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Neural Systems and Rehabilitation Engineering, IEEE Transactions on

Issue 6 • Date Nov. 2013

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  • [Front cover]

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  • IEEE Transactions on Neural Systems and Rehabilitation Engineering publication information

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  • High-Density Intracortical Microelectrode Arrays With Multiple Metallization Layers for Fine-Resolution Neuromonitoring and Neurostimulation

    Page(s): 869 - 879
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    Intracortical microelectrodes play a prominent role in the operation of neural interfacing systems. They provide an interface for recording neural activities and modulating their behavior through electric stimulation. The performance of such systems is thus directly meliorated by advances in electrode technology. We present a new architecture for intracortical electrodes designed to increase the number of recording/stimulation channels for a given set of shank dimensions. The architecture was implemented on silicon using microfabrication process and fabricated 3-mm-long electrode shanks with six relatively large (110 μm×110 μm) pads in each shank for electrographic signal recording to detect important precursors with potential clinical relevance and electrical stimulation to correct neural behavior with low-power dissipation in an implantable device. Moreover, an electrode mechanical design was developed to increase its stiffness and reduce shank deflection to improve spatial accuracy during an electrode implantation. Furthermore, the pads were post-processed using pulsated low current electroplating and reduced their impedances by ~ 30 times compared to the traditionally fabricated pads. The paper also presents microfabrication process, electrodes characterization, comparison to the commercial equivalents, and in vitro and in vivo validations. View full abstract»

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  • Seizure Prediction Using Spike Rate of Intracranial EEG

    Page(s): 880 - 886
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    Reliable prediction of forthcoming seizures will be a milestone in epilepsy research. A method capable of timely predicting the occurrence of seizures could significantly improve the quality of life for epilepsy patients and open new therapeutic approaches. Seizures are usually characterized by generalized spike wave discharges. With the advent of seizures, the variation of spike rate (SR) will have different manifestations. In this study, a seizure prediction approach based on spike rate is proposed and evaluated. Firstly, a low-pass filter is applied to remove the high frequency artifacts in electroencephalogram (EEG). Then, the morphology filter is used to detect spikes and compute SR, and SR is smoothed with an average filter. Finally, the performance of smoothed SR (SRm) in EEG during interictal, preictal, and ictal periods is analyzed and employed as an index for seizure prediction. Experiments with long-term intracranial EEGs of 21 patients show that the proposed seizure prediction approach achieves a sensitivity of 75.8% with an average false prediction rate of 0.09/h. The low computational complexity of the proposed approach enables its possibility of applications in an implantable device for epilepsy therapy. View full abstract»

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  • L1-Regularized Multiway Canonical Correlation Analysis for SSVEP-Based BCI

    Page(s): 887 - 896
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    Canonical correlation analysis (CCA) between recorded electroencephalogram (EEG) and designed reference signals of sine-cosine waves usually works well for steady-state visual evoked potential (SSVEP) recognition in brain-computer interface (BCI) application. However, using the reference signals of sine- cosine waves without subject-specific and inter-trial information can hardly give the optimal recognition accuracy, due to possible overfitting, especially within a short time window length. This paper introduces an L1-regularized multiway canonical correlation analysis (L1-MCCA) for reference signal optimization to improve the SSVEP recognition performance further. A multiway extension of the CCA, called MCCA, is first presented, in which collaborative CCAs are exploited to optimize the reference signals in correlation analysis for SSVEP recognition alternatingly from the channel-way and trial-way arrays of constructed EEG tensor. L1-regularization is subsequently imposed on the trial-way array optimization in the MCCA, and hence results in the more powerful L1-MCCA with function of effective trial selection. Both the proposed MCCA and L1-MCCA methods are validated for SSVEP recognition with EEG data from 10 healthy subjects, and compared to the ordinary CCA without reference signal optimization. Experimental results show that the MCCA significantly outperforms the CCA for SSVEP recognition. The L1-MCCA further improves the recognition accuracy which is significantly higher than that of the MCCA. View full abstract»

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  • The Component Structure of Event-Related Potentials in the P300 Speller Paradigm

