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Neural Systems and Rehabilitation Engineering, IEEE Transactions on

Issue 4 • Date July 2013

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  • Front cover

    Publication Year: 2013 , Page(s): C1
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  • IEEE Transactions on Neural Systems and Rehabilitation Engineering publication information

    Publication Year: 2013 , Page(s): C2
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  • Table of contents

    Publication Year: 2013 , Page(s): 521 - 522
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  • Guest Editorial - Neural engineering: An exciting, multi-disciplinary, and revolutionary research field

    Publication Year: 2013 , Page(s): 523
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  • Evaluation of a MEMS-Based Dual Metal-Layer Thin-Film Microelectrode Array for Suprachoroidal Electrical Stimulation

    Publication Year: 2013 , Page(s): 524 - 531
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1563 KB) |  | HTML iconHTML  

    A double metal-layer thin-film platinum microelectrode array was fabricated for implantation between sclera and choroid based on MEMS processing techniques and photosensitive polyimide material. The array was composed of 60 stimulating sites (6 × 10) and four selectable returning electrodes. The diameter of each stimulating electrode was 350 μm with a center-to-center spacing of 750 μm. The transient voltage responses of the electrode to current pulse stimulation indicated a charge-injection capacity greater than 52.1 μC/cm2. Acute in vivo animal experiments showed that the implicit time of electrically evoked potentials (EEPs) was 17.09 ± 1.45 ms at a threshold current of 25.55 ± 5.43 μA for a full-row of simultaneously stimulated electrodes (i.e. current applied simultaneously to each of the 10 electrodes). Individual electrode stimulation threshold was 48.57 ± 6.90 μA. The corresponding threshold charge densities were 13.28 ± 2.82 μC/cm2 and 25.24 ± 3.59 μC/cm2, respectively. The spatial spread of the maximally recorded P1 response in the EEPs indicated a correspondence between the retinal stimulation site and the focal response location in the cortex. This method of array fabrication is suitable for acute suprachoroidal stimulation, and has a potential use for the fabrication of a visual prosthesis. View full abstract»

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  • Adaptive Inverse Control of Neural Spatiotemporal Spike Patterns With a Reproducing Kernel Hilbert Space (RKHS) Framework

    Publication Year: 2013 , Page(s): 532 - 543
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2876 KB) |  | HTML iconHTML  

    The precise control of spiking in a population of neurons via applied electrical stimulation is a challenge due to the sparseness of spiking responses and neