showed saturation-free recording after stimulation, which makes it possible to recover neural spike as early as in 2 ms at the stimulating electrode with digital elimination methods.

COMPARISON WITH EXISTING METHODS

With our system we could record neural signals after stimulation that was difficult with high gain and high pass filtered recording system due to amplifier saturation.

CONCLUSIONS

Our new system can enhance interface performance with its higher robustness and with simple system configuration.

Feasibility of Nitrogen Doped Ultrananocrystalline Diamond Microelectrodes for Electrophysiological Recording From Neural Tissue

Neural prostheses that can monitor the physiological state of a subject are becoming clinically viable through improvements in the capacity to record from neural tissue. However, a significant limitation of current devices is that it is difficult to fabricate electrode arrays that have both high channel counts and the appropriate electrical properties required for neural recordings. In earlier work, we demonstrated nitrogen doped ultrananocrystalline diamond (N-UNCD) can provide efficacious electrical stimulation of neural tissue, with high charge injection capacity, surface stability and biocompatibility. In this work, we expand on this functionality to show that N-UNCD electrodes can also record from neural tissue owing to its low electrochemical impedance. We show that N-UNCD electrodes are highly flexible in their application, with successful recordings of action potentials from single neurons in an in vitro retina preparation, as well as local field potential responses from in vivo visual cortex tissue. Key properties of N-UNCD films, combined with scalability of electrode array fabrication with custom sizes for recording or stimulation along with integration through vertical interconnects to silicon based integrated circuits, may in future form the basis for the fabrication of versatile closed-loop neural prostheses that can both record and stimulate.

ERAASR: an algorithm for removing electrical stimulation artifacts from multielectrode array recordings

OBJECTIVE

Electrical stimulation is a widely used and effective tool in systems neuroscience, neural prosthetics, and clinical neurostimulation. However, electrical artifacts evoked by stimulation prevent the detection of spiking activity on nearby recording electrodes, which obscures the neural population response evoked by stimulation. We sought to develop a method to clean artifact-corrupted electrode signals recorded on multielectrode arrays in order to recover the underlying neural spiking activity.

APPROACH

We created an algorithm, which performs estimation and removal of array artifacts via sequential principal components regression (ERAASR). This approach leverages the similar structure of artifact transients, but not spiking activity, across simultaneously recorded channels on the array, across pulses within a train, and across trials. The ERAASR algorithm requires no special hardware, imposes no requirements on the shape of the artifact or the multielectrode array geometry, and comprises sequential application of straightforward linear methods with intuitive parameters. The approach should be readily applicable to most datasets where stimulation does not saturate the recording amplifier.

MAIN RESULTS

The effectiveness of the algorithm is demonstrated in macaque dorsal premotor cortex using acute linear multielectrode array recordings and single electrode stimulation. Large electrical artifacts appeared on all channels during stimulation. After application of ERAASR, the cleaned signals were quiescent on channels with no spontaneous spiking activity, whereas spontaneously active channels exhibited evoked spikes which closely resembled spontaneously occurring spiking waveforms.

SIGNIFICANCE

We hope that enabling simultaneous electrical stimulation and multielectrode array recording will help elucidate the causal links between neural activity and cognition and facilitate naturalistic sensory protheses.

Signal processing methods for reducing artifacts in microelectrode brain recordings caused by functional electrical stimulation

OBJECTIVE

Functional electrical stimulation (FES) is a promising technology for restoring movement to paralyzed limbs. Intracortical brain-computer interfaces (iBCIs) have enabled intuitive control over virtual and robotic movements, and more recently over upper extremity FES neuroprostheses. However, electrical stimulation of muscles creates artifacts in intracortical microelectrode recordings that could degrade iBCI performance. Here, we investigate methods for reducing the cortically recorded artifacts that result from peripheral electrical stimulation.