    Page(s): 897 - 907
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    We investigated the componential structure of event-related potentials elicited while participants use the P300 BCI. Six healthy participants “typed” all characters in a 6 × 6 matrix twice in a random sequence. A principal component analysis indicated that in addition to the P300, target flashes elicited an earlier frontal positivity, possibly a Novelty P3. The amplitudes of both P300 and the Novelty P3 varied with the matrix row in which the target character was located. However, the P300 elicited by row flashes was largest for targets in the lower part of the matrix, whereas the Novelty P3 elicited by column flashes was largest in the top part. Classification accuracy using stepwise linear discriminant analysis mirrored the pattern in the Novelty P3 (an accuracy difference of 0.1 between rows 1 and 6). When separate classifiers were generated to rely solely on the P300 or solely on the Novelty P3, the latter function led to higher accuracy (a mean accuracy difference of about 0.2 between classifiers). A possible explanation is that some nontarget flashes elicit a P300, leading to lower selection accuracy of the respective classifier. In an additional set of data from six different participants we replicated the ERP structure of the initial analyses and characterized the spatial distributions more closely by using a dense electrode array. Overall, our findings provide new insights in the componential structure of ERPs elicited in the P300 speller paradigm and have important implications for optimizing the speller's selection accuracy. View full abstract»

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  • Automated Detection of Instantaneous Gait Events Using Time Frequency Analysis and Manifold Embedding

    Page(s): 908 - 916
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    Accelerometry is a widely used sensing modality in human biomechanics due to its portability, non-invasiveness, and accuracy. However, difficulties lie in signal variability and interpretation in relation to biomechanical events. In walking, heel strike and toe off are primary gait events where robust and accurate detection is essential for gait-related applications. This paper describes a novel and generic event detection algorithm applicable to signals from tri-axial accelerometers placed on the foot, ankle, shank or waist. Data from healthy subjects undergoing multiple walking trials on flat and inclined, as well as smooth and tactile paving surfaces is acquired for experimentation. The benchmark timings at which heel strike and toe off occur, are determined using kinematic data recorded from a motion capture system. The algorithm extracts features from each of the acceleration signals using a continuous wavelet transform over a wide range of scales. A locality preserving embedding method is then applied to reduce the high dimensionality caused by the multiple scales while preserving salient features for classification. A simple Gaussian mixture model is then trained to classify each of the time samples into heel strike, toe off or no event categories. Results show good detection and temporal accuracies for different sensor locations and different walking terrains. View full abstract»

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  • On the Construction of a Skill-Based Wheelchair Navigation Profile

    Page(s): 917 - 927
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    Assisted wheelchair navigation is of key importance for persons with severe disabilities. The problem has been solved in different ways, usually based on the shared control paradigm. This paradigm consists of giving the user more or less control on a need basis. Naturally, these approaches require personalization: each wheelchair user has different skills and needs and it is hard to know a priori from diagnosis how much assistance must be provided. Furthermore, since there is no such thing as an average user, sometimes it is difficult to quantify the benefits of these systems. This paper proposes a new method to extract a prototype user profile using real traces based on more than 70 volunteers presenting different physical and cognitive skills. These traces are clustered to determine the average behavior that can be expected from a wheelchair user in order to cope with significant situations. Processed traces provide a prototype user model for comparison purposes, plus a simple method to obtain without supervision a skill-based navigation profile for any user while he/she is driving. This profile is useful for benchmarking but also to determine the situations in which a given user might require more assistance after evaluating how well he/she compares to the benchmark. Profile-based shared control has been successfully tested by 18 volunteers affected by left or right brain stroke at Fondazione Santa Lucia, in Rome, Italy. View full abstract»

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  • A System for Delivering Mechanical Stimulation and Robot-Assisted Therapy to the Rat Whisker Pad During Facial Nerve Regeneration

    Page(s): 928 - 937
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    Functional recovery is typically poor after facial nerve transection and surgical repair. In rats, whisking amplitude remains greatly diminished after facial nerve regeneration, but can recover more completely if the whiskers are periodically mechanically stimulated during recovery. Here we present a robotic “whisk assist” system for mechanically driving whisker movement after facial nerve injury. Movement patterns were either preprogrammed to reflect natural amplitudes and frequencies, or movements of the contralateral (healthy) side of the face were detected and used to control real-time mirror-like motion on the denervated side. In a pilot study, 20 rats were divided into nine groups and administered one of eight different whisk assist driving patterns (or control) for 5-20 minutes, five days per week, across eight weeks of recovery after unilateral facial nerve cut and suture repair. All rats tolerated the mechanical stimulation well. Seven of the eight treatment groups recovered average whisking amplitudes that exceeded controls, although small group sizes precluded statistical confirmation of group differences. The potential to substantially improve facial nerve recovery through mechanical stimulation has important clinical implications, and we have developed a system to control the pattern and dose of stimulation in the rat facial nerve model. View full abstract»

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  • Powered Hip Exoskeletons Can Reduce the User's Hip and Ankle Muscle Activations During Walking

