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Neural Systems and Rehabilitation Engineering, IEEE Transactions on

Issue 1 • Date Feb. 2011

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  • [Front cover]

    Publication Year: 2011 , Page(s): C1
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  • IEEE Transactions on Neural Systems and Rehabilitation Engineering publication information

    Publication Year: 2011 , Page(s): C2
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  • An SSVEP BCI to Control a Hand Orthosis for Persons With Tetraplegia

    Publication Year: 2011 , Page(s): 1 - 5
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1359 KB) |  | HTML iconHTML  

    Brain-computer interface (BCI) systems allow people to send messages or commands without moving, and hence can provide an alternative communication and control channel for people with limited motor function. In this study, we demonstrate a BCI system for orthosis control. Our BCI was asynchronous, meaning that subjects could move the orthosis whenever they wanted, instead of pacing themselves to external cues. Seven subjects each performed two tasks with a BCI that relied on steady state visual evoked potentials (SSVEPs). Although none of the subjects had any training, six subjects showed good control with a positive predictive value (PPV) higher than 60%. The overall PPV for all subjects reached 78% ±10%. However, the false positive rate was high, and some subjects dislike the flickering lights required in SSVEP BCIs. In follow-up work, we hope to reduce both the false positive rate and the annoyance produced by flickering lights by hybridizing this BCI with a “brain switch,” which could allow people to turn the SSVEP system on or off using a second type of brain activity when they do not wish to control the orthosis. We also hope to validate this approach with people with tetraplegia. View full abstract»

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  • A Dictionary-Driven P300 Speller With a Modified Interface

    Publication Year: 2011 , Page(s): 6 - 14
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (691 KB) |  | HTML iconHTML  

    P300 spellers are mainly composed of an interface, by which alphanumerical characters are presented to users, and a classification system, which identifies the target character by using acquired EEG data. In this study, we proposed modifications both to the interface and to the classification system, in order to reduce the number of required stimulus repetitions and consequently boost the information transfer rate. We initially incorporated a custom-built dictionary into the classification system, and conducted a study on 14 healthy subjects who copy-spelled 15 four letter words. Incorporating the dictionary, the mean accuracy at five trials increased from 72.86% to 95.71%. To further increase the system performance, we first validated the hypothesis that for a conventional P300 system, most target-error pairs lie on the same row or column. Then based on the validated hypothesis, we adjusted letter positions on the well-known from A to Z interface. The same subjects spelled the same 15 words using the modified interface as well, and the mean information transfer rate at two trials reached 55.32 bits/min. View full abstract»

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  • Closed-Loop Control of Deep Brain Stimulation: A Simulation Study

    Publication Year: 2011 , Page(s): 15 - 24
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (413 KB) |  | HTML iconHTML  

    Deep brain stimulation (DBS) is an effective therapy to treat movement disorders including essential tremor, dystonia, and Parkinson's disease. Despite over a decade of clinical experience the mechanisms of DBS are still unclear, and this lack of understanding makes the selection of stimulation parameters quite challenging. The objective of this work was to develop a closed-loop control system that automatically adjusted the stimulation amplitude to reduce oscillatory neuronal activity, based on feedback of electrical signals recorded from the brain using the same electrode as implanted for stimulation. We simulated a population of 100 intrinsically active model neurons in the Vim thalamus, and the local field potentials (LFPs) generated by the population were used as the feedback (control) variable for closed loop control of DBS amplitude. Based on the correlation between the spectral content of the thalamic activity and tremor (Hua , 1998), (Lenz , 1988), we implemented an adaptive minimum variance controller to regulate the power spectrum of the simulated LFPs and restore the LFP power spectrum present under tremor conditions to a reference profile derived under tremor free conditions. The controller was based on a recursively identified autoregressive model (ARX) of the relationship between stimulation input and LFP output, and showed excellent performances in tracking the reference spectral features through selective changes in the theta (2-7 Hz), alpha (7-13 Hz), and beta (13-35 Hz) frequency ranges. Such changes reflected modifications in the firing patterns of the model neuronal population, and, differently from open-loop DBS, replaced the tremor-related pathological patterns with patterns similar to those simulated in tremor-free conditions. The closed-loop controller generated a LFP spectrum that approximated more closely the spectrum present in the tremor-free condition than did open loop fixed intensity stimulation and adapted to match the spectrum afte- - r a change in the neuronal oscillation frequency. This computational study suggests the feasibility of closed-loop control of DBS amplitude to regulate the spectrum of the local field potentials and thereby normalize the aberrant pattern of neuronal activity present in tremor. View full abstract»