APPROACH

One participant in the BrainGate2 pilot clinical trial had two intracortical microelectrode arrays placed in the motor cortex, and thirty-six stimulating intramuscular electrodes placed in the muscles of the contralateral limb. We characterized intracortically recorded electrical artifacts during both intramuscular and surface stimulation. We compared the performance of three artifact reduction methods: blanking, common average reference (CAR) and linear regression reference (LRR), which creates channel-specific reference signals, composed of weighted sums of other channels.

MAIN RESULTS

Electrical artifacts resulting from surface stimulation were 175  ×  larger than baseline neural recordings (which were 110 µV peak-to-peak), while intramuscular stimulation artifacts were only 4  ×  larger. The artifact waveforms were highly consistent across electrodes within each array. Application of LRR reduced artifact magnitudes to less than 10 µV and largely preserved the original neural feature values used for decoding. Unmitigated stimulation artifacts decreased iBCI decoding performance, but performance was almost completely recovered using LRR, which outperformed CAR and blanking and extracted useful neural information during stimulation artifact periods.

SIGNIFICANCE

The LRR method was effective at reducing electrical artifacts resulting from both intramuscular and surface FES, and almost completely restored iBCI decoding performance (>90% recovery for surface stimulation and full recovery for intramuscular stimulation). The results demonstrate that FES-induced artifacts can be easily mitigated in FES  +  iBCI systems by using LRR for artifact reduction, and suggest that the LRR method may also be useful in other noise reduction applications.

Modulating Lateral Geniculate Nucleus Neuronal Firing for Visual Prostheses: A Kalman Filter-Based Strategy

Developing visual prostheses that target inner brain structures along the visual pathway represent a new hope for patients with completely damaged early visual pathway sites. One of the major challenges in the development of subcortical and cortical visual prostheses is tuning electrical stimulation that could optimally induce desired visual percepts. In this paper, we propose a Kalman filter-based strategy that could be used to identify electrical stimulation patterns that mimic a specific visual input for thalamic visual prostheses. We demonstrate the performance of the proposed strategy using a population of lateral geniculate nucleus neurons modeled using an adapted generalized non-linear model. A mean correlation of 0.69 is obtained between visually evoked and electrically evoked responses-driven using the proposed strategy-for an optimal electrode-placement setup. In addition, we demonstrate the performance for a random electrode-placement setup in which a mean correlation of 0.26 is obtained. For this latter setup, our analysis reveals an inversely proportional relationship between the obtained correlation and the distance between each neuron and the nearest electrode. The proposed strategy could be thus utilized to tune and enhance the performance of thalamic visual prostheses as well as other prosthesis systems.

Changes in the electromechanical delay components during a fatiguing stimulation in human skeletal muscle: an EMG, MMG and force combined approach

PURPOSE

Peripheral fatigue involves electrochemical and mechanical mechanisms. An electromyographic, mechanomyographic and force combined approach may permit a kinetic evaluation of the changes at the synaptic, skeletal muscle fiber, and muscle-tendon unit level during a fatiguing stimulation.

METHODS

Surface electromyogram, mechanomyogram, force and stimulation current were detected from the gastrocnemius medialis muscle in twenty male participants during a fatiguing stimulation (twelve blocks of 35 Hz stimulations, duty cycle 9 s on/1 s off, duration 120 s). The total electromechanical delay and its three components (between stimulation current and electromyogram, synaptic component; between electromyogram and mechanomyogram signal onset, muscle fiber electrochemical component, and between mechanomyogram and force signal onset, mechanical component) were calculated. Interday reliability and sensitivity were determined.

RESULTS

After fatigue, peak force decreased by 48% (P < 0.05) and the total electromechanical delay and its synaptic, electrochemical and mechanical components lengthened from 25.8 ± 0.9, 1.47 ± 0.04, 11.2 ± 0.6, and 13.1 ± 1.3 ms to 29.0 ± 1.6, 1.56 ± 0.05, 12.4 ± 0.9, and 17.2 ± 0.6 ms, respectively (P < 0.05). During fatigue, the total electromechanical delay and the mechanical component increased significantly after the 40th second, and then remained stable. The synaptic and electrochemical components lengthened significantly after the 20th and 30th second, respectively. Interday reliability was high to very high, with an adequate level of sensitivity.

