First-In-Human Demonstration of High Frequency Electrical Motor Nerve Block: Case Report.

ABSTRACT: This feasibility study tested the capability of high frequency stimulation (HFS) to block muscle contractions elicited by electrical stimulation of the same nerve proximally. During a tendon lengthening surgery in the forearm, the anterior interosseous nerve (AIN) was exposed. A specialized nerve cuff electrode was placed around the nerve, and a stimulating probe held on the nerve 1 cm proximal to the cuff electrode delivered pulses of current causing the pronator quadratus muscle to contract. Through the cuff electrode, 20 kHz HFS was delivered to the nerve for 10 seconds during proximal stimulation. HFS amplitudes between 5 and 10 mA peak-to-peak were tested to determine which produced complete and partial block of the electrically induced contractions. The minimum HFS amplitude that produced complete block was 8 mA, with lower amplitudes producing partial block. In all trials, muscle contractions resumed immediately after HFS was turned off. This demonstration of high frequency electrical nerve block is a milestone in the road to clinical implementation of HFS mediated motor block for spasticity.

Δ BP-Net: Monitoring "Changes" in Blood Pressure Using PPG with Self-contrastive Masking.

Estimating blood pressure (BP) values from physiological signals (e.g., photoplethysmogram (PPG)) using deep learning models has recently received increased attention, yet challenges remain in terms of models' generalizability. Here, we propose taking a new approach by framing the problem as tracking the "changes" in BP over an interval, rather than directly estimating its value. Indeed, continuous monitoring of acute changes in BP holds promising implications for clinical applications (e.g., hypertensive emergencies). As a solution, we first present a self-contrastive masking (SCM) model, designed to perform pair-wise temporal comparisons within the input signal. We then leverage the proposed SCM model to introduce ΔBPNet, a model trained to detect elevations/drops greater than a given threshold in the systolic blood pressure (SBP) over an interval, from PPG. Using data from PulseDB, 1) we evaluate the performance of ΔBP-Net on previously unseen subjects, 2) we test ΔBP-Net's ability to generalize across domains by training and testing on different datasets, and 3) we compare the performance of ΔBP-Net with existing PPG-based BP-estimation models in detecting over-threshold SBP changes. Formulating the problem as a binary classification task (i.e., over-threshold SBP elevation/ drop or not), ΔBP-Net achieves 75.97%/73.19% accuracy on data from subjects unseen during training. Additionally, the proposed ΔBP-Net outperforms ΔSBP estimations derived from existing PPG-based BP-estimation methods. Overall, by shifting the focus from estimating the value of SBP to detecting overthreshold "changes" in SBP, this work introduces a new potential for using PPG in clinical BP monitoring, and takes a step forward in addressing the challenges related to the generalizability of PPG-based BP-estimation models.

Demographic Information Fusion Using Attentive Pooling In CNN-GRU Model For Systolic Blood Pressure Estimation.

Fusing demographic information into deep learning models has become of interest in recent end-to-end cuff-less blood pressure (BP) estimation studies in order to achieve improved performance. Conventionally, the demographic feature vector is concatenated with the pooled embedding vector. Here, using an attention-based convolutional neural network-gated recurrent unit (CNN-GRU), we present a new approach and fuse the demographic information into the attentive pooling module. Our results demonstrate that, under calibration-based testing protocol, the proposed approach provides improved systolic blood pressure (SBP) estimation accuracy (with R2=0.86 and mean absolute error (MAE)=4.90 mmHg) compared to both the baseline model with no demographic information fused, and the conventional approach of fusing demographic information. Our work showcases the feasibility of using attention-based methods to combine demographic features with deep learning models, and suggests new ways for fusing demographic information in deep learning models to achieve improved BP estimation accuracy.

Restoring continuous finger function with temporarily paralyzed nonhuman primates using brain-machine interfaces.