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  • Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems

    Publication Year: 2011 , Page(s): 25 - 34
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (826 KB) |  | HTML iconHTML  

    The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5 ± 0.5 s (mean ±s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25±3 single units by a factor of 7.0±0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems. View full abstract»

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  • Wireless Transmission of Neural Signals Using Entropy and Mutual Information Compression

    Publication Year: 2011 , Page(s): 35 - 44
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (995 KB) |  | HTML iconHTML  

    Two of the most critical tasks when designing a portable wireless neural recording system are to limit power consumption and to efficiently use the limited bandwidth. It is known that for most wireless devices the majority of power is consumed by the wireless transmitter and it often represents the bottleneck of the overall design. This paper compares two compression techniques that take advantage of the sparseness of the neural spikes in neural recordings using an information theoretic formalism to enhance the well-established vector quantization (VQ) algorithm. The two discriminative VQ algorithms are applied to neuronal recordings proving their ability to accurately reconstruct action potential (AP) regions of the neuronal signal while compressing background activity without using thresholds. The two operational modes presented offer distinct characteristics to lossy compression. The first approach requires no preprocessing or prior knowledge of the signal while the second requires a training set of spikes to obtain AP templates. The compression algorithms are implemented on an on-board digital signal processor (DSP) and results show that power consumption is decreased while the bandwidth is more efficiently utilized. The compression algorithms have been tested in real time on a hardware platform (PICO DSP ) enhanced with the DSP which runs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range from 70:1 and 40:1 depending on the signal to noise ratio (SNR) of the input signal. The spike sorting accuracy in the reconstructed data is 95% compatible to the original neural data. View full abstract»

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  • Design and Testing of an Advanced Implantable Neuroprosthesis With Myoelectric Control

    Publication Year: 2011 , Page(s): 45 - 53
    Cited by:  Papers (4)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2154 KB) |  | HTML iconHTML  

    An implantable stimulator-telemeter (IST-12) was developed for applications in neuroprosthetic restoration of limb function in paralyzed individuals. The IST-12 provides 12 stimulation channels and two myoelectric signal (MES) channels. The MES circuitry includes a two-channel multiplexer, preamplifier, variable gain amplifier/bandpass filter, full-wave rectifier, and bin integrator. Power and control signals are transmitted from an external control unit to the IST-12 through an inductive link. Recorded MES signals are telemetered back to the external control unit through the same inductive link. Following bench testing, one device was implanted chronically in a dog for 15 months and evaluated. Conditions were identified in which MES could be recorded with minimal stimulus artifact. The ability to record MES in the presence of stimulation was verified, confirming the potential of the IST-12 to be used as a myoelectric controlled neuroprosthesis. View full abstract»

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  • Rigorous a Posteriori Assessment of Accuracy in EMG Decomposition

    Publication Year: 2011 , Page(s): 54 - 63
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (438 KB) |  | HTML iconHTML  