CONCLUSIONS

The kinetic evaluation of the delays during the fatiguing stimulation highlighted different onsets and kinetics, with the events at synaptic level being the first to reveal a significant elongation, followed by those at the intra-fiber level. The mechanical events, which were the most affected by fatigue, were the last to lengthen.

Human-FES Cooperative Control for Wrist Movement: A Preliminary Study

Functional electrical stimulation (FES) sometimes applies to patients with partial paralysis, so human voluntary control and FES control both exist. Our study aims to build a cooperative controller to achieve human-FES cooperation. This cooperative controller is formed by a classical FES controller and an impedance controller. The FES controller consists of a back propagation (BP) neural network-based feedforward controller and a PID-based feedback controller. The function of impedance controller is to convert volitional force/torque, which is estimated from a three-stage filter based on EMG, into additional angle. The additional angle can reduce the FES intensity in our cooperative controller, comparing to that in classical FES controller. Some assessment experiments are designed to test the performance of the cooperative controller.

A microcontroller platform for the rapid prototyping of functional electrical stimulation-based gait neuroprostheses

Functional electrical stimulation (FES) has been used over the last decades as a method to rehabilitate lost motor functions of individuals with spinal cord injury, multiple sclerosis, and post-stroke hemiparesis. Within this field, researchers in need of developing FES-based control solutions for specific disabilities often have to choose between either the acquisition and integration of high-performance industry-level systems, which are rather expensive and hardly portable, or develop custom-made portable solutions, which despite their lower cost, usually require expert-level electronic skills. Here, a flexible low-cost microcontroller-based platform for rapid prototyping of FES neuroprostheses is presented, designed for reduced execution complexity, development time, and production cost. For this reason, the Arduino open-source microcontroller platform was used, together with off-the-shelf components whenever possible. The developed system enables the rapid deployment of portable FES-based gait neuroprostheses, being flexible enough to allow simple open-loop strategies but also more complex closed-loop solutions. The system is based on a modular architecture that allows the development of optimized solutions depending on the desired FES applications, even though the design and testing of the platform were focused toward drop foot correction. The flexibility of the system was demonstrated using two algorithms targeting drop foot condition within different experimental setups. Successful bench testing of the device in healthy subjects demonstrated these neuroprosthesis platform capabilities to correct drop foot.

Suppression of stimulus artifact contaminating electrically evoked electromyography

BACKGROUND

Electrical stimulation of muscle or nerve is a very useful technique for understanding of muscle activity and its pathological changes for both diagnostic and therapeutic purposes. During electrical stimulation of a muscle, the recorded M wave is often contaminated by a stimulus artifact. The stimulus artifact must be removed for appropriate analysis and interpretation of M waves.

OBJECTIVES

The objective of this study was to develop a novel software based method to remove stimulus artifacts contaminating or superimposing with electrically evoked surface electromyography (EMG) or M wave signals.

METHODS

The multiple stage method uses a series of signal processing techniques, including highlighting and detection of stimulus artifacts using Savitzky-Golay filtering, estimation of the artifact contaminated region with Otsu thresholding, and reconstruction of such region using signal interpolation and smoothing. The developed method was tested using M wave signals recorded from biceps brachii muscles by a linear surface electrode array. To evaluate the performance, a series of semi-synthetic signals were constructed from clean M wave and stimulus artifact recordings with different degrees of overlap between them.

RESULTS

The effectiveness of the developed method was quantified by a significant increase in correlation coefficient and a significant decrease in root mean square error between the clean M wave and the reconstructed M wave, compared with those between the clean M wave and the originally contaminated signal. The validity of the developed method was also demonstrated when tested on each channel's M wave recording using a linear electrode array.

CONCLUSIONS

The developed method can suppress stimulus artifacts contaminating M wave recordings.

