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Epidural spinal cord stimulation (ESCS) is a potential treatment for the recovery of the motor function in spinal cord injury (SCI) patients. Since the mechanism of ESCS remains unclear, it is necessary to study the neurophysiological principles in animal experiments and standardize the clinical treatment. In this paper, an ESCS system is proposed for animal experimental study. The proposed system provides a fully implantable and programmable stimulating system for complete SCI rat model, along with a wireless charging power solution. The system is composed of an implantable pulse generator (IPG), a stimulating electrode, an external charging module and an Android application (APP) via a smartphone. The IPG has an area of ${25} \times {25}$ mm2 and can output 8 channels of stimulating currents. Stimulating parameters, including amplitude, frequency, pulse width and sequence, can be programmed through the APP. The IPG was encapsulated with a zirconia ceramic shell and two-month implantable experiments were carried out in 5 rats with SCI. The main focus of the animal experiment was to show that the ESCS system could work stably in SCI rats. The IPG implanted in vivo can be charged through the external charging module in vitro without anesthetizing the rats. The stimulating electrode was implanted according to the distribution of ESCS motor function regions of rats and fixed on the vertebrae. The lower limb muscles of SCI rats can be activated effectively. The two-month SCI rats needed greater stimulating current intensity than the one-month SCI rats The results indicated that the stimulating system provides an effective and simplified tool for studying the ESCS application in motor function recovery for untethered animals. [ABSTRACT FROM AUTHOR]

Gait analysis continues to be an important technique for many clinical applications to diagnose and monitor certain diseases. Many mental and physical abnormalities cause measurable differences in a person's gait. Gait analysis has applications in sport, computer games, physical rehabilitation, clinical assessment, surveillance, human recognition, modeling, and many other fields. There are established methods using various sensors for gait analysis, of which accelerometers are one of the most often employed. Accelerometer sensors are generally more user friendly and less invasive. In this paper, we review research regarding accelerometer sensors used for gait analysis with particular focus on clinical applications. We provide a brief introduction to accelerometer theory followed by other popular sensing technologies. Commonly used gait phases and parameters are enumerated. The details of selecting the papers for review are provided. We also review several gait analysis software. Then we provide an extensive report of accelerometry-based gait analysis systems and applications, with additional emphasis on trunk accelerometry. We conclude this review with future research directions. [ABSTRACT FROM AUTHOR]

Detection of sagittal spine and spinopelvic disorder or injury is a key issue in children and adults due to variation in shape and orientation. Especially in remote patient monitoring for proper diagnose the structure and angular deviation of the lumbar spine and pelvis are required. So automatic rehabilitation process, especially for bedridden people at home, is very much essential for spinal cord injury patients to optimize the quick diagnosis process. The main objective of this work is to improve the classification rate of the vertebral spinal cord sensing data for automatic rehabilitation process. In this paper, a filter based multi-level segmentation and classification approach is implemented on the vertebral column dataset. In this approach, sensor generated spinal cord data are used in order to predict the severity level of each spinal cord disorder. In this approach, a novel vertebral data pre-processing method, a multi-level sensing approach and an improved random forest technique is proposed to predict the disorder with high true positive rate. Experimental results proved that the present model has better efficiency than the existing vertebral classifiers such as Naïve Bayes, Neural Network, Adaboost, Random forest and SVM in terms of true positive rate; TP = 0.9813, Accuracy = 0.9783, Error rate = 0.0246 are concerned. [ABSTRACT FROM AUTHOR]

Epidural spinal cord stimulation has been reported to partially restore volitional movement and autonomic functions after motor and sensory-complete spinal cord injury (SCI). Modern spinal cord stimulation platforms offer significant flexibility in spatial and temporal parameters of stimulation delivered. Heterogeneity in SCI and injury-related symptoms necessitate stimulation personalization to maximally restore functions. However, the large multi-dimensional stimulation space makes exhaustive tests impossible. In this paper, we present a Bayesian optimization strategy for identifying personalized optimal stimulation patterns based on the participant’s expressed preference for stimulation settings. We present companion validation protocols for investigating the credibility of learned preference models. The results obtained for five participants in the E-STAND spinal cord stimulation clinical trial are reported. Personalized preference models produced by the proposed learning and optimization algorithm show that there is more similarity in optimal frequency than in pulse width across participants. Across five participants, the average model prediction accuracy is 71.5% in internal cross-validation and 65.6% in prospective validation. Statistical tests of both validation studies show that the ability of the preference models to correctly predict unseen preference data is significantly greater than chance. The personalized preference models are also shown to be significantly correlated with motor task performance across participants. We show that several aspects in participants’ quality of life has been improved over the course of the trial. Overall, the results indicate that the Bayesian preference optimization algorithm could assist clinicians in the systematic programming of individualized therapeutic stimulation settings and improve the therapeutic outcomes. [ABSTRACT FROM AUTHOR]

