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Neural Systems and Rehabilitation Engineering, IEEE Transactions on

Issue 4 • Date Aug. 2008

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Displaying Results 1 - 19 of 19
  • [Front cover]

    Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Neural Systems and Rehabilitation Engineering publication information

    Page(s): C2
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    Freely Available from IEEE
  • Comparative Analysis of Spectral Approaches to Feature Extraction for EEG-Based Motor Imagery Classification

    Page(s): 317 - 326
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1087 KB)  

    The quantification of the spectral content of electroencephalogram (EEG) recordings has a substantial role in clinical and scientific applications. It is of particular relevance in the analysis of event-related brain oscillatory responses. This work is focused on the identification and quantification of relevant frequency patterns in motor imagery (MI) related EEGs utilized for brain-computer interface (BCI) purposes. The main objective of the paper is to perform comparative analysis of different approaches to spectral signal representation such as power spectral density (PSD) techniques, atomic decompositions, time-frequency (t-f) energy distributions, continuous and discrete wavelet approaches, from which band power features can be extracted and used in the framework of MI classification. The emphasis is on identifying discriminative properties of the feature sets representing EEG trials recorded during imagination of either left- or right-hand movement. Feature separability is quantified in the offline study using the classification accuracy (CA) rate obtained with linear and nonlinear classifiers. PSD approaches demonstrate the most consistent robustness and effectiveness in extracting the distinctive spectral patterns for accurately discriminating between left and right MI induced EEGs. This observation is based on an analysis of data recorded from eleven subjects over two sessions of BCI experiments. In addition, generalization capabilities of the classifiers reflected in their intersession performance are discussed in the paper. View full abstract»

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  • Automatic Classification of Athletes With Residual Functional Deficits Following Concussion by Means of EEG Signal Using Support Vector Machine

    Page(s): 327 - 335
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (916 KB)  

    There is a growing body of knowledge indicating long-lasting residual electroencephalography (EEG) abnormalities in concussed athletes that may persist up to 10-year postinjury. Most often, these abnormalities are initially overlooked using traditional concussion assessment tools. Accordingly, premature return to sport participation may lead to recurrent episodes of concussion, increasing the risk of recurrent concussions with more severe consequences. Sixty-one athletes at high risk for concussion (i.e., collegiate rugby and football players) were recruited and underwent EEG baseline assessment. Thirty of these athletes suffered from concussion and were retested at day 30 postinjury. A number of task-related EEG recordings were conducted. A novel classification algorithm, the support vector machine (SVM), was applied as a classifier to identify residual functional abnormalities in athletes suffering from concussion using a multichannel EEG data set. The total accuracy of the classifier using the 10 features was 77.1%. The classifier has a high sensitivity of 96.7% (linear SVM), 80.0% (nonlinear SVM), and a relatively lower but acceptable selectivity of 69.1% (linear SVM) and 75.0% (nonlinear SVM). The major findings of this report are as follows: 1) discriminative features were observed at theta, alpha, and beta frequency bands, 2) the minimal redundancy relevance method was identified as being superior to the univariate -test method in selecting features for the model calculation, 3) the EEG features selected for the classification model are linked to temporal and occipital areas, and 4) postural parameters influence EEG data set and can be used as discriminative features for the classification model. Overall, this report provides sufficient evidence that 10 EEG features selected for final analysis and SVM may be potentially used in clinical practice for automatic classification of athletes with residual brain functional abnormalities following a concussion episod- - e. View full abstract»

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  • Nonlinear Modeling of Causal Interrelationships in Neuronal Ensembles

    Page(s): 336 - 352
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    The increasing availability of multiunit recordings gives new urgency to the need for effective analysis of ldquomultidimensionalrdquo time-series data that are derived from the recorded activity of neuronal ensembles in the form of multiple sequences of action potentials-treated mathematically as point-processes and computationally as spike-trains. Whether in conditions of spontaneous activity or under conditions of external stimulation, the objective is the identification and quantification of possible causal links among the neurons generating the observed binary signals. A multiple-input/multiple-output (MIMO) modeling methodology is presented that can be used to quantify the neuronal dynamics of causal interrelationships in neuronal ensembles using spike-train data recorded from individual neurons. These causal interrelationships are modeled as transformations of spike-trains recorded from a set of neurons designated as the ldquoinputsrdquo into spike-trains recorded from another set of neurons designated as the ldquooutputsrdquo. The MIMO model is composed of a set of multiinput/single-output (MISO) modules, one for each output. Each module is the cascade of a MISO Volterra model and a threshold operator generating the output spikes. The Laguerre expansion approach is used to estimate the Volterra kernels of each MISO module from the respective input-output data using the least-squares method. The predictive performance of the model is evaluated with the use of the receiver operating characteristic (ROC) curve, from which the optimum threshold is also selected. The Mann-Whitney statistic is used to select the significant inputs for each output by examining the statistical significance of improvements in the predictive accuracy of the model when the respective inputs is included. Illustrative examples are presented for a simulated system and for an actual application using multiunit data recordings from the hippocampus of a behaving rat. View full abstract»