The effectiveness of FES-evoked EMG potentials to assess muscle force and fatigue in individuals with spinal cord injury

The evoked electromyographic signal (eEMG) potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES)-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05) between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI) population.

H-reflexes reduce fatigue of evoked contractions after spinal cord injury

INTRODUCTION

Neuromuscular electrical stimulation (NMES) over a muscle belly (mNMES) generates contractions predominantly through M-waves, while NMES over a nerve trunk (nNMES) can generate contractions through H-reflexes in people who are neurologically intact. We tested whether the differences between mNMES and nNMES are present in people with chronic motor-complete spinal cord injury and, if so, whether they influence contraction fatigue.

METHODS

Plantar-flexion torque and soleus electromyography were recorded from 8 participants. Fatigue protocols were delivered using mNMES and nNMES on separate days.

RESULTS

nNMES generated contractions that fatigued less than mNMES. Torque decreased the least when nNMES generated contractions, at least partly through H-reflexes (n = 4 participants; 39% decrease), and torque decreased the most when contractions were generated through M-waves, regardless of NMES site (nNMES 71% decrease, n = 4; mNMES, 73% decrease, n = 8).

CONCLUSIONS

nNMES generates contractions that fatigue less than mNMES, but only when H-reflexes contribute to the evoked contractions.

Ultrasound imaging and semi-automatic analysis of active muscle features in electrical stimulation by optical flow

Ultrasound imaging is an effective way to measure the muscle activity in electrical stimulation studies. However, it is a time consuming task to manually measure pennation angle and muscle thickness, which are the benchmark features to analyze muscle activity from the ultrasound imaging. In previous studies, the muscle features were measured by calculating optical flow of the pennation angle by using only fibers of a muscle from the ultrasound, without carefully considering moving muscle edges during active and passive contraction. Therefore, this study aimed to measure the pennation angle and muscle thickness by using the edges and fibers of a muscle in a quantitative way in a semi-automatic optical flow based approach. The results of the semi-automatic analysis were compared to that of manual measurement. Through the comparison, it is clear that the proposed algorithm could achieve higher accuracy in tracking the thickness and pennation angle for a sequence of ultrasound images.

Effects of fatigue on the electromechanical delay components in gastrocnemius medialis muscle

PURPOSE

Under electrically evoked contractions, the time interval between the onset of the stimulation pulse (Stim) and the beginning of force (F) development can be partitioned (Delay(TOT)), by an electromyographic (EMG), mechanomyographic (MMG) and F combined approach, into three components each containing different parts of the electrochemical and mechanical processes underlying neuromuscular activation and contraction. The aim of the study was to evaluate inter- and intra-operator reliability of the measurements and to assess the effects of fatigue on the different Delay(TOT) components.

METHODS

Sixteen participants underwent two sets of tetanic stimulations of the gastrocnemius medialis muscle, with 10 min of rest in between. After a fatiguing protocol of 120 s, tetanic stimulations were replicated. The same protocol was repeated on a different day. Stim, EMG, MMG and F signals were recorded during contraction. Delay(TOT) and its three components (between Stim and EMG, Δt Stim-EMG; between EMG and MMG, Δt EMG-MMG and between MMG and F, Δt MMG-F) were calculated.

RESULTS

Before fatigue, Delay(TOT), Δt Stim-EMG, Δt EMG-MMG and Δt MMG-F lasted 27.5 ± 0.9, 1.4 ± 0.1, 9.2 ± 0.5 and 16.8 ± 0.7 ms, respectively. Fatigue lengthened Delay(TOT), Δt Stim-EMG, Δt EMG-MMG and Δt MMG-F by 18, 7, 16 and 22 %, respectively. Δt Stim-EMG, Δt EMG-MMG and Δt MMG-F contributed to Delay(TOT) lengthening by 2, 27 and 71 %, respectively. Reliability was always from high to very high.