In this paper, we present the design, control, and preliminary evaluation of the Symbitron exoskeleton, a lower limb modular exoskeleton developed for people with a spinal cord injury. The mechanical and electrical configuration and the controller can be personalized to accommodate differences in impairments among individuals with spinal cord injuries (SCI). In hardware, this personalization is accomplished by a modular approach that allows the reconfiguration of a lower-limb exoskeleton with ultimately eight powered series actuated (SEA) joints and high fidelity torque control. For SCI individuals with an incomplete lesion and sufficient hip control, we applied a trajectory-free neuromuscular control (NMC) strategy and used the exoskeleton in the ankle-knee configuration. For complete SCI individuals, we used a combination of a NMC and an impedance based trajectory tracking strategy with the exoskeleton in the ankle-knee-hip configuration. Results of a preliminary evaluation of the developed hardware and software showed that SCI individuals with an incomplete lesion could naturally vary their walking speed and step length and walked faster compared to walking without the device. SCI individuals with a complete lesion, who could not walk without support, were able to walk with the device and with the support of crutches that included a push-button for step initiation Our results demonstrate that an exoskeleton with modular hardware and control allows SCI individuals with limited or no lower limb function to receive tailored support and regain mobility. [ABSTRACT FROM AUTHOR]

We developed a superconducting quantum interference device (SQUID)-based biomagnetometer system for magnetoneurograms. The system was improved from a previously reported prototype magnetospinograph (MSG)/neurograph (MNG) system to satisfy the additional requirements that arose when we investigated practical clinical applications of the MSG/MNG in a hospital. The dimensions of the vector-type SQUID flux sensor array were increased to 150 mm × 188 mm, and the shape of the cryostat was modified so that the peripheral nerves at different body parts of a subject who assumed various postures, including positions provoking neurological symptoms, could be examined. In this paper, the improved MNG system is described in detail. Functional imaging of the brachial plexuses of subjects whose arms were in the abduction and external rotation position, which is one of the typical symptom-provocative positions for the shoulder, was achieved using the improved MNG system. [ABSTRACT FROM AUTHOR]

Advances in magnetic resonance (MR) imaging techniques enable the accurate measurements of cerebrospinal fluid (CSF) flow in the human brain. In addition, image reconstruction tools facilitate the collection of patient-specific brain geometry data such as the exact dimensions of the ventricular and subarachnoidal spaces (SAS) as well as the computer-aided reconstruction of the CSF-filled spaces. The solution of the conservation of CSF mass and momentum balances over a finite computational mesh obtained from the MR images predict the patients' CSF flow and pressure field. Advanced image reconstruction tools used in conjunction with first principles of fluid mechanics allow an accurate verification of the CSF flow patters for individual patients. This paper presents a detailed analysis of pulsatile CSF flow and pressure dynamics in a normal and hydrocephalic patient. Experimental CSF flow measurements and computational results of flow and pressure fields in the ventricular system, the SAS and brain parenchyma are presented. The pulsating CSF motion is explored in normal and pathological conditions of communicating hydrocephalus. This paper predicts small transrnantle pressure differences between lateral ventricles and SASs (~ 10 Pa). The transmantle pressure between ventricles and SAS remains small even in the hydrocephalic patient (~ 30 Pa), but the ICP pulsatility increases by a factor of four. The computational fluid dynamics (CFD) results of the predicted CSF flow velocities are in good agreement with Cine MRI measurements. Differences between the predicted and observed CSF flow velocities in the prepontine area point towards complex brain-CSF interactions. The paper presents the complete computational model to predict the pulsatile CSF flow in the cranial cavity. [ABSTRACT FROM AUTHOR]

Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions. [ABSTRACT FROM AUTHOR]

Predicting the functional outcomes of spinal cord disorder patients after medical treatments, such as a surgical operation, has always been of great interest. Accurate posttreatment prediction is especially beneficial for clinicians, patients, care givers, and therapists. This paper introduces a prediction method for postoperative functional outcomes by a novel use of Gaussian process regression. The proposed method specifically considers the restricted value range of the target variables by modeling the Gaussian process based on a truncated Normal distribution, which significantly improves the prediction results. The prediction has been made in assistance with target tracking examinations using a highly portable and inexpensive handgrip device, which greatly contributes to the prediction performance. The proposed method has been validated through a dataset collected from a clinical cohort pilot involving $15$ patients with cervical spinal cord disorder. The results show that the proposed method can accurately predict postoperative functional outcomes, Oswestry disability index and target tracking scores, based on the patient's preoperative information with a mean absolute error of $0.079$ and $0.014$ (out of $1.0$), respectively. [ABSTRACT FROM PUBLISHER]