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  • Linear Time Delay Methods and Stability Analyses of the Human Spine. Effects of Neuromuscular Reflex Response

    Page(s): 353 - 359
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (773 KB) |  | HTML iconHTML  

    Linear stability methods were applied to a biomechanical model of the human musculoskeletal spine to investigate effects of reflex gain and reflex delay on stability. Equations of motion represented a dynamic 18 degrees-of-freedom rigid-body model with time-delayed reflexes. Optimal muscle activation levels were identified by minimizing metabolic power with the constraints of equilibrium and stability with zero reflex time delay. Muscle activation levels and associated muscle forces were used to find the delay margin, i.e., the maximum reflex delay for which the system was stable. Results demonstrated that stiffness due to antagonistic co-contraction necessary for stability declined with increased proportional reflex gain. Reflex delay limited the maximum acceptable proportional reflex gain, i.e., long reflex delay required smaller maximum reflex gain to avoid instability. As differential reflex gain increased, there was a small increase in acceptable reflex delay. However, differential reflex gain with values near intrinsic damping caused the delay margin to approach zero. Forward-dynamic simulations of the fully nonlinear time-delayed system verified the linear results. The linear methods accurately found the delay margin below which the nonlinear system was asymptotically stable. These methods may aid future investigations in the role of reflexes in musculoskeletal stability. View full abstract»

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  • The Effects on Kinematics and Muscle Activity of Walking in a Robotic Gait Trainer During Zero-Force Control

    Page(s): 360 - 370
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    “Assist as needed” control algorithms promote activity of patients during robotic gait training. Implementing these requires a free walking mode of a device, as unassisted motions should not be hindered. The goal of this study was to assess the normality of walking in the free walking mode of the LOPES gait trainer, an 8 degrees-of-freedom lightweight impedance controlled exoskeleton. Kinematics, gait parameters and muscle activity of walking in a free walking mode in the device were compared with those of walking freely on a treadmill. Average values and variability of the spatio-temporal gait variables showed no or small (relative to cycle-to-cycle variability) changes and the kinematics showed a significant and relevant decrease in knee angle range only. Muscles involved in push off showed a small decrease, whereas muscles involved in acceleration and deceleration of the swing leg showed an increase of their activity. Timing of the activity was mainly unaffected. Most of the observed differences could be ascribed to the inertia of the exoskeleton. Overall, walking with the LOPES resembled free walking, although this required several adaptations in muscle activity. These adaptations are such that we expect that Assist as Needed training can be implemented in LOPES. View full abstract»

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  • Assistive Control System Using Continuous Myoelectric Signal in Robot-Aided Arm Training for Patients After Stroke

    Page(s): 371 - 379
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1016 KB)  

    In some stroke rehabilitation programs, robotic systems have been used to aid the patient to train. In this study, a myoelectrically controlled robotic system with 1 degree-of-freedom was developed to assist elbow training in a horizontal plane with intention involvement for people after stroke. The system could provide continuous assistance in extension torque, which was proportional to the amplitude of the subject's electromyographic (EMG) signal from the triceps, and could provide resistive torques during movement. This study investigated the system's effect on restoring the upper limb functions of eight subjects after chronic stroke in a twenty-session rehabilitation training program. In each session, there were 18 trials comprising different combinations of assistive and resistive torques and an evaluation trial. Each trial consisted of five cycles of repetitive elbow flexion and extension between 90deg and 0deg at a constant velocity of 10deg /s. With the assistive extension torque, subjects could reach a more extended position in the first session. After 20 sessions of training, there were statistically significant improvements in the modified Ashworth scale, Fugl-Meyer scale for shoulder and elbow, motor status scale, elbow extension range, muscle strength, and root mean square error between actual elbow angle and target angle. The results showed that the twenty-session training program improved upper limb functions. View full abstract»

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  • Investigating Scale Invariant Dynamics in Minimum Toe Clearance Variability of the Young and Elderly During Treadmill Walking

    Page(s): 380 - 389
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (753 KB)  