CONCLUSIONS

The combined approach allowed a reliable calculation of the three contributors to Delay(TOT). The effects of fatigue on each Delay(TOT) component could be precisely assessed.

Neuronal Responses in the Globus Pallidus during Subthalamic Nucleus Electrical Stimulation in Normal and Parkinson's Disease Model Rats

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been widely used as a treatment for the movement disturbances caused by Parkinson's disease (PD). Despite successful application of DBS, its mechanism of therapeutic effect is not clearly understood. Because PD results from the degeneration of dopamine neurons that affect the basal ganglia (BG) network, investigation of neuronal responses of BG neurons during STN DBS can provide informative insights for the understanding of the mechanism of therapeutic effect. However, it is difficult to observe neuronal activity during DBS because of large stimulation artifacts. Here, we report the observation of neuronal activities of the globus pallidus (GP) in normal and PD model rats during electrical stimulation of the STN. A custom artifact removal technique was devised to enable monitoring of neural activity during stimulation. We investigated how GP neurons responded to STN stimulation at various stimulation frequencies (10, 50, 90 and 130 Hz). It was observed that activities of GP neurons were modulated by stimulation frequency of the STN and significantly inhibited by high frequency stimulation above 50 Hz. These findings suggest that GP neuronal activity is effectively modulated by STN stimulation and strongly dependent on the frequency of stimulation.

Empirical mode decomposition as a tool to remove the function electrical stimulation artifact from surface electromyograms: preliminary investigation

Rectification of surface EMGs during electrical stimulations (ES) is still a problem to be solved. The broad band frequency components of ES artifact overlap with the EMG spectrum, make this task challenging. In this study, we investigate the potential use of empirical mode decomposition (EMD) method to remove the stimulus artifact from surface EMGs collected during such applications. We hypothesize that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic modes which can be used to isolate ES artifact. Basic EMD is tested on two signals - ES induced EMG and EMG of voluntary contractions added with simulated ES signal. The algorithm isolates the EMG from ES artifact with considerable success. Further, the EMD method along with the energy operator -TKEO gives even better representation of the EMG signal. However, some high frequency data was lost during reconstruction process. Hence, there is further need to investigate the relationship between the EMD parameters and stimulus artifact properties so that the algorithm can be optimized to reconstruct pure artifact free EMG signal with minimum lost of data.

A blink restoration system with contralateral EMG triggered stimulation and real-time artifact blanking

Patients suffering from facial paralysis are on the hazard of disfigurement and loss of vision due to loss of blink function. Functional-electrical stimulation (FES) is one possible way of restoring blink and other functions in these patients. A blink restoration system for uni-lateral facial paralyzed patients is described in this paper. The system achieves restoration of synchronized blink through processing the myoelectric signal of orbicularis oculi at the normal side in real-time as the trigger to stimulate the paralyzed eyelid. Design issues are discussed, including EMG processing, stimulating strategies and real-time artifact blanking. Two artifact removal approaches based on sample and hold and digital filtering technique are proposed and implemented. Finally, the whole system has been verified on rabbit models.

Temporal muscle activation assessment by ultrasound imaging during flexor withdrawal reflex and voluntary contraction

Activating flexor reflexes by electrical stimulation has been used as a mechanism to initiate the swing phase or to enhance it for spinal cord injured patients. However, it is necessary to know their contraction dynamics in order to artificially induce them at the right moment of a walking cycle. This requires understanding the temporal activation pattern of both surface and deep muscles simultaneously. This study aimed at developing a system to measure and analyze the temporal activation of both surface and deep muscles during voluntary contraction and flexor reflexes (also called withdrawal reflexes) using ultrasound imaging. A set of experiments were done to verify the validity of the system, while exploring the temporal pattern of muscle activation during flexor reflexes. As a result, we were able to quantify the surface and deep muscle activity by measuring the muscle thickness, pennation angle and long-axis displacement, from the ultrasound images.