Spinal cord stimulation (SCS) has enabled motor recovery in paraplegics with motor complete spinal cord injury (SCI). However, the physiological mechanisms underlying this recovery are unknown. This paper analyzes muscle synergies in two motor complete SCI patients under SCS during standing and compares them with muscle synergies in healthy subjects, in order to help elucidate the mechanisms that enable motor control through SCS. One challenge is that standard muscle synergy extraction algorithms, such as non-negative matrix factorization (NMF), fail when applied to SCI patients under SCS. We develop a new algorithm–rShiftNMF–to extract muscle synergies in these cases. We find muscle synergies extracted by rShiftNMF are significantly better at interpreting electromyography (EMG) activity, and resulting synergy features are more physiologically meaningful. By analyzing muscle synergies from SCI patients and healthy subjects, we find that: 1) SCI patients rely significantly on muscle synergy activation to generate motor activity; 2) interleaving SCS can selectively activate an additional muscle synergy that is critical to SCI standing; and 3) muscle synergies extracted from SCI patients under SCS differ substantially from those extracted from healthy subjects. We provide evidence that after spinal cord injury, SCS influences motor function through muscle synergy activation. [ABSTRACT FROM AUTHOR]

Quantifying spinal cord (SC) atrophy in neurodegenerative and traumatic diseases brings important diagnosis and prognosis information for the clinician. We recently developed the PropSeg method, which allows for fast, accurate and automatic segmentation of the SC on different types of MRI contrast (e.g., T1-, T2- and T2^{\ast}-weighted sequences) and any field of view. However, comparing measurements from the SC between subjects is hindered by the lack of a generic coordinate system for the SC. In this paper, we present a new framework combining PropSeg and a vertebral level identification method, thereby enabling direct inter- and intra-subject comparison of SC measurements for large cohort studies as well as for longitudinal studies. Our segmentation method is based on the multi-resolution propagation of tubular deformable models. Coupled with an automatic intervertebral disk identification method, our segmentation pipeline provides quantitative metrics of the SC and spinal canal such as cross-sectional areas and volumes in a generic coordinate system based on vertebral levels. This framework was validated on 17 healthy subjects and on one patient with SC injury against manual segmentation. Results have been compared with an existing active surface method and show high local and global accuracy for both SC and spinal canal (Dice coefficients =0.91 \pm 0.02) segmentation. Having a robust and automatic framework for SC segmentation and vertebral-based normalization opens the door to bias-free measurement of SC atrophy in large cohorts. [ABSTRACT FROM AUTHOR]

In recent years, ultrasound has been increasingly used to guide needle insertion procedures for spinal anesthesia. The primary anatomical targets are facet joints and epidural spaces. For these procedures, accurate visualization of the spine anatomy is of critical importance. Challenges arising from the interactions between the ultrasound beam and spinal structures including tilt caused by specular reflections, off-axis interference, and reverberations often result in weakened and blurred vertebra surfaces. Previously, adaptive beamforming methods have been proposed to improve the resolution and contrast. However, most of these methods are not specialized for improving the contrast of specular targets like bones. In this paper, we propose an accumulated angle factor (AAF)-based beamforming method customized for bone surface enhancement. This approach applies a Hilbert transform on delay compensated channel data across the receive aperture. The accumulated phase change across the receive aperture is then calculated and utilized as the weight in the beamforming output. We compared our method with classical delay and sum (DAS) beamforming method and adaptive beamforming methods such as Wiener, phase coherence factor (PCF), CF, and generalized CF (GCF) beamforming. In 12 $in~vivo$ volunteer data sets, the mean contrast ratio between the vertebrae surface and the surrounding tissue for DAS, Wiener, PCF, CF, GCF, and the proposed AAF methods are 0.49, 0.64, 0.82, 0.77, 0.76, and 0.91, respectively. The contrast is significantly improved in the proposed method. [ABSTRACT FROM AUTHOR]

We address the problem of the segmentation of cerebral white matter structures from diffusion tensor images (DTI). A DTI produces, from a set of diffusion-weighted MR images, tensor- valued images where each voxel is assigned with a 3 × 3 symmetric, positive-definite matrix. This second order tensor is simply the co- variance matrix of a local Gaussian process, with zero-mean, modeling the average motion of water molecules. As we will show in this paper, the definition of a dissimilarity measure and statistics between such quantities is a nontrivial task which must be tackled carefully. We claim and demonstrate that, by using the theoretically well-founded differential geometrical properties of the manifold of multivariate normal distributions, it is possible to improve the quality of the segmentation results obtained with other dissimilarity measures such as the Euclidean distance or the Kull- back-Leibler divergence. The main goal of this paper is to prove that the choice of the probability metric, i.e., the dissimilarity measure, has a deep impact on the tensor statistics and, hence, on the achieved results. We introduce a variational formulation, in the level-set framework, to estimate the optimal segmentation of a DTI according to the following hypothesis: Diffusion tensors exhibit a Gaussian distribution in the different partitions. We must also respect the geometric constraints imposed by the interfaces existing among the cerebral structures and detected by the gradient of the DTI. We show how to express all the statistical quantities for the different probability metrics. We validate and compare the results obtained on various synthetic data-sets, a biological rat spinal cord phantom and human brain DTIs. [ABSTRACT FROM AUTHOR]