    Page(s): 938 - 948
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    In this paper, we study the human locomotor adaptation to the action of a powered exoskeleton providing assistive torque at the user's hip during walking. To this end, we propose a controller that provides the user's hip with a fraction of the nominal torque profile, adapted to the specific gait features of the user from Winter's reference data . The assistive controller has been implemented on the ALEX II exoskeleton and tested on ten healthy subjects. Experimental results show that when assisted by the exoskeleton, users can reduce the muscle effort compared to free walking. Despite providing assistance only to the hip joint, both hip and ankle muscles significantly reduced their activation, indicating a clear tradeoff between hip and ankle strategy to propel walking. View full abstract»

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  • Real-Time Motor Unit Identification From High-Density Surface EMG

    Page(s): 949 - 958
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    This study addresses online decomposition of high-density surface electromyograms (EMG) in real time. The proposed method is based on the previously published Convolution Kernel Compensation (CKC) technique and shares the same decomposition paradigm, i.e., compensation of motor unit action potentials and direct identification of motor unit (MU) discharges. In contrast to previously published version of CKC, which operates in batch mode and requires ~ 10 s of EMG signal, the real-time implementation begins with batch processing of ~ 3 s of the EMG signal in the initialization stage and continues on with iterative updating of the estimators of MU discharges as blocks of new EMG samples become available. Its detailed comparison to previously validated batch version of CKC and asymptotically Bayesian optimal linear minimum mean square error (LMMSE) estimator demonstrates high agreement in identified MU discharges among all three techniques. In the case of synthetic surface EMG with 20 dB signal-to-noise ratio, MU discharges were identified with average sensitivity of 98%. In the case of experimental EMG, real-time CKC fully converged after initial 5 s of EMG recordings and real-time and batch CKC agreed on 90% of MU discharges, on average. The real-time CKC identified slightly fewer MUs than its batch version (experimental EMG, 4 MUs versus 5 MUs identified by batch CKC, on average), but required only 0.6 s of processing time on regular personal computer for each second of multichannel surface EMG. View full abstract»

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  • Assisting Versus Repelling Force-Feedback for Learning of a Line Following Task in a Wheelchair

    Page(s): 959 - 968
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    Previous work has shown that training with the “assist-as-needed” method using a force-feedback joystick can improve the driving performance of children and adults. This paper is the first study to evaluate training with a repelling force versus an assisting force for learning of a line following task in a wheelchair through a force-feedback joystick. We designed a robotic training wheelchair, that can accurately localize itself in the training environment, and implemented assisting and repelling force fields on the force-feedback joystick. The training protocol included three groups. The control (CT) group received no force feedback. The assisting force (AF) group was trained using the “assist-as-needed” paradigm. The repelling force (RF) group was trained with the repelling force field. We observed that both the AF and RF groups improved their driving skills. The error reductions of both groups were not statistically different under the current setting. We believe that this pilot study could provide a promising foundation regarding the effects of a robotic wheelchair training algorithm on motor learning. View full abstract»

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  • Force Adaptation in Human Walking With Symmetrically Applied Downward Forces on the Pelvis

    Page(s): 969 - 978
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    The application of external constraints and/or applied forces during movement can lead to reactive as well as adaptive changes in human motion. Previous research has shown adaptation in walking kinematics when external forces were applied to a leg. This work aims to study adaptation in human walking when externally applied forces were present on the pelvis during the swing and stance phases of both legs. A novel tethered pelvic assist device (TPAD) was used to passively apply symmetric downward forces on the human pelvis while walking. During the experiment, eight healthy subjects walked on a treadmill at a constant speed while their kinematics and foot pressure data were recorded. Data analysis revealed that the healthy subjects exhibited both reactive as well as adaptive changes in their gait parameters. The immediate response of the subjects was to increase their hip flexion to clear their foot off the ground as they were unable to lift their pelvis to their usual height in the presence of downward forces. Seven out of eight subjects resisted the downward forces to move their pelvis up. Eventually, they reached a level of downward force that they could sustain over the training session. This adaptation to the downward force was reflected in the heel peak pressure values during the cycles of the gait. On removing the tethers, aftereffects in heel peak pressure values were observed as a result of higher magnitude of pelvic acceleration in vertical direction. In summary, symmetrically applied external forces on the pelvis of healthy subjects resulted in reactive changes in the gait kinematics and adaptive changes in the gait kinetics and the foot interaction forces with the ground. View full abstract»

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  • A Dual-Mode Human Computer Interface Combining Speech and Tongue Motion for People with Severe Disabilities