An in vivo investigation of inferior colliculus single neuron responses to cochlear nucleus pulse train stimulation

The auditory brain stem implant (ABI) is being used clinically to restore hearing to patients unable to benefit from a cochlear implant (CI). Speech perception outcomes for ABI users are typically poor compared with most CI users. The ABI is implanted either on the surface of or penetrating through the cochlear nucleus in the auditory brain stem and uses stimulation strategies developed for auditory nerve stimulation with a CI. Although the stimulus rate may affect speech perception outcomes with current stimulation strategies, no studies have systematically investigated the effect of stimulus rate electrophysiologically or clinically. We therefore investigated rate response properties and temporal response properties of single inferior colliculus (IC) neurons from penetrating ABI stimulation using stimulus rates ranging from 100 to 1,600 pulses/s in the rat. We found that the stimulus rate affected the proportion of response types, thresholds, and dynamic ranges of IC activation. The stimulus rate was also found to affect the temporal properties of IC responses, with higher rates providing more temporally similar responses to acoustic stimulation. Suppression of neural firing and inhibition in IC neurons was also found, with response properties varying with the stimulus rate. This study demonstrated that changes in the ABI stimulus rate results in significant differences in IC neuron response properties. Due to electrophysiological differences, the stimulus rate may also change perceptual properties. We suggest that clinical evaluation of the ABI stimulus rate should be performed.

Motor unit recruitment when neuromuscular electrical stimulation is applied over a nerve trunk compared with a muscle belly: quadriceps femoris

Neuromuscular electrical stimulation (NMES) can be delivered over a nerve trunk or muscle belly and both can generate contractions through peripheral and central pathways. Generating contractions through peripheral pathways is associated with a nonphysiological motor unit recruitment order, which may limit the efficacy of NMES rehabilitation. Presently, we compared recruitment through peripheral and central pathways for contractions of the knee extensors evoked by NMES applied over the femoral nerve vs. the quadriceps muscle. NMES was delivered to evoke 10 and 20% of maximum voluntary isometric contraction torque 2–3 s into the NMES (time1) in two patterns: 1) constant frequency (15 Hz for 8 s); and 2) step frequency (15–100-15 Hz and 25–100-25 Hz for 3–2-3 s, respectively). Torque and electromyographic activity recorded from vastus lateralis and medialis were quantified at the beginning (time1) and end (time2; 6–7 s into the NMES) of each pattern. M-waves (peripheral pathway), H-reflexes, and asynchronous activity (central pathways) during NMES were quantified. Torque did not differ regardless of NMES location, pattern, or time. For both muscles, M-waves were ∼7–10 times smaller and H-reflexes ∼8–9 times larger during NMES over the nerve compared with over the muscle. However, unlike muscles studied previously, neither torque nor activity through central pathways were augmented following 100 Hz NMES, nor was any asynchronous activity evoked during NMES at either location. The coefficient of variation was also quantified at time2to determine the consistency of each dependent measure between three consecutive contractions. Torque, M-waves, and H-reflexes were most variable during NMES over the nerve. In summary, NMES over the nerve produced contractions with the greatest recruitment through central pathways; however, considering some of the limitations of NMES over the femoral nerve, it may be considered a good complement to, as opposed to a replacement for, NMES over the quadriceps muscle for maintaining muscle quality and reducing contraction fatigue during NMES rehabilitation.

Evoked EMG-based torque prediction under muscle fatigue in implanted neural stimulation

