Corticospinal inhibition investigated in relation to upper extremity motor function in cervical spinal cord injury.

OBJECTIVE: Corticospinal inhibitory mechanisms are relevant to functional recovery but remain poorly understood after spinal cord injury (SCI). Post-injury characteristics of contralateral silent period (CSP), a measure of corticospinal inhibition evaluated using transcranial magnetic stimulation (TMS), is inconsistent in literature. We envisioned that investigating CSP across muscles with varying degrees of weakness may be a reasonable approach to resolve inconsistencies and elucidate the relevance of corticospinal inhibition for upper extremity function following SCI. METHODS: We studied 27 adults with chronic C1-C8 SCI (age 48.8 ± 16.1 years, 3 females) and 16 able-bodied participants (age 33.2 ± 11.8 years, 9 females). CSP characteristics were assessed across biceps (muscle power = 3-5) and triceps (muscle power = 1-3) representing stronger and weaker muscles, respectively. We assessed functional abilities using the Capabilities of the Upper Extremity Test (CUE-T). RESULTS: Participants with chronic SCI had prolonged CSPs for biceps but delayed and diminished CSPs for triceps compared to able-bodied participants. Early-onset CSPs for biceps and longer, deeper CSPs for triceps correlated with better CUE-T scores. CONCLUSIONS: Corticospinal inhibition is pronounced for stronger biceps but diminished for weaker triceps muscle in SCI indicating innervation relative to the level of injury matters in the study of CSP. SIGNIFICANCE: Nevertheless, corticospinal inhibition or CSP holds relevance for upper extremity function following SCI.

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.

Can the electrically stimulated manual muscle test differentiate upper from lower motor neuron injury in persons with acute SCI?

OBJECTIVE: To determine if the motor response on the stimulated manual muscle test (SMMT) in muscles with a grade 0 motor score on the manual muscle test (MMT) can differentiate lower motor neuron (LMN) from upper motor neuron (UMN) injury based on the presence of spontaneous activity (SA) with needle EMG. DESIGN: Prospective Study. PARTICIPANTS/METHODS: Twenty-one subjects with acute traumatic cervical SCI. METHODS: An upper extremity International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) evaluation was completed on all subjects. A needle EMG and an electrically stimulated manual muscle test (SMMT) were completed on all key upper extremity muscles with a MMT motor score of zero. RESULTS: The MMT, SMMT and Needle EMG were done on 77 muscles. The SMMT motor score was 0 on 10 muscles and >1 on 67 muscles. The needle EMG identified spontaneous activity (SA) in 55/77 muscles. Seventy percent (7/10) of the muscles with MMT and SMMT motor score of zero demonstrated SA on EMG. Seventy-two percent (48/67) of the muscles with MMT motor score = 0 and SMMT motor score ≥1 demonstrated SA on EMG. CONCLUSION: In our study, 70% of the muscles with a SMMT motor response of zero and 72% of the muscles with a SMMT motor response greater than or equal to one demonstrated SA on EMG. The use of the SMMT as a clinical measure to differentiate LMN from UMN integrity may be limited when applied.

The Effects of Filtering PPG Signal on Pulse Arrival Time-Systolic Blood Pressure Correlation.

Pulse arrival time (PAT), evaluated from electro-cardiogram (ECG) and photoplethysmogram (PPG) signals, has been widely used for cuff-less blood pressure (BP) estimation due to its high correlation with BP. However, the question of whether filtering the PPG signal impacts the extracted PAT values and consequently, the correlation between PAT and BP, has not been investigated before. In this paper, using data from 18 subjects, changes in the PAT values, and in the subject-specific PAT-systolic BP (SBP) correlation caused by filtering the PPG signal with variable cutoff frequencies in the range of 2 to 15 Hz are studied. For PAT extraction, three PPG characteristic points (foot, maximum slope and systolic peak) are considered. Results show that differences in the cutoff frequency can shift the PAT values and introduce a worst-case error of over 8.2 mmHg for SBP estimation, indicating that PPG signal filter settings can impact PAT-based BP estimations. Our study suggests that extracting the PAT from the maximum slope point of PPG signal filtered at 10 Hz provides the most stable correlation with SBP.

Evaluation of Activated Carbon and Platinum Black as High-Capacitance Materials for Platinum Electrodes.