The lateral bending test is routinely used by clinicians for the preoperative assessment of spinal mobility. The evaluation of bending motion is usually based on the qualitative analysis of a two-dimensional (2-D) antero-posterior X-ray image. The aim of this paper is to introduce a novel three-dimensional (3-D) reconstruction technique that is a prerequisite for the quantitative 3-D analysis of lateral bending motion. An algorithm was developed for the 3-D reconstruction of the spine from a single X-ray image. The X-ray is calibrate using a small calibration object and an explicit calibration algorithm. The information contained in the single X-ray is completed by registering a priori 3LD geometric models of individual vertebrae. Part of the error yielded by the 3-D12-D registration is corrected by a vertebral alignment constraint that aims to minimize intervertebral dislocations. Three-di- mensional models of 15 different scoliosis patients, obtained from a standard stereo-radiographic 3-D reconstruction, were used in simulation and validation experiments. Experimental results show that the new method is robust and accurate. With pessimistic levels of simulated noise, the average root mean square reconstruction error is 2.89 mm, which is appropriate for common clinical applications. [ABSTRACT FROM AUTHOR]

This paper considers the use of cubic splines, instead of polynomials, to represent the static nonlinearities in block structured models. It introduces a system identification algorithm for the Hammerstein structure, a static nonlinearity followed by a linear filter, where cubic splines represent the static nonlinearity and the linear dynamics are modeled using a finite impulse response filter. The algorithm uses a separable least squares Levenberg-Marquardt optimization to identify Hammerstein cascades whose nonlinearities are modeled by either cubic splines or polynomials. These algorithms are compared in simulation, where the effects of variations in the input spectrum and distribution, and those of the measurement noise are examined. The two algorithms are used to fit Hammerstein models to stretch reflex electromyogram (EMG) data recorded from a spinal cord injured patient. The model with the cubic spline nonlinearity provides more accurate predictions of the reflex EMG than the polynomial based model, even in novel data. [ABSTRACT FROM AUTHOR]

A variety of robotic rehabilitation devices have been proposed for gait rehabilitation after stoke, but have only produced moderate results when compared to conventional physiotherapy. We suggest a novel approach to robotic interventions which takes advantage of mechanisms of inter-limb coordination. In order to test the viability of this approach, we apply unilateral floor stiffness perturbations via a unique robotic device and observe evoked contralateral leg responses in kinematics, as well as muscle activations, in healthy subjects. The real-time control of floor stiffness is utilized to uniquely differentiate force and kinematic feedback, creating novel sensory perturbations. We present results of repeatable and scalable evoked kinematic and muscular response of the unperturbed leg in healthy subjects. Moreover, we provide insight into the fundamental sensorimotor mechanisms of inter-leg coordination. We also lay the foundation for model-based rehabilitation strategies for impaired walkers by presenting a mathematical model that accurately describes the relationship between the magnitude of the stiffness perturbation and the evoked muscle activity. One of the most significant advantages of this approach over current practices is the safety of the patient, since this does not require any direct manipulation of the impaired leg. The novel methods and results presented in this paper set the foundation for a paradigm shift in robotic interventions for gait rehabilitation.

Spasticity is a common motor disorder following a variety of upper motor neuron lesions that seriously affects the quality of patient’s life. We aimed to evaluate whether muscle spasms can be suppressed by blocking nerve signal conduction. A rat model of lower limb spasm was prepared and the conduction of pathological nerve signals were blocked to study the inhibitory effect of nerve signal block on muscle spasm. The experimental results showed that 4 weeks after the 9th segment of the rat’s thoracic spinal cord was completely transacted, the ${H}/{M}$ -ratio of the lower limbs increased, and rate-dependent depression was weakened. When the rat model was stimulated by external forces, the electromyography (EMG) signals of the spastic gastrocnemius muscles continued to erupt. After blocking the conduction of nerve signals in the rat sciatic nerve, the spastic EMG signal of the gastrocnemius muscle disappeared. The effective blocking time and blocking efficiency increased with increasing blocking signal amplitude, and the maximum blocking efficiency reached 73%. The experimental results of this study proved the feasibility of inhibiting lower limb spasticity by blocking nerve signal conduction. [ABSTRACT FROM AUTHOR]

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

In this paper, we report the development of a flexible base array of penetrating electrodes which can be used to interface with the spinal cord. A customizable and feasible fabrication protocol is described. The flexible base arrays were fabricated and implanted into surrogate cords which were elongated by 12%. The resulting strains were optically measured across the cord and compared to those associated with two types of electrodes arrays (one without a base and one with a rigid base connecting the electrodes). The deformation behavior of cords implanted with the flexible base arrays resembled the behavior of cords implanted with individual microwires that were not connected through a base. The results of the strain test were used to validate a 2-D finite element model. The validated model was used to assess the stresses induced by the electrodes of the three types of arrays on the cord, and to examine how various design parameters (thickness, base modulus, etc.,) impact the mechanical behavior of the electrode array. Rigid base arrays induced higher stresses on the cord than the flexible base arrays which in turn imposed higher stresses than the individual microwire implants. The developed flexible base array showed improvement over the rigid base array; however, its stiffness needs to be further reduced to emulate the mechanical behavior of individual microwire arrays without a base. [ABSTRACT FROM PUBLISHER]