In patients with complete spinal cord injury, fatigue occurs rapidly and there is no proprioceptive feedback regarding the current muscle condition. Therefore, it is essential to monitor the muscle state and assess the expected muscle response to improve the current FES system toward adaptive force/torque control in the presence of muscle fatigue. Our team implanted neural and epimysial electrodes in a complete paraplegic patient in 1999. We carried out a case study, in the specific case of implanted stimulation, in order to verify the corresponding torque prediction based on stimulus evoked EMG (eEMG) when muscle fatigue is occurring during electrical stimulation. Indeed, in implanted stimulation, the relationship between stimulation parameters and output torques is more stable than external stimulation in which the electrode location strongly affects the quality of the recruitment. Thus, the assumption that changes in the stimulation-torque relationship would be mainly due to muscle fatigue can be made reasonably. The eEMG was proved to be correlated to the generated torque during the continuous stimulation while the frequency of eEMG also decreased during fatigue. The median frequency showed a similar variation trend to the mean absolute value of eEMG. Torque prediction during fatigue-inducing tests was performed based on eEMG in model cross-validation where the model was identified using recruitment test data. The torque prediction, apart from the potentiation period, showed acceptable tracking performances that would enable us to perform adaptive closed-loop control through implanted neural stimulation in the future.

High-frequency electrical stimulation in the nucleus accumbens of morphine-treated rats suppresses neuronal firing in reward-related brain regions

Background

Previous studies have reported that high-frequency stimulation (HFS) in the nucleus accumbens (NAc) is a potential treatment modality for drug craving and relapse. We aimed to explore the electrophysiological changes in reward-related brain regions during NAc stimulation and reveal the effects of stimulation frequency and target changes on NAc neuronal activities.

Material/Methods

Twenty-eight rats were randomized into saline (n=8) and morphine (n=20) groups. The morphine group was further divided into core (n=10, only the core of the NAc was stimulated) and shell (n=10, only the shell of the NAc was stimulated) subgroups. Conditioned place preference (CPP) behavior of the rats was evaluated to confirm morphine preference after morphine injection and CPP training for 10 days. We recorded NAc neuronal responses to NAc core stimulation at different frequencies, as well as changes in VP and VTA neuronal firing during NAc core stimulation, and changes in NAc neuronal firing during NAc shell stimulation.

Results

The results indicate that high frequency stimulation was more effective in suppressing NAc neuronal activities than low frequency stimulation and that core stimulation was more effective than shell stimulation. Most VP neurons were inhibited by NAc core stimulation, while VTA neurons were not.

Conclusions

The results suggest that electrical stimulation in the NAc can suppress neuronal firing in reward-related brain regions. The stimulation might be frequency- dependent in suppressing neuronal firing. The core and shell of the NAc play different roles in suppressing NAc neuronal firing as 2 stimulating targets.

A novel device to suppress electrical stimulus artifacts in electrophysiological experiments

Electrophysiological studies of the effects of electrical brain stimulation have to contend with stimulus artifacts, which complicate both the maintenance of recorded neuron waveforms at recording time, and the post-hoc analysis of the data. The artifacts can be removed by digitally averaging some or all of the (stereotypic) artifact waveforms across artifacts, and then subtracting the resulting template from the recorded waveform at the time of artifact production. Available software-based approaches to this problem are effective but time consuming, and do not help with the problem of maintaining the recording quality at recording time. Alternative hardware-based methods are effective as well, but relatively inflexible and very expensive. We here provide a detailed description of a simple high-performance artifact removal device based on a multi-processor microcontroller as well as analog-to-digital and digital-to-analog converters. This device provides the benefits of self-adapting online-removal of stimulus artifacts for a fraction of the price of the commercially available devices. The device is fully customizable, and can be easily adjusted to various stimulation conditions, as well as AC line noise removal.

A mixed FES/EMG system for real time analysis of muscular fatigue

In this article, we present a functional electrical stimulator allowing the extraction in real time of M-wave characteristics from resulting EMG recodings in order to quantify muscle fatigue. This system is composed of three parts. A Labview software managing the stimulation output and electromyogram (EMG) input signal, a hardware part amplifying the output and input signal and a link between the two previous parts which is made up from input/output module (NIdaq USB 6251). In order to characterize the fatigue level, the Continuous Wavelet Transform is applied yielding a local maxima detection. The fatigue is represented on a scale from 0 for a fine shaped muscle to 100 for a very tired muscle. Premilary results are given.