The application of direct current (DC) produces a rapid and reversible nerve conduction block. However, prolonged injection of charge through a smooth platinum electrode has been found to cause damage to nervous tissue. This damage can be mitigated by incorporating high-capacitance materials (HCM) (e.g., activated carbon or platinum black) into electrode designs. HCMs increase the storage charge capacity (i.e., "Q value") of capacitive devices. However, consecutive use of these HCM electrodes degrades their surface. This paper evaluates activated carbon and platinum black (PtB) electrode designs in vitro to determine the design parameters which improve surface stability of the HCMs. Electrode designs with activated carbon and PtB concentrations were stressed using soak, bend and vibration testing to simulate destructive in vivo environments. A Q value decrease represented the decreased stability of the electrode-HCM interface. Soak test results supported the long-term Q value stabilization (mean = 44.3 days) of HCM electrodes, and both HCMs displayed unique Q value changes in response to soaking. HCM material choices, Carbon Ink volume, and application of Nafion™ affected an electrode's ability to resist Q value degradation. These results will contribute to future developments of HCM electrodes designed for extended DC application for in vivo nerve conduction block.

Safety and efficacy of transcranial direct current stimulation in upper extremity rehabilitation after tetraplegia: protocol of a multicenter randomized, clinical trial.

STUDY DESIGN: A multisite, randomized, controlled, double-blinded phase I/II clinical trial. OBJECTIVE: The purpose of this clinical trial is to evaluate the safety, feasibility and efficacy of pairing noninvasive transcranial direct current stimulation (tDCS) with rehabilitation to promote paretic upper extremity recovery and functional independence in persons living with chronic cervical spinal cord injury (SCI). SETTING: Four-site trial conducted across Cleveland Clinic, Louis Stokes Veterans Affairs Medical Center of Cleveland and MetroHealth Rehabilitation Rehabilitation Institute of Ohio, and Kessler Foundation of New Jersey. METHODS: Forty-four adults (age ≥18 years) with tetraplegia following cervical SCI that occurred ≥1-year ago will participate. Participants will be randomly assigned to receive anodal tDCS or sham tDCS given in combination with upper extremity rehabilitation for 15 sessions each over 3-5 weeks. Assessments will be made twice at baseline separated by at least a 3-week interval, once at end-of-intervention, and once at 3-month follow-up. PRIMARY OUTCOME MEASURE(S): Primary outcome measure is upper extremity motor impairment assessed using the Graded Redefined Assessment of Strength, Sensibility and Prehension (GRASSP) scale. Functional abilities will be assessed using Capabilities of Upper Extremity-Test (CUE-T), while functional independence and participation restrictions will be evaluated using the self-care domain of Spinal Cord Independent Measure (SCIM), and Canadian Occupational Performance Measure (COPM). SECONDARY OUTCOME MEASURES: Treatment-associated change in corticospinal excitability and output will also be studied using transcranial magnetic stimulation (TMS) and safety (reports of adverse events) and feasibility (attrition, adherence etc.) will also be evaluated. TRIAL REGISTRATION: ClincalTrials.gov identifier NCT03892746. This clinical trial is being performed at four sites within the United States: Cleveland Clinic (lead site), Louis Stokes Cleveland Veterans Affairs Medical Center (VAMC) and MetroHealth Rehabilitation Institute in Ohio, and Kessler Foundation in New Jersey. The U.S. Army Medical Research Acquisition Activity, 820 Chandler Street, Fort Detrick MD 21702-5014 is the awarding and administering acquisition office.

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.

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 via Small Convolutional Neural Networks.

Deep learning-based cuff-less blood pressure (BP) estimation methods have recently gained increased attention as they can provide accurate BP estimation with only one physiological signal as input. In this paper, we present a simple and effective method for cuff-less BP estimation by training a small-scale convolutional neural network (CNN), modified from LeNet-5, with images created from short segments of the photoplethysmogram (PPG) signal via visibility graph (VG). Results show that the trained modified LeNet-5 model achieves an error performance of 0.184±7.457 mmHg for the systolic BP (SBP), and 0.343±4.065 mmHg for the diastolic BP (DBP) in terms of the mean error (ME) and the standard deviation (SD) of error between the estimated and reference BP. Both the SBP and the DBP accuracy rank grade A under the British Hypertension Society (BHS) protocol, demonstrating that our proposed method is an accurate way for cuff-less 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.

PulseLab: An Integrated and Expandable Toolbox for Pulse Wave Velocity-based Blood Pressure Estimation.