This paper examines how electrical stimulation of the spinal cord can modulate the output of the central pattern generator (CPG) for locomotion. Application of discrete current pulses to a single spinal segment was shown to affect multiple parameters of an ongoing locomotor pattern in an in vitro spinal cord. For any given stimulus, the effects on frequency, duration, and symmetry of locomotor output were strongly dependent on the phase at which stimulation was applied within the CPG cycle. Additionally, most stimuli had an immediate impact and evinced no effects on subsequent cycles. The most dramatic changes were seen when stimulation was applied during motor bursting: stimuli applied to the ipsilateral spinal hemicord increased the burst length, while stimuli applied to the contralateral spinal hemicord decreased the burst length. Smaller changes were observed when stimulating during delays between motor bursts. Thus, phasic stimulation was shown to influence the behavior of the CPG and spinal locomotion circuits on a cycle-by-cycle basis. This work represents the first step toward our ultimate goal of developing a neuroprosthetic device to restore locomotion after a severe spinal cord injury.

In this paper, we examine the control signals that are required to generate stepping using two different intraspinal microstimulation (ISMS) paradigms and discuss the theoretical feasibility of controlling ISMS-evoked stepping using a brain computer interface. Tonic (constant amplitude) and phasic (modulated amplitude) ISMS protocols were used to produce stepping in the hind limbs of paralyzed cats. Low-amplitude tonic ISMS activated a spinal locomotor-like network that resulted in bilateral stepping of the hind limbs. Phasic ISMS generated coordinated stepping by simultaneously activating flexor synergies in one limb coupled with extensor synergies in the other. Using these ISMS paradigms, we propose that one or two independent cortical signals will be adequate for controlling ISMS-induced stepping after SCI.

This paper aims in interpreting the leg muscles responses recorded by electromyography during magnetic stimulation of the spinal cord by computing the electric field induced in the spinal cord and the nearby areas during this procedure. A simplified model of the spine was created and a Finite Difference Method algorithm was implemented in Matlab. [ABSTRACT FROM AUTHOR]

The central nervous system (CNS) is the most difficult target for drug delivery therapies. Despite datasets available describing physiological, biochemical, cellular, and metabolic properties of the CNS, the development of infusion therapies still faces major delivery challenges. There is a need for the integration of data obtained from different experimental modalities to design molecular therapies. In this paper, we propose a novel mathematical method for the integration of datasets to generate useful dosing criteria for infusion therapies. A case study is used to demonstrate the design of gene silencing therapies to down regulate NMDA receptors in the spinal cord for chronic pain management. Based on experimentally derived kinetics for short interfering RNA (siRNA) and magnetic resonance images, the biodistribution and pharmacokinetics of siRNAs were predicted for different infusion modes. This adaptable, multiscale computational platform enables the prediction of dose–response on an organ-wide level. The quantitative integration of valuable datasets with engineering precision is expected to accelerate the clinical implementation of novel therapeutics. [ABSTRACT FROM PUBLISHER]

During the last decade, intraspinal microstimulation (ISMS) has been proposed as a potential technique for restoring motor function in paralyzed limbs. A major challenge to restoration of a desired functional limb movement through the use of ISMS is the development of a robust control strategy for determining the stimulation patterns. Accurate and stable control of limbs by functional intraspinal microstimulation is a very difficult task because neuromusculoskeletal systems have significant nonlinearity, time variability, large latency and time constant, and muscle fatigue. Furthermore, the controller must be able to compensate the effect of the dynamic interaction between motor neuron pools and electrode sites during ISMS. In this paper, we present a robust strategy for multi-joint control through ISMS in which the system parameters are adapted online and the controller requires no offline training phase. The method is based on the combination of sliding mode control with fuzzy logic and neural control. Extensive experiments on six rats are provided to demonstrate the robustness, stability, and tracking accuracy of the proposed method. Despite the complexity of the spinal neuronal networks, our results show that the proposed strategy could provide accurate tracking control with fast convergence and could generate control signals to compensate for the effects of muscle fatigue. [ABSTRACT FROM PUBLISHER]

Superconducting quantum interference device (SQUID)-based spinal cord evoked magnetic field (SCEF) measurement systems are being developed for the diagnosis of spinal cord diseases such as myelopathy. Previous papers have reported several SQUID magnetometers optimized for the detection of the magnetic field evoked by axonal nerve activity at the neck of subjects in sitting or supine positions, thus enabling noninvasive functional imaging of the cervical spinal cord. In this study, we implemented two improvements in the SQUID SCEF system to extend its application range and to make it suitable for practical use in hospitals. One was a newly designed cryostat that was implemented in order to apply the SCEF measurement not only to the cervical region but also to wider regions such as the lumbar or sacral regions. The other improvement was the implementation of SQUID driving electronics to detect not only conventional fast SCEF components accompanied by action potentials but also slow SCEF components resulting from postsynaptic activity. We also implemented direct flux feedback using a set of reference sensors composed of three SQUID magnetometers arranged in an orthogonal orientation in order to reduce noise. We then performed an SCEF measurement using the improved system and successfully observed the distribution of the magnetic field from the sacral region with a peak amplitude of less than 10 fT. [ABSTRACT FROM AUTHOR]