Objective.Brain-machine interfaces (BMIs) have shown promise in extracting upper extremity movement intention from the thoughts of nonhuman primates and people with tetraplegia. Attempts to restore a user's own hand and arm function have employed functional electrical stimulation (FES), but most work has restored discrete grasps. Little is known about how well FES can control continuous finger movements. Here, we use a low-power brain-controlled functional electrical stimulation (BCFES) system to restore continuous volitional control of finger positions to a monkey with a temporarily paralyzed hand.Approach.We delivered a nerve block to the median, radial, and ulnar nerves just proximal to the elbow to simulate finger paralysis, then used a closed-loop BMI to predict finger movements the monkey was attempting to make in two tasks. The BCFES task was one-dimensional in which all fingers moved together, and we used the BMI's predictions to control FES of the monkey's finger muscles. The virtual two-finger task was two-dimensional in which the index finger moved simultaneously and independently from the middle, ring, and small fingers, and we used the BMI's predictions to control movements of virtual fingers, with no FES.Main results.In the BCFES task, the monkey improved his success rate to 83% (1.5 s median acquisition time) when using the BCFES system during temporary paralysis from 8.8% (9.5 s median acquisition time, equal to the trial timeout) when attempting to use his temporarily paralyzed hand. In one monkey performing the virtual two-finger task with no FES, we found BMI performance (task success rate and completion time) could be completely recovered following temporary paralysis by executing recalibrated feedback-intention training one time.Significance.These results suggest that BCFES can restore continuous finger function during temporary paralysis using existing low-power technologies and brain-control may not be the limiting factor in a BCFES neuroprosthesis.

Neuroprosthesis for individuals with spinal cord injury.

OBJECTIVE: Individuals who sustain a traumatic spinal cord injury (SCI) often have a loss of multiple body systems. Significant functional improvement can be gained by individual SCI through the use of neuroprostheses based on electrical stimulation. The most common actions produced are grasp, overhead reach, trunk posture, standing, stepping, bladder/bowel/sexual function, and respiratory functions. METHODS: We review the fundamental principles of electrical stimulation, which are established, allowing stimulation to be safely delivered through implanted devices for many decades. We review four common clinical applications for SCI, including grasp/reach, standing/stepping, bladder/bowel function, and respiratory functions. Systems used to implement these functions have many common features, but are also customized based on the functional goals of each approach. Further, neuroprosthetic systems are customized based on the needs of each user. RESULTS & CONCLUSION: The results to date show that implanted neuroprostheses can have a significant impact on the health, function, and quality of life for individuals with SCI. A key focus for the future is to make implanted neuroprostheses broadly available to the SCI population.

PulseDB: A large, cleaned dataset based on MIMIC-III and VitalDB for benchmarking cuff-less blood pressure estimation methods.

There has been a growing interest in developing cuff-less blood pressure (BP) estimation methods to enable continuous BP monitoring from electrocardiogram (ECG) and/or photoplethysmogram (PPG) signals. The majority of these methods have been evaluated using publicly-available datasets, however, there exist significant discrepancies across studies with respect to the size, the number of subjects, and the applied pre-processing steps for the data that is eventually used for training and testing the models. Such differences make conducting performance comparison across models largely unfair, and mask the generalization capability of various BP estimation methods. To fill this important gap, this paper presents "PulseDB," the largest cleaned dataset to date, for benchmarking BP estimation models that also fulfills the requirements of standardized testing protocols. PulseDB contains 1) 5,245,454 high-quality 10 -s segments of ECG, PPG, and arterial BP (ABP) waveforms from 5,361 subjects retrieved from the MIMIC-III waveform database matched subset and the VitalDB database; 2) subjects' identification and demographic information, that can be utilized as additional input features to improve the performance of BP estimation models, or to evaluate the generalizability of the models to data from unseen subjects; and 3) positions of the characteristic points of the ECG/PPG signals, making PulseDB directly usable for training deep learning models with minimal data pre-processing. Additionally, using this dataset, we conduct the first study to provide insights about the performance gap between calibration-based and calibration-free testing approaches for evaluating generalizability of the BP estimation models. We expect PulseDB, as a user-friendly, large, comprehensive and multi-functional dataset, to be used as a reliable source for the evaluation of cuff-less BP estimation methods.

Cuff-Less Blood Pressure Estimation From Photoplethysmography via Visibility Graph and Transfer Learning.