    Current research applying variability measures of gait parameters has demonstrated promise for helping to solve one of the “holy grails” of geriatric research by defining markers that can be used to prospectively identify persons at risk of falling . The minimum toe clearance (MTC) event occurs during the leg swing phase of the gait cycle and is a task highly sensitive to the spatial and balance control properties of the locomotor system. The aim of this study is to build upon the current state of research by investigating the magnitude and dynamic structure from the MTC time series fluctuations due to aging and locomotor disorder. Thirty healthy young (HY), 27 healthy elderly (HE), and 10 falls risk (FR) elderly individuals (who presented a prior history of trip-related falls) participated in treadmill walking for at least 10 min at their preferred speed. Continuous MTC data were collected and the first 512 data points were analyzed. The following variability indices were quantified: 1) MTC mean and standard deviation (SD), 2) PoincarÉ plot indices of MTC variability (SD1, SD2, SD1/SD2), 3) a wavelet based multiscale exponent \beta to describe the dynamic structure of MTC fluctuations, and 4) detrended fluctuation analysis exponent \alpha to investigate the presence of long-range correlations in MTC time series data. Results showed that stride-to-stride MTC time series has a nonlinear structure in all three groups when compared against randomly shuffled surrogate MTC data. Test on aging effects showed the MTC central tendency was significantly lower (p\ll 0.01) and the magnitude of the MTC variability significantly higher (p\ll 0.01) . This trend changed when - - comparing FR subjects against age-matched HE as both the central tendency (p\ll 0.01) and magnitude of the variability (p\ll 0.01) increased significantly in FR. Although the magnitude of MTC variability increased with age, the nonlinear indices represented by \alpha , \beta , and SD1/SD2 demonstrated that the nonlinear structure of MTC does not change significantly due to aging (p>0.05) . There were, however, significant differences between HY and FR for \beta (between scale 1 and 2; p\ll 0.01 ) and \alpha (p\ll 0.05) . Out of all the variability measures applied, \beta _{{\rm Wv}2-4} , SD1/SD2, SD2 of critical MTC parameter were found to be potential markers to be able to reliably identify FR from HE subjects. Further research is required to understand the mechanisms underlying the cause of MTC variability. View full abstract»

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  • An ElectroHydraulic Actuated Ankle Foot Orthosis to Generate Force Fields and to Test Proprioceptive Reflexes During Human Walking

    Page(s): 390 - 399
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1081 KB) |  | HTML iconHTML  

    The control of human walking can be temporarily modified by applying forces to the leg. To study the neural mechanisms underlying this adaptive capacity, a device delivering controlled forces and high-velocity displacements to the ankle was designed. A new solution, involving a closed circuit hydraulic system composed of two cylinders (master-slave) mutually connected by hoses and controlled by an electric motor was preferred over classical mechanical/electrical approaches. The slave cylinder delivers desired torques to the ankle using a light weight, custom-designed ankle-foot orthosis. This electrohydraulic orthosis (EHO) can produce several types of force fields during walking, including constant, position-dependent, and phase-dependent. With phase-dependent force fields, active torque cancellation maintains low-residual torques (les1.85 Nm root mean square) outside of the zone of force application for walking speeds ranging from 0.2 to 4.5 km/h. Rapid ankle stretches/unloads (>200deg/s) can also be produced alone or during force field application, and elicited proprioceptive reflexes in ankle muscles. In conclusion, the EHO is capable of delivering controlled force fields and of activating proprioceptive reflexes during human walking. It will provide the flexibility needed to test the adaptability of healthy and pathological gait control, and to address some of its underlying neural mechanisms. View full abstract»

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  • Computational Modeling of User Errors for the Design of Virtual Scanning Keyboards

    Page(s): 400 - 409
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (780 KB) |  | HTML iconHTML  

    Virtual scanning keyboards are used by persons with severe speech and motion impairments as communication aids. Each of these systems consists of a virtual keyboard and a ldquoscanning and access switchrdquo based alternate input method. Designers of such keyboards face problems due to the difficulties in testing prototypes with disabled users. Model-based design approaches were proposed in order to alleviate the problems. In model-based design, systems are evaluated with user models reducing the need for extensive user testing. The existing model-based approaches, however, do not consider the effect of user errors in evaluating systems. The lack of consideration of errors limits the practical usefulness of the resulting designs. To overcome this limitation, we have performed empirical studies of errors on virtual scanning keyboards. From our study results, we have derived predictive models of user's error behavior. We have used the models to develop ldquoErrorProneness,rdquo a numerical error measure for virtual scanning keyboards. We have proposed a method using the ldquoErrorPronenessrdquo measure for taking the effects of errors into account in model-based design. Methods employed in our study, results obtained, the predictive user models, the error measure, and the proposed design method are presented in this paper. View full abstract»