This review of spinal cord stimulation (SCS) and its technology begins with an overview of the history and background of electroanalgesia, from the use of electric fish in ancient times through the development of the first SCS devices. Discussion of the clinical goals of SCS as a treatment for neuropathic and ischemic pain includes accepted and emerging indications and focuses on various aspects of the technical goal of appropriate paresthesia coverage. While acknowledging that much remains to be discovered about the mechanisms of action of SCS, the review describes what is known about its neurochemical effects and summarizes the results of experimental and clinical studies that seek to illuminate why SCS is effective. After noting the importance and development of computer modeling studies that indicate ways to improve delivery of the electrical pulses, the review covers the advantages of various types of SCS electrodes and power generators and the use of computerized methods to optimize SCS therapy in individual patients and to provide information about the clinical performance of various types of equipment. Finally, this paper identifies important design issues and options as well as the challenges posed by various failure modes, by environmental and medical precautions, and by cost effectiveness and patient access issues. [ABSTRACT FROM AUTHOR]

Locomotor training using body weight support on a treadmill and manual assistance is a promising rehabilitation technique following neurological injuries, such as spinal cord injury (SC!) and stroke. Previous robots that automate this technique impose constraints on naturalistic walking due to their kinematic structure, and are typically operated in a stiff mode, limiting the ability of the patient or human trainer to influence the stepping pattern. We developed a pneumatic gait training robot that allows for a full range of natural motion of the legs and pelvis during treadmill walking, and provides compliant assistance. However, we observed an unexpected consequence of the device's compliance: unimpaired and SC! individuals invariably began walking out-of-phase with the device. Thus, the robot perturbed rather than assisted stepping. To address this problem, we developed a novel algorithm that synchronizes the device in real-time to the actual motion of the individual by sensing the state error and adjusting the replay timing to reduce this error. This paper describes data from experiments with individuals with SCI that demonstrate the effectiveness of the synchronization algorithm, and the potential of the device for relieving the trainers of strenuous work while maintaining naturalistic stepping. [ABSTRACT FROM AUTHOR]

In rehabilitation medicine, it is necessary for medical staff members to recommend the suitable computer input device for each patient with a spinal cord injury. This paper describes a measurement and evaluation system to determine the computer input ability of patients with tetraplegia. The authors will define a measurement procedure, a set of objective parameters, and a graphical representation of the parameters. They measure the position locus of the mouse cursor when a patient operates a computer using a computer input device. Using the representation, the medical staff can evaluate the patient's computer input ability and understand the characteristics of the patient's computer operation. [ABSTRACT FROM AUTHOR]

The effects of spinal cord injuries are likely to be ameliorated with the help of functional electrical stimulation of the spinal cord, a technique that may benefit from a new style of electrode: the cylindrical multielectrode. This paper describes the specifications for, fabrication techniques for, and in vitro evaluation of cylindrical multielectrodes. Four tip shapes were tested to determine which shape required the lowest peak force and would, therefore, be expected to minimize dimpling during implantation. The impedance of the electrode interface was monitored for changes due to insertion as well as repetitive delivery of current pulses. The charge delivery capacity was determined by testing with safe (≤ 0.6 mC/cm²) and damaging levels (≥ 0.8 mC/cm²) of charge density. The results of these tests suggest that this electrode design could be used to stimulate neurons in the ventral horn of the spinal cord. [ABSTRACT FROM AUTHOR]

Disturbances of the cerebrospinal fluid (CS) flow in the brain can lead to hydrocephalus, a condition affecting thousands of people annually in the US. Considerable controversy exists about fluid and pressure dynamics, and about how the brain cephalic.,This paper presents a new model based on the first principles of fluid mechanics,This model of fluid-structure in tractions predicts flow and pressures throughout the brain's ventricular pathways consistent with both animal intracranial pressure (ICP) measurements and human CINE haste-contrast magnetic resonance imagine f\data. The commotions provide approximation of the tissue deformations of the brain pre\aerenchyma. The model also aqueduct as well as the changes in ICP's due to brain tissue compression. It does not require the exist\fence of large transmural pressure differences as the force for ventricular expansion. Finally, the new model gives an explanation of communication Hydrocephalus and the phenomenon of asymmetric hydrocephalus. [ABSTRACT FROM AUTHOR]