This paper presents a new solution that enables the use of transfer learning for cuff-less blood pressure (BP) monitoring via short duration of photoplethysmogram (PPG). The proposed method estimates BP with low computational budget by 1) creating images from segments of PPG via visibility graph (VG), hence, preserving the temporal information of the PPG waveform, 2) using pre-trained deep convolutional neural network (CNN) to extract feature vectors from VG images, and 3) solving for the weights and bias between the feature vectors and the reference BPs with ridge regression. Using the University of California Irvine (UCI) database consisting of 348 records, the proposed method achieves a best error performance of 0.00±8.46 mmHg for systolic blood pressure (SBP), and -0.04±5.36 mmHg for diastolic blood pressure (DBP), respectively, in terms of the mean error (ME) and the standard deviation (SD) of error, ranking grade B for SBP and grade A for DBP under the British Hypertension Society (BHS) protocol. Our novel data-driven method offers a computationally-efficient end-to-end solution for rapid and user-friendly cuff-less PPG-based BP estimation.

Fuzzy Logic Control of Heartrate by Electrical Block of Vagus Nerve.

Although vagus nerve stimulation (VNS) can be used to reduce heartrate by enhancing parasympathetic activity, a fully controllable intervention would also require a method for downregulating parasympathetic activity. A direct current (DC) block can be applied to a nerve to block its action potential conduction. This nerve block can be used to downregulate parasympathetic activity by blocking afferent reflexes. The damaging effects of reactions that occur at the electrode-nerve interface using conventional platinum electrodes can be avoided by separating the electrode from the nerve. Using a biocompatible, ionically conducting medium, the electrode and the damaging reactions can be isolated in a vessel away from the nerve. This type of electrode has been called the Separated Interface Nerve Electrode (SINE). Fuzzy logic control (FLC) is a controller approach that is well suited to physiological systems. The SINE, controlled by an FLC, was utilized to block a stimulated vagus nerve and regulate heart rate. The FLC was able to maintain the heartrate at a pre-determined setpoint while still achieving instant recovery when the block was removed.

A 280 µW, 108 dB DR PPG-Readout IC With Reconfigurable, 2nd-Order, Incremental ΔΣM Front-End for Direct Light-to-Digital Conversion.

This paper reports on a low-power readout IC (ROIC) for high-fidelity recording of the photoplethysmogram (PPG) signal. The system comprises a highly reconfigurable, continuous-time, second-order, incremental delta-sigma modulator (I-ΔΣM) as a light-to-digital converter (LDC), a 2-channel 10b light-emitting diode (LED) driver, and an integrated digital signal processing (DSP) unit. The LDC operation in intermittent conversion phases coupled with digital assistance by the DSP unit allow signal-aware, on-the-fly cancellation of the dc and ambient light-induced components of the photodiode current for more efficient use of the full-scale input range for recording of the small-amplitude, ac, PPG signal. Fabricated in TSMC 0.18 µm 1P/6M CMOS, the PPG ROIC exhibits a high dynamic range of 108.2 dB and dissipates on average 15.7 µW from 1.5 V in the LDC and 264 µW from 2.5 V in one LED (and its driver), while operating at a pulse repetition frequency of 250 Hz and 3.2% duty cycling. The overall functionality of the ROIC is also demonstrated by high-fidelity recording of the PPG signal from a human subject fingertip in the presence of both natural light and indoor light sources of 60 Hz.

Powering strategies for implanted multi-function neuroprostheses for spinal cord injury.

Implantable motor neuroprosthetic systems can restore function to individuals with significant disabilities, such as spinal cord injury, stroke, cerebral palsy, and multiple sclerosis. Neuroprostheses provide restored functionality by electrically activating paralysed muscles in coordinated patterns that replicate (enable) controlled movement that was lost through injury or disease. It is important to consider the general topology of the implanted system itself. The authors demonstrate that the wired multipoint implant technology is practical and feasible as a basis for the development of implanted multi-function neuroprosthetic systems. The advantages of a centralised power supply are significant. Heating due to recharge can be mitigated by using an actively cooled external recharge coil. Using this approach, the time required to perform a full recharge was significantly reduced. This approach has been demonstrated as a practical option for regular clinical use of implanted neuroprostheses.