Generalized framework for stimulus artifact removal

Stimulation is extensively used in neuroscience research in diverse fields ranging from cognitive to clinical. Studying the effect of electrical and magnetic stimulation on neuronal activity is complicated by large stimulation-derived artifacts on the recording electrodes, which mask the spiking activity. Multiple studies have suggested a variety of solutions for the removal of artifacts and were typically directed at specific stimulation setups. In this study we introduce a generalized framework for stimulus artifacts removal, the Stimulus Artifact Removal Graphical Environment (SARGE). The framework provides an encapsulated environment for a multi-stage removal process, starting from the stimulus pulse detection, through estimation of the artifacts and their removal, and finally to signal reconstruction and the assessment of removal quality. The framework provides the user with subjective graphical and objective quantitative tools for assessing the resulting signal, and the ability to adjust the process to optimize the results. This extendable publicly available framework supports different types of stimulation, stimulation patterns and shapes, and a variety of artifact estimation methods. We exemplify the removal of artifacts generated by electrical micro- and macro-stimulation and magnetic stimulation and different stimulation protocols. The use of different estimation methods, such as averaging and function fitting is demonstrated, and the differences between them are discussed. Finally, the quality of removal is assessed and validated using quantitative measures and combined experimental-simulation studies. The framework marks a shift from "algorithm" and "data" centric approach to a "workflow" centric approach, thus introducing an innovative concept to the artifact removal process.

Reducing blanking artifact in electrically evoked compound action potentials

The main source of distortion in the recording of the electrically evoked compound action potentials is the stimulus artifact. The popular hardware blanking technique tends to reduce this artifact, but generates a blanking artifact as a consequence of the transient state in the amplifier. In this paper we propose two techniques to deal with the blanking artifact. The proposed techniques are combined with conventional and generalized alternating stimulation in order to reduce both stimulus and blanking artifacts in the recording of the evoked potentials. A comparison over 126 evoked potential recordings reveals that the proposed blanking artifact reduction methods improve the quality of electrically evoked compound action potential recordings.

Influence of evoked response latency and amplitude on stimulus artifact removal

The removal of stimulus artifacts is a challenge not only to evoked potentials but also to other electrically-elicited signals such as M wave and direct cortical responses. Several techniques try to remove stimulus artifacts. However, the influence of the amplitude ratio between signal and artifact has not been reported yet. Neither has been the effect of the delay between stimulus and signal. So, this work aimed to study the relationship between the evoked response's parameters (amplitude; latency) and the associated errors, for several amplitude ratios and delays between stimulus artifact and evoked response simulation models. In order to do so, the evoked responses were represented by a mathematical function with varying amplitudes and latencies. The stimulus artifacts were represented by the concatenation of a rectangular bipolar pulse and three exponential functions. Reasonable results were obtained for these models, whenever the amplitude ratio between evoked response and artifact was between 5% and 40%, and the evoked response's latency was within the range of 3ms to 8ms. These results showed that the technique has the potential to contribute to stimulus artifact removal on somatosensory evoked potentials recorded at the elbow, for both wrist and hand stimulation of the median nerve.

Filtering Out Deep Brain Stimulation Artifacts Using a Nonlinear Oscillatory Model

This letter is devoted to the suppression of spurious signals (artifacts) in records of neural activity during deep brain stimulation. An approach based on nonlinear adaptive model with self-oscillations is proposed. We developed an algorithm of adaptive filtering based on this approach. The proposed algorithm was tested using recordings collected from patients during the stimulation. This was then compared to existing methods and showed the best performance.

Complete optical neurophysiology: toward optical stimulation and recording of neural tissue

Direct optical methods to stimulate and record neural activity provide artifact-free, noninvasive, and noncontact neurophysiological procedures. For stimulation, focused mid-infrared light alters membrane potential and activates individual neural processes. Simultaneous intrinsic scattered light parameters, including birefringence changes, can record neural activity with signals similar to potentiometric dyes. The simultaneous combination of optical stimulation and optical recording techniques provide the potential for powerful tools that may someday remove the need for invasive wires during electrophysiological recordings.