Accurate planning of radiation therapy entails the definition of treatment volumes and a clear delimitation of normal tissue of which unnecessary exposure should be prevented. The spinal cord is a radiosensitive organ, which should be precisely identified because an overexposure to radiation may lead to undesired complications for the patient such as neuronal disfunction or paralysis. In this paper, a knowledge-based approach to identifying the spinal cord in computed tomography images of the thorax is presented. The approach relies on a knowledge-base which consists of a so-called anatomical structures map (ASM) and a task-oriented architecture called the plan solver. The ASM contains a frame-like knowledge representation of the macro-anatomy in the human thorax. The plan solver is responsible for determining the position, orientation and size of the structures of interest to radiation therapy. The plan solver relies on a number of image processing operators. Some are so-called atomic (e.g., thresholding and snakes) whereas others are composite. The whole system has been implemented on a standard PC. Experiments performed on the image material from 23 patients show that the approach results in a reliable recognition of the spinal cord (92% accuracy) and the spinal canal (85% accuracy). The lamina is more problematic to locate correctly (accuracy 72%). The position of the outer thorax is always determined correctly. [ABSTRACT FROM AUTHOR]

The recent development of genetically encoded calcium indicators enables monitoring in vivo the activity of neuronal populations. Most analysis of these calcium transients relies on linear regression analysis based on the sensory stimulus applied or the behavior observed. To estimate the basic properties of the functional neural circuitry, we propose a network approach to calcium imaging recorded at single cell resolution. Differently from previous analysis based on cross-correlation, we used Granger-causality estimates to infer information propagation between the activities of different neurons. The resulting functional network was then modeled as a directed graph and characterized in terms of connectivity and node centralities. We applied our approach to calcium transients recorded at low frequency (4 Hz) in ventral neurons of the zebrafish spinal cord at the embryonic stage when spontaneous coiling of the tail occurs. Our analysis on population calcium imaging data revealed a strong ipsilateral connectivity and a characteristic hierarchical organization of the network hubs that supported established propagation of activity from rostral to caudal spinal cord. Our method could be used for detecting functional defects in neuronal circuitry during development and pathological conditions. [ABSTRACT FROM AUTHOR]

Surface electromyography (EMG) signals have shown promising applications in human-machine interfacing (HMI) systems such as orthotics, prosthetics, and exoskeletons. Nevertheless, existing myoelectric control methods, generally based on time-domain or frequency-domain features, could not directly interpret neural commands. EMG decomposition techniques have become a prevailing solution to decode the motor neuron discharges from the spinal cord, whereas only single degree-of-freedom (DoF) movements are primarily involved in the current neural-based interfaces, resulting in limited intuitiveness and functionality. Here, we propose a non-invasive framework to analyze motor unit activities and estimate wrist torques during simultaneous contractions of multiple DoFs. Motor unit discharges were decoded from surface EMG signals and pooled into groups during sequential wrist movements. Then three neural features were extracted and linearly projected to the torques of multi-DoF tasks. On average, there were 44 $\pm$ 13 motor units identified for each motion with a PNR value of 25.8 $\pm$ 2.9 dB. The neural features outperformed the classic EMG feature on the estimation accuracy with higher correlation coefficients and smoothness. These results demonstrate the feasibility and superiority of the proposed framework in kinetics estimation of simultaneous movements, extending the potential applications of surface EMG decomposition in human-machine interfaces. [ABSTRACT FROM AUTHOR]

In recent years, the parity–time (PT) symmetry principle has been introduced into wireless power transfer (WPT) systems, which can improve the stability of WPT within a certain range. In this article, we analyze the generalized PT-symmetry conditions of four basic WPT topologies based on circuit theory (CT) and coupled mode theory (CMT). The results show that the series–parallel (SP) topology meets the PT-symmetry condition based on the CMT, although it does not meet the condition obtained by the CT. The symmetry between the energy of the two-resonance system is established in the SP topology. According to this unique characteristic, a constant-voltage WPT system for spinal cord stimulation is designed, which is independent of the transfer distance and load in a wide range. [ABSTRACT FROM AUTHOR]

Neural interfacing is essential for advancing our fundamental understanding of movement neurophysiology and for developing human-machine interaction systems. This can be achieved at different levels of the central nervous system (CNS) and peripheral nervous system (PNS); however, direct neural interfaces with brain and nerve tissues face important challenges and are currently limited to clinical cases of severe motor impairment. Recent advances in electronics and signal processing for recording and analyzing surface electromyographic (sEMG) signals allow for a radically new way of establishing human interfaces by reverse engineering the neural information embedded in the electrical activity of skeletal muscles. This approach provides a window into the spiking activity of motor neurons in the spinal cord. In this article, we present a brief overview of neural interfaces and discuss the properties of multichannel sEMG in comparison to other CNS and PNS recording modalities. We then describe signal processing approaches for neural interfacing from sEMG, with a focus on recent breakthroughs in convolutive blind source separation (BSS) methods and deep learning techniques. When combined, these approaches establish unique noninvasive human-machine interfaces for neurotechnologies, with applications in medical devices and large-scale consumer electronics. [ABSTRACT FROM AUTHOR]