A Rare Case of Cervical Charcot After Spinal Cord Injury: A Case Report.

CASE: We present a rare case of cervical Charcot disease that was diagnosed in a paraplegic patient by loss of function caudal to the original level of spinal cord injury. Clinical imaging, diagnosis, differentials, and operative management are discussed. CONCLUSIONS: Charcot disease of the cervical spine is rare and very difficult to diagnose in the paraplegic patient population. High clinical suspicion should be maintained in these patients who demonstrate any form of neurologic deterioration, mechanical instability, or change in spinal alignment. It is often necessary to rule out infection. Spinal decompression and surgical stabilization is the treatment of choice.

A Carbon Slurry Separated Interface Nerve Electrode for Electrical Block of Nerve Conduction.

Direct current (DC) nerve block has been shown to provide a complete block of nerve conduction without unwanted neural firing. Previous work shows that high capacitance electrodes can be used to safely deliver a DC block. Another way of delivering DC safely is through a separated interface nerve electrode (SINE), such that any reactive species that are generated by the passage of DC are contained in a vessel away from the nerve. This design has been enhanced by using a high capacitance carbon "slurry" as the electrode in the external vessel to extend the capacity of the electrode (CSINE). With this new design, it was possible to provide 50 min of continuous nerve block without recharge while still maintaining complete recovery of neural signals. Up to 46 C of charge delivery was applied for a total of 4 h of nerve block with complete recovery. Because of the extended delivery time, it was possible to explore several properties of DC block that would not be revealed without the capability of a long-duration continuous block. It was possible to achieve complete block at lower values of DC if the block was applied for a longer period of time. Depending on the amount of charge applied during the block, the recovery was delayed for a period of time before complete force recovery was restored. These new properties provide novel techniques for device development to optimize charge delivery time and device powering concerns.

Neuromodulation for Functional Electrical Stimulation.

This article describes the application of neuromodulation in different ways to motor recovery, to replace lost function, or to improve function of organ systems for those who have experienced spinal cord injury or stroke. Multiple devices have been developed and are currently available for use whereas others are still in the experimental stage. Multiple uses of neuromodulation are described.

Measurement of block thresholds in kiloHertz frequency alternating current peripheral nerve block.

BACKGROUND: Kilohertz frequency alternating currents (KHFAC) produce rapid nerve conduction block of mammalian peripheral nerve and have potential clinical applications in reducing peripheral nerve hyperactivity. The experimental investigation of KHFAC nerve block requires a robust output measure and this has proven to be the block threshold (BT), the lowest current or voltage at which the axons of interest are completely blocked. All significant literature in KHFAC nerve block, both simulations and experimental, were reviewed to determine the block threshold method that was used. The two common methods used are the High-Low method experimentally and the Binary search method for simulations. NEW METHOD: Four methods to measure the block threshold (High-Low, High-Low-High, Binary and Random) at three frequencies (10, 20 and 30 kHz) were compared through randomized repeated experiments in the in-vivo rodent sciatic nerve-gastrocnemius model. RESULTS: The literature review showed that more than 50% of publications did not measure the block threshold. The experimental results showed no statistical difference in the BT value between the four methods. COMPARISON WITH EXISTING METHOD(S): However, there were differences in the number of significant onset responses, depending on the method. The run time for the BT determination was the shortest for the High-Low method. CONCLUSIONS: It is recommended that all research in electrical nerve block, including KHFAC, should include measurement of the BT. The High-Low method is recommended for most experimental situations but the Binary method could also be a viable option, especially where onset responses are minimal.

Design and testing of a 96-channel neural interface module for the Networked Neuroprosthesis system.