    Page(s): 979 - 991
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    We are presenting a new wireless and wearable human computer interface called the dual-mode Tongue Drive System (dTDS), which is designed to allow people with severe disabilities to use computers more effectively with increased speed, flexibility, usability, and independence through their tongue motion and speech. The dTDS detects users' tongue motion using a magnetic tracer and an array of magnetic sensors embedded in a compact and ergonomic wireless headset. It also captures the users' voice wirelessly using a small microphone embedded in the same headset. Preliminary evaluation results based on 14 able-bodied subjects and three individuals with high level spinal cord injuries at level C3-C5 indicated that the dTDS headset, combined with a commercially available speech recognition (SR) software, can provide end users with significantly higher performance than either unimodal forms based on the tongue motion or speech alone, particularly in completing tasks that require both pointing and text entry. View full abstract»

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  • Surface Versus Untargeted Intramuscular EMG Based Classification of Simultaneous and Dynamically Changing Movements

    Page(s): 992 - 998
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    The pattern recognition-based myoelectric control scheme is in the process of being implemented in clinical settings, but it has been mainly tested on sequential and steady state data. This paper investigates the ability of pattern recognition to resolve movements that are simultaneous and dynamically changing and compares the use of surface and untargeted intramuscular EMG signals for this purpose. Ten able-bodied subjects participated in the study. Both EMG types were recorded concurrently from the right forearm. The subjects were instructed to track dynamic contraction profiles using single and combined degrees of freedom in three trials. During trials one and two, the amplitude and the frequency of the profile were kept constant (nonmodulated data), and during trial three, the two parameters were modulated (modulated data). The results showed that the performance was up to 93% for nonmodulated tasks, but highly depended on the nature of the data used. Surface and untargeted intramuscular EMG had equal performance for data of similar nature (nonmodulated), but the performance of intramuscular EMG decreased, compared to surface, when tested on modulated data. However, the results of intramuscular recordings obtained in this study are promising for future use of implantable electrodes, because, besides the value added in terms of potential chronic implantation, the performance is theoretically the same as for surface EMG provided that enough information is captured in the recordings. Nevertheless, care should be taken when training the system since data obtained from selective recordings probably need more training data to generalize to new signals. View full abstract»

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  • Accelerometry-Based Gait Analysis and Its Application to Parkinson's Disease Assessment— Part 2 : A New Measure for Quantifying Walking Behavior

    Page(s): 999 - 1005
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    Gait analysis is a valuable tool for obtaining quantitative information on motor deficits in Parkinson's disease (PD). Since the characteristic gait patterns of PD patients may not be fully identified by brief examination in a clinic, long-term, and unobtrusive monitoring of their activities is essential, especially in a nonclinical setting. This paper describes a single accelerometer-based gait analysis system for the assessment of ambulatory gait properties. Acceleration data were recorded continuously for up to 24 h from normal and PD subjects, from which gait peaks were picked out and the relationship between gait cycle and vertical gait acceleration was evaluated. By fitting a model equation to the relationships, a quantitative index was obtained for characterizing the subjects' walking behavior. The averaged index for PD patients with gait disorder was statistically smaller than the value for normal subjects. The proposed method could be used to evaluate daily gait characteristics and thus contribute to a more refined diagnosis and treatment of the disease. View full abstract»

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  • Effect of Early and Late Rehabilitation Onset in a Chronic Rat Model of Ischemic Stroke— Assessment of Motor Cortex Signaling and Gait Functionality Over Time

    Page(s): 1006 - 1015
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    The aim of the present study was to investigate the effects of ischemic stroke and onset of subsequent rehabilitation of gait function in rats. Nine male Sprague-Dawley rats were instrumented with a 16-channel intracortical (IC) electrode array. An ischemic stroke was induced within the hindlimb area of the left motor cortex. The rehabilitation consisted of a repetitive training paradigm over 28 days, initiated on day one (“Early-onset”, 5 rats) and on day seven, (“Late-onset”, 4 rats). Data were obtained from IC microstimulation tests, treadmill walking tests, and beam walking tests. Results revealed an expansion of the hindlimb representation within the motor cortex area and an increased amount of cortical firing rate modulation for the “Early-onset” group but not for the “Late-onset” group. Kinematic data revealed a significant change for both intervention groups. However, this difference was larger for the “Early-onset” group. Results from the beam walking test showed functional performance deficits following stroke which returned to pre-stroke level after the rehabilitative training. The results from the present study indicate the existence of a critical time period following stroke where onset of rehabilitative training may be more effective and related to a higher degree of true recovery. View full abstract»

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  • Open Access

    Page(s): 1016
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  • 2013 Index IEEE Transactions on Neural Systems and Rehabilitation Engineering Vol. 21

    Page(s): 1017 - 1037
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  • IEEE Transactions on Neural Systems and Rehabilitation Engineering information for authors

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  • Table of contents

    Page(s): C4
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IEEE Transactions on Neural Systems and Rehabilitation Engineering focuses on the rehabilitative and neural aspects of biomedical engineering.

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Paul Sajda
Columbia University