    If electromyography (EMG) decomposition is to be a useful tool for scientific investigation, it is essential to know that the results are accurate. Because of background noise, waveform variability, motor-unit action potential (MUAP) indistinguishability, and perplexing superpositions, accuracy assessment is not straightforward. This paper presents a rigorous statistical method for assessing decomposition accuracy based only on evidence from the signal itself. The method uses statistical decision theory in a Bayesian framework to integrate all the shape- and firing-time-related information in the signal to compute an objective a posteriori measure of confidence in the accuracy of each discharge in the decomposition. The assessment is based on the estimated statistical properties of the MUAPs and noise and takes into account the relative likelihood of every other possible decomposition. The method was tested on 3 pairs of real EMG signals containing 4-7 active MUAP trains per signal that had been decomposed by a human expert. It rated 97% of the identified MUAP discharges as accurate to within ± 0.5 ms with a confidence level of 99%, and detected six decomposition errors. Cross-checking between signal pairs verified all but two of these assertions. These results demonstrate that the approach is reliable and practical for real EMG signals. View full abstract»

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  • Optimization of Spring-Loaded Crutches via Boundary Value Problem

    Publication Year: 2011 , Page(s): 64 - 70
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (594 KB) |  | HTML iconHTML  

    The objective of the work is to optimize the design of spring-loaded crutches by choosing appropriate spring stiffness based on their dynamic characteristics. It was shown in the literature that ambulation with spring-loaded crutches reduces the initial impulse yielded by ambulation with standard crutches and provides a propulsion mechanism. This research not only provides a genre of the spring-loaded crutches via compliance, but also proposes an approach to optimize the stiffness of the helical spring through studying the dynamics of crutch stance. The method is developed using a boundary value problem and its solution method and is studied numerically. Experiments were carried out on four subjects in a biomechanics laboratory. It suggests that the optimized spring-loaded crutches guarantee the propulsion mechanism at the right time and right position during dynamical ambulation. View full abstract»

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  • Upslope Walking With a Powered Knee and Ankle Prosthesis: Initial Results With an Amputee Subject

    Publication Year: 2011 , Page(s): 71 - 78
    Cited by:  Papers (27)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (947 KB) |  | HTML iconHTML  

    This paper extends a previously developed level- ground walking control methodology to enable an above knee amputee to walk up slopes using a powered knee and ankle prosthesis. Experimental results corresponding to walking on level ground and two different slope angles (5° and 10°) with the powered prosthesis using the control method are compared to walking under the same conditions with a passive prosthesis. The data indicate that the powered prosthesis with the upslope walking controller is able to reproduce several kinematic characteristics of healthy upslope walking that the passive prosthesis does not (such as knee flexion after heel strike and a powered ankle plantarflexion during push-off). Finally, results are shown that demonstrate the ability of the prosthesis to generate a slope estimate, which is in turn utilized to adapt the underlying control parameters to the corresponding slope. View full abstract»

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  • Muscle Plasticity in Rat Following Spinal Transection and Chronic Intraspinal Microstimulation

    Publication Year: 2011 , Page(s): 79 - 83
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1300 KB) |  | HTML iconHTML  

    Intraspinal microstimulation (ISMS) employs electrical stimulation of the ventral grey matter to reactivate paralyzed skeletal muscle. This work evaluated the transformations in the quadriceps muscle that occurred following complete transection and chronic stimulation with ISMS or a standard nerve cuff (NCS). Stimulation was applied for 30 days, 4 h/day. Both methods induced significant increases in time-to-peak tension (ISMS 35%, NCS 25%) and half rise-time (ISMS 39%, NCS 25%) compared to intact controls (IC). Corresponding increases in type-IIA myosin heavy chain (MHC) and decreases in type-IID MHC were noted compared to IC. These results were unexpected because ISMS recruits motor units in a near-normal physiological order while NCS recruits motor units in a reversed order. Spinal cord transection and 30 days of stimulation did not alter either recruitment profile. The slope of the force recruitment curves obtained through ISMS following transection and 30 days of stimulation was similar to that obtained in intact animals, and 3.4-fold shallower than that obtained through NCS. The transformations observed in the current work are best explained by the near maximal level of motor unit recruitment, the total daily time of activity and the tonic nature of the stimulation paradigm. View full abstract»