BACKGROUND: The loss of motor functions resulting from spinal cord injury can have devastating implications on the quality of one's life. Functional electrical stimulation has been used to help restore mobility, however, current functional electrical stimulation (FES) systems require residual movements to control stimulation patterns, which may be unintuitive and not useful for individuals with higher level cervical injuries. Brain machine interfaces (BMI) offer a promising approach for controlling such systems; however, they currently still require transcutaneous leads connecting indwelling electrodes to external recording devices. While several wireless BMI systems have been designed, high signal bandwidth requirements limit clinical translation. Case Western Reserve University has developed an implantable, modular FES system, the Networked Neuroprosthesis (NNP), to perform combinations of myoelectric recording and neural stimulation for controlling motor functions. However, currently the existing module capabilities are not sufficient for intracortical recordings. METHODS: Here we designed and tested a 1 × 4 cm, 96-channel neural recording module prototype to fit within the specifications to mate with the NNP. The neural recording module extracts power between 0.3-1 kHz, instead of transmitting the raw, high bandwidth neural data to decrease power requirements. RESULTS: The module consumed 33.6 mW while sampling 96 channels at approximately 2 kSps. We also investigated the relationship between average spiking band power and neural spike rate, which produced a maximum correlation of R = 0.8656 (Monkey N) and R = 0.8023 (Monkey W). CONCLUSION: Our experimental results show that we can record and transmit 96 channels at 2ksps within the power restrictions of the NNP system and successfully communicate over the NNP network. We believe this device can be used as an extension to the NNP to produce a clinically viable, fully implantable, intracortically-controlled FES system and advance the field of bioelectronic medicine.

Advanced Assessment of the Upper Limb in Tetraplegia: A Three-Tiered Approach to Characterizing Paralysis.

Background: More than half of all individuals who sustain a spinal cord injury (SCI) experience some degree of impairment in the upper limb. Functional use of the arm and hand is of paramount importance to these individuals. Fortunately, the number of clinical trials and advanced interventions targeting upper limb function are increasing, generating optimism for improved recovery and restoration after SCI. New interventions for restoring function and improving recovery require more detailed examination of the motor capacities of the upper limb. Objectives: The purpose of this article is to introduce a three-tiered approach to evaluating motor function, with specific attention to the characteristics of weak and fully paralyzed muscles during acute rehabilitation. The three tiers include (1) evaluation of voluntary strength via manual muscle testing, (2) evaluation of lower motor neuron integrity in upper motor neuron-paralyzed muscles using surface electrical stimulation, and (3) evaluation of latent motor responses in paralyzed muscles that exhibit a strong response to electrical stimulation, using surface electromyographic recording electrodes. These characteristics contribute important information that can be utilized to mitigate potential secondary conditions such as contractures and identify effective interventions such as activity-based interventions or reconstructive procedures. Our goal is to encourage frontline clinicians - occupational and physical therapists who are experts in muscle assessment - to consider a more in-depth analysis of paralysis after SCI. Conclusion: Given the rapid advancements in SCI research and clinical interventions, it is critical that methods of evaluation and classification evolve. The success or failure of these interventions may depend on the specific characteristics identified in our three-tiered assessment. Without this assessment, the physiological starting point for each individual is unknown, adding significant variability in the outcomes of these interventions.

Evolution of Neuroprosthetic Approaches to Restoration of Upper Extremity Function in Spinal Cord Injury.

Background: Spinal cord injury (SCI) occurring at the cervical levels can result in significantly impaired arm and hand function. People with cervical-level SCI desire improved use of their arms and hands, anticipating that regained function will result in improved independence and ultimately improved quality of life. Neuroprostheses provide the most promising method for significant gain in hand and arm function for persons with cervical-level SCI. Neuroprostheses utilize small electrical currents to activate peripheral motor nerves, resulting in controlled contraction of paralyzed muscles. Methods: A myoelectrically-controlled neuroprosthesis was evaluated in 15 arms in 13 individuals with cervical-level SCI. All individuals had motor level C5 or C6 tetraplegia. Results: This study demonstrates that an implanted neuroprosthesis utilizing myoelectric signal (MES)-controlled stimulation allows considerable flexibility in the control algorithms that can be utilized for a variety of arm and hand functions. Improved active range of motion, grip strength, and the ability to pick up and release objects were improved in all arms tested. Adverse events were few and were consistent with the experience with similar active implantable devices. Conclusion: For individuals with cervical SCI who are highly motivated, implanted neuroprostheses provide the opportunity to gain arm and hand function that cannot be gained through the use of orthotics or surgical intervention alone. Upper extremity neuroprostheses have been shown to provide increased function and independence for persons with cervical-level SCI.