Recent developments in the field of cellular therapeutics have indicated the potential of stem cell injections directly to the spinal cord. Injections require either open surgery or a Magnetic Resonance Imaging (MRI) guided injection. Needle positioning during MRI imaging is a significant hurdle to direct spinal injection, as the small target region and interlaminar space require high positioning accuracy. Objective: To improve both the procedure time and positioning accuracy, an MRI guided robotic needle positioning system is developed. Methods: The robot uses linear piezoelectric motors to directly drive a parallel plane positioning mechanism. Feedback is provided through MRI during the orientation procedure. Both accuracy and repeatability of the robot are characterized. Results: This system is found to be capable of repeatability below 51 μm. Needle endpoint error is limited by imaging modality, but is validated to 156 μm. Conclusion: The reported robot and MRI image feedback system is capable of repeatable and accurate needle guide positioning. Significance: This high accuracy will result in a significant improvement to the workflow of spinal injection procedures. [ABSTRACT FROM AUTHOR]

Spinal Cord Injury (SCI) is a severe condition that can result in loss of motor and sensory functions by disrupting communication among neurons, i.e., neuro-spike communication. Future information and communication technology (ICT) based treatment techniques for SCI are expected to rely on nano networks, deployed inside the body. In this respect, modeling neuro-spike communication channels in the spinal cord and revealing the relationship between channel metrics and SCI are required to realize these treatment techniques and diagnosis tools such as replacement neural implants, high-performance diagnosis tools, which are based on ICT metrics instead of large medical data. Therefore, in this study, we focus on a spinal cord network, namely the descending spinal cord pathway, which is responsible for the transmission of brain motor signals to the spinal cord. We aim to analyze the rate of motor information flow to the corresponding muscle. To this end, we model the spinal cord motor network as a layered network consisting of a cascade of two independent neuro-spike channels, which are brain-spinal cord network and spinal cord interneuron-spinal cord motoneuron network. We derive upper and lower bounds for the total rate across the brain-spinal cord network and interneuron-spinal cord network. Our evaluations demonstrate that the total rate in the case of upper motor neuron syndrome (UMNS), which manifests itself with muscle weakness, approaches zero, where the brain-spinal cord network becomes a bottleneck. In lower motor neuron syndrome (LMNS), which results in muscle atrophy, the total rate again approaches zero with the loss of spinal cord motoneurons (MN). [ABSTRACT FROM AUTHOR]

Powered exoskeletons are among the emerging technologies claiming to assist functional ambulation. The potential to adapt robotic assistance based on specific motor abilities of incomplete spinal cord injury (iSCI) subjects, is crucial to optimize Human-Robot Interaction (HRI). Achilles, an autonomous wearable robot able to assist ankle during walking, was developed for iSCI subjects and utilizes a NeuroMuscular Controller (NMC). NMC can be used to adapt robotic assistance based on specific residual functional abilities of subjects. The main aim of this pilot study was to analyze the effects of the NMC-controlled Achilles, used as an assistive device, on chronic iSCI participants’ performance, by assessing gait speed during 10-session training of robot-aided walking. Secondary aims were to assess training impact on participants’ motion, clinical and functional features and to evaluate subjective perspective in terms of attitude towards technology, workload, usability and satisfaction. Results showed that 5 training sessions were necessary to significantly improve robot-aided gait speed on short paths and consequently to optimize HRI. Moreover, the training allowed participants who initially were not able to walk for 6 minutes, to improve gait endurance during Achilles-aided walking and to reduce perceived fatigue. Improvements were obtained also in gait speed during free walking, thus suggesting a potential rehabilitative impact, even if Achilles-aided walking was not faster than free walking. Participants’ subjective evaluations indicated a positive experience. [ABSTRACT FROM AUTHOR]

Nearly all spinal cord injured (SCI) individuals lose bladder control and are prone to kidney complications if intermittent catheterization is not applied. Electrical stimulation of the sacral anterior roots with an implantable neuroprosthesis is one means to restore continence and control micturition. However, only a small percentage of the SCI population benefits from this solution because of its drawbacks, e.g., section of sacral posterior roots with loss of spared sensitivity. There has been renewed interest in spinal cord stimulation in recent years, but most studies have focused on locomotion and only few have reported the impact on visceral functions. Moreover, even though the lumbosacral spinal cord is the location of many pre-cabled neural networks (involved in locomotion, bladder, and bowel management), the functional selectivity of spinal stimulations has never been investigated in detail. Here, we present: 1) a methodology designed to study lumbosacral epispinal-intradural stimulation selectivity; 2) preliminary results assessing the impact of epispinal stimulation on bladder and bowel functions in two domestic pigs; and 3) a comparison of these visceral responses with abdominal and lower limb activities. Our experiments resulted in selective bladder and rectal responses, i.e., without hind paw responses, thus reaffirming the rehabilitation potential of spinal cord stimulation. [ABSTRACT FROM AUTHOR]

This brief presents a 15-channel, 30-V, implantable current stimulator for restoring locomotion control after spinal cord injuries. The stimulator features performance specifications comparable to those of large desktop instrumentation: high linearity, high precision of the delivered currents, small channel-to-channel mismatches, and a fast settling time of $0.3~\mu \text{s}$. An analog-to-digital converter-based active charge balancing scheme using a digital proportional–integral controller was implemented in firmware. [ABSTRACT FROM AUTHOR]