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  • Receptive Field Characteristics Under Electrotactile Stimulation of the Fingertip

    Page(s): 410 - 415
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (476 KB)  

    Skin on human fingertips has high concentrations of mechanoreceptors, which are used to provide fine resolution tactile representations of our environment. Here, we explore the ability to discriminate electrotactile stimulation at four sites on the fingertip. Electrical stimulation was delivered to arrays of electrodes centered on the index fingertip (volar aspect). Accuracy of discrimination was tested by examining electrode size, interelectrode spacing, and stimulation frequency as primary factors. Electrical stimulation was delivered at 2 mA with the pulse width modulated to be at (or above) perceptual threshold at 25 and 75 Hz and an average pulse width of 1.03 ms ( +/- 0.70 ms standard deviation). Discrimination of the stimulated locations under this stimulation paradigm was significantly above chance level in all cases. Subjects' ability to discriminate stimulus location was not significantly influenced by electrode size or stimulation frequency when considered as separate factors. However, increased electrode spacing significantly increased subjects' ability to discriminate the location of the stimulated electrode. Further analysis revealed that errors were only significantly reduced along the medial-lateral direction with increasing interelectrode spacing. These results suggest that the electrotactile stimulus localization on the fingertip has some directional dependency, in addition to its dependency on interelectrode spacing. The neural mechanisms underlying this phenomenon are discussed in relation to electrical stimulus transduction characteristics of tactile mechanoreceptors. View full abstract»

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  • Stimulation of the Expiratory Muscles Using Microstimulators

    Page(s): 416 - 420
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    Respiratory complications constitute a major cause of morbidity and mortality in patients with spinal cord injury. These complications arise in part due to the loss of supraspinal control over the expiratory muscles and the resultant difficulties in clearing airway secretions effectively. The purpose of the present study is to evaluate the efficacy of lower thoracic spinal nerve stimulation using wireless microstimulators in activating the expiratory muscles. Studies were performed on nine anesthetized dogs. A thoracic laminectomy was performed on each dog, and was followed by spinal cord transection at T2. A total of 16 microstimulators (supplied by the Alfred Mann Foundation, Santa Clarita, CA) were inserted percutaneously into the bilateral intercostal nerves approximately 1 \sim 3 cm distal to the neuroforamen from T7 to L1 in each dog. The stimulation parameters were: frequency of 20 Hz , pulse width of 200 \mu{\rm s} , and stimulation burst of 2 s. The stimulation intensities were 3.78, 5.4, 8.1, and 10.8 mA. The pressure-generating capacity of the expiratory muscles was evaluated by the change in airway pressure ({\rm P}_{\rm aw}) at functional residual capacity, which was produced by the microstimulators during airway occlusion. As a general trend, the expiratory pressure generated using the microstimulators increased with increasing intensity and the number of spinal nerves recruited. The maximal expiratory pressures generated from one, two, three, four, five, six, seven, and eight pairs of spinal nerves were 8.4 \pm 0.8, 12.2 \pm 1.0, 14.6 \pm 1.4, 17.8 \pm 1.8, 23.0 View full abstract»

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  • Correction to "Asynchronous Decoding of Dexterous Finger Movements Using M1 Neurons" [Feb 08 3-14]

    Page(s): 421
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (29 KB) |  | HTML iconHTML  

    In the above titled paper (ibid., vol. 16, no. 1, pp. 3-14, Feb 08), there were a few errors. Corrections are presented here. View full abstract»

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  • The 4th International IEEE EMBS Conference on Neural Engineering

    Page(s): 422
    Save to Project icon | Request Permissions | PDF file iconPDF (429 KB)  
    Freely Available from IEEE
  • Engineering the Future of Biomedicine

    Page(s): 423
    Save to Project icon | Request Permissions | PDF file iconPDF (618 KB)  
    Freely Available from IEEE
  • Systems thinking?

    Page(s): 424
    Save to Project icon | Request Permissions | PDF file iconPDF (580 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Neural Systems and Rehabilitation Engineering Information for authors

    Page(s): C3
    Save to Project icon | Request Permissions | PDF file iconPDF (28 KB)  
    Freely Available from IEEE
  • Table of contents

    Page(s): C4
    Save to Project icon | Request Permissions | PDF file iconPDF (34 KB)  
    Freely Available from IEEE

Aims & Scope

IEEE Transactions on Neural Systems and Rehabilitation Engineering focuses on the rehabilitative and neural aspects of biomedical engineering.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Paul Sajda
Columbia University