Reversible conduction block in peripheral nerve using electrical waveforms.

INTRODUCTION: Electrical nerve block uses electrical waveforms to block action potential propagation. MATERIALS & METHODS: Two key features that distinguish electrical nerve block from other nonelectrical means of nerve block: block occurs instantly, typically within 1 s; and block is fully and rapidly reversible (within seconds). RESULTS: Approaches for achieving electrical nerve block are reviewed, including kilohertz frequency alternating current and charge-balanced polarizing current. We conclude with a discussion of the future directions of electrical nerve block. CONCLUSION: Electrical nerve block is an emerging technique that has many significant advantages over other methods of nerve block. This field is still in its infancy, but a significant expansion in the clinical application of this technique is expected in the coming years.

Transcranial direct current stimulation (tDCS) paired with massed practice training to promote adaptive plasticity and motor recovery in chronic incomplete tetraplegia: A pilot study.

OBJECTIVE: Our goal was to determine if pairing transcranial direct current stimulation (tDCS) with rehabilitation for two weeks could augment adaptive plasticity offered by these residual pathways to elicit longer-lasting improvements in motor function in incomplete spinal cord injury (iSCI). DESIGN: Longitudinal, randomized, controlled, double-blinded cohort study. SETTING: Cleveland Clinic Foundation, Cleveland, Ohio, USA. PARTICIPANTS: Eight male subjects with chronic incomplete motor tetraplegia. INTERVENTIONS: Massed practice (MP) training with or without tDCS for 2 hrs, 5 times a week. OUTCOME MEASURES: We assessed neurophysiologic and functional outcomes before, after and three months following intervention. Neurophysiologic measures were collected with transcranial magnetic stimulation (TMS). TMS measures included excitability, representational volume, area and distribution of a weaker and stronger muscle motor map. Functional assessments included a manual muscle test (MMT), upper extremity motor score (UEMS), action research arm test (ARAT) and nine hole peg test (NHPT). RESULTS: We observed that subjects receiving training paired with tDCS had more increased strength of weak proximal (15% vs 10%), wrist (22% vs 10%) and hand (39% vs. 16%) muscles immediately and three months after intervention compared to the sham group. Our observed changes in muscle strength were related to decreases in strong muscle map volume (r=0.851), reduced weak muscle excitability (r=0.808), a more focused weak muscle motor map (r=0.675) and movement of weak muscle motor map (r=0.935). CONCLUSION: Overall, our results encourage the establishment of larger clinical trials to confirm the potential benefit of pairing tDCS with training to improve the effectiveness of rehabilitation interventions for individuals with SCI. TRIAL REGISTRATION: NCT01539109.

Upper Extremity Assessment in Tetraplegia: The Importance of Differentiating Between Upper and Lower Motor Neuron Paralysis.

Scientific advances are increasing the options for improved upper limb function in people with cervical level spinal cord injury (SCI). Some of these interventions rely on identifying an aspect of paralysis that is not uniformly assessed in SCI: the integrity of the lower motor neuron (LMN). SCI can damage both the upper motor neuron and LMN causing muscle paralysis. Differentiation between these causes of paralysis is not typically believed to be important during SCI rehabilitation because, regardless of the cause, the muscles are no longer under voluntary control by the patient. Emerging treatments designed to restore upper extremity function (eg, rescue microsurgical nerve transfers, motor learning-based interventions, functional electrical stimulation) all require knowledge of LMN status. The LMN is easily evaluated using surface electrical stimulation and does not add significant time to the standard clinical assessment of SCI. This noninvasive evaluation yields information that contributes to the development of a lifetime upper extremity care plan for maximizing function and quality of life. Given the relative simplicity of this assessment and the far-reaching implications for treatment and function, we propose that this assessment should be adopted as standard practice for acute cervical SCI.