In this paper, we introduce PulseLab, a comprehensive MATLAB toolbox that enables estimating the blood pressure (BP) from electrocardiogram (ECG) and photoplethysmogram (PPG) signals using pulse wave velocity (PWV)-based models. This universal framework consists of 6 sequential modules, covering end-to-end procedures that are needed for estimating BP from raw PPG/ECG data. These modules are "dataset formation", "signal pre-processing", "segmentation", "characteristic-points detection", "pulse transit time (PTT)/ pulse arrival time (PAT) calculation", and "model validation". The toolbox is expandable and its application programming interface (API) is built such that newly-derived PWV-BP models can be easily included. The toolbox also includes a user-friendly graphical user interface (GUI) offering visualization for step-by-step processing of physiological signals, position of characteristic points, PAT/PTT values, and the BP regression results. To the best of our knowledge, PulseLab is the first comprehensive toolbox that enables users to optimize their model by considering several factors along the process for obtaining the most accurate model for cuff-less BP estimation.

Design and Testing of Stimulation and Myoelectric Recording Modules in an Implanted Distributed Neuroprosthetic System.

Implantable motor neuroprostheses can restore functionality to individuals with neurological disabilities by electrically activating paralyzed muscles in coordinated patterns. The typical design of neuroprosthetic systems relies on a single multi-use device, but this limits the number of stimulus and sensor channels that can be practically implemented. To address this limitation, a modular neuroprosthesis, the "Networked Neuroprosthesis" (NNP), was developed. The NNP system is the first fully implanted modular neuroprosthesis that includes implantation of all power, signal processing, biopotential signal recording, and stimulating components. This paper describes the design of stimulation and recording modules, bench testing to verify stimulus outputs and appropriate filtering and recording, and validation that the components function properly while implemented in persons with spinal cord injury. The results of system testing demonstrated that the NNP was functional and capable of generating stimulus pulses and recording myoelectric, temperature, and accelerometer signals. Based on the successful design, manufacturing, and testing of the NNP System, multiple clinical applications are anticipated.

Combining direct current and kilohertz frequency alternating current to mitigate onset activity during electrical nerve block.

Objective.Electrical nerve block offers the ability to immediately and reversibly block peripheral nerve conduction and would have applications in the emerging field of bioelectronics. Two modalities of electrical nerve block have been investigated-kilohertz frequency alternating current (KHFAC) and direct current (DC). KHFAC can be safely delivered with conventional electrodes, but has the disadvantage of having an onset response, which is a period of increased neural activation before block is established and currently limits clinical translation. DC has long been known to block neural conduction without an onset response but creates damaging reactive species. Typical electrodes can safely deliver DC for less than one second, but advances in high capacitance electrodes allow DC delivery up to 10 s without damage. The present work aimed to combine DC and KHFAC into a single waveform, named the combined reduced onset waveform (CROW), which can initiate block without an onset response while also maintaining safe block for long durations. This waveform consists of a short, DC pre-pulse before initiating KHFAC.Approach.Simulations of this novel waveform were carried out in the axonal simulation environment NEURON to test feasibility and gain insight into the mechanisms of action. Two sets of acute experiments were then conducted in adult Sprague-Dawley rats to determine the effectiveness of the waveform in mitigating the onset response.Main results.The CROW reduced the onset response bothin silicoandin vivo. The onset area was reduced by over 90% with the tested parameters in the acute experiments. The amplitude of the DC pulse was shown to be particularly important for effective onset mitigation, requiring amplitudes 6-8 times the DC block threshold.Significance.This waveform can reliably reduce the onset response due to KHFAC and could allow for wider clinical implementation of electrical nerve block.

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.

Myoelectric signal from below the level of spinal cord injury as a command source for an implanted upper extremity neuroprosthesis - a case report.

Implanted motor neuroprostheses offer significant restoration of function for individuals with spinal cord injury. Providing adequate user control for these devices is a challenge but is crucial for successful performance. Electromyographic (EMG) signals can serve as effective control sources, but the number of above-injury muscles suitable to provide EMG-based control signals is very limited. Previous work has shown the presence of below-injury volitional myoelectric signals even in subjects diagnosed with motor complete spinal cord injury. In this case report, we present a demonstration of a hand grasp neuroprosthesis being controlled by a user with a C6 level, motor complete injury through EMG signals from their toe flexor. These signals were successfully translated into a functional grasp output, which performed similarly to the participant's usual shoulder position control in a grasp-release functional test. This proof-of-concept demonstrates the potential for below-injury myoelectric activity to serve as a novel form of neuroprosthesis control.

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.