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  • Effects of Biphasic Current Pulse Frequency, Amplitude, Duration, and Interphase Gap on Eye Movement Responses to Prosthetic Electrical Stimulation of the Vestibular Nerve

    Publication Year: 2011 , Page(s): 84 - 94
    Cited by:  Papers (16)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1169 KB) |  | HTML iconHTML  

    An implantable prosthesis that stimulates vestibular nerve branches to restore sensation of head rotation and vision-stabilizing reflexes could benefit individuals disabled by bilateral loss of vestibular (inner ear balance) function. We developed a prosthesis that partly restores normal function in animals by delivering pulse frequency modulated (PFM) biphasic current pulses via electrodes implanted in semicircular canals. Because the optimal stimulus encoding strategy is not yet known, we investigated effects of varying biphasic current pulse frequency, amplitude, duration, and interphase gap on vestibulo-ocular reflex (VOR) eye movements in chinchillas. Increasing pulse frequency increased response amplitude while maintaining a relatively constant axis of rotation. Increasing pulse amplitude (range 0-325 μA) also increased response amplitude but spuriously shifted eye movement axis, probably due to current spread beyond the target nerve. Shorter pulse durations (range 28-340 μs) required less charge to elicit a given response amplitude and caused less axis shift than longer durations. Varying interphase gap (range 25-175 μs) had no significant effect. While specific values reported herein depend on microanatomy and electrode location in each case, we conclude that PFM with short duration biphasic pulses should form the foundation for further optimization of stimulus encoding strategies for vestibular prostheses intended to restore sensation of head rotation. View full abstract»

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  • A Training System of Orientation and Mobility for Blind People Using Acoustic Virtual Reality

    Publication Year: 2011 , Page(s): 95 - 104
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2112 KB) |  | HTML iconHTML  

    A new auditory orientation training system was developed for blind people using acoustic virtual reality (VR) based on a head-related transfer function (HRTF) simulation. The present training system can reproduce a virtual training environment for orientation and mobility (O&M) instruction, and the trainee can walk through the virtual training environment safely by listening to sounds such as vehicles, stores, ambient noise, etc., three-dimensionally through headphones. The system can reproduce not only sound sources but also sound reflection and insulation, so that the trainee can learn both sound location and obstacle perception skills. The virtual training environment is described in extensible markup language (XML), and the O&M instructor can edit it easily according to the training curriculum. Evaluation experiments were conducted to test the efficiency of some features of the system. Thirty subjects who had not acquired O&M skills attended the experiments. The subjects were separated into three groups: a no-training group, a virtual-training group using the present system, and a real-training group in real environments. The results suggested that virtual-training can reduce “veering” more than real-training and also can reduce stress as much as real training. The subjective technical and anxiety scores also improved. View full abstract»

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  • Robust Neuro-Sliding Mode Multivariable Control Strategy for Powered Wheelchairs

    Publication Year: 2011 , Page(s): 105 - 111
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (673 KB) |  | HTML iconHTML  

    This paper proposes an advanced robust multivariable control strategy for a powered wheelchair system. The new control strategy is based on a combination of the systematic triangularization technique and the robust neuro-sliding mode control approach. This strategy effectively copes with parameter uncertainties and external disturbances in real-time in order to achieve robustness and optimal performance of a multivariable system. This novel strategy reduces coupling effects on a multivariable system, eliminates chattering phenomena, and avoids the plant Jacobian calculation problem. Furthermore, the strategy can also achieve fast and global convergence using less computation. The effectiveness of the new multivariable control strategy is verified in real-time implementation on a powered wheelchair system. The obtained results confirm that robustness and desired performance of the overall system are guaranteed, even under parameter uncertainty and external disturbance effects. View full abstract»

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    Publication Year: 2011 , Page(s): 112
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  • IEEE Transactions on Neural Systems and Rehabilitation Engineering information for authors

    Publication Year: 2011 , Page(s): C3
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  • Table of contents

    Publication Year: 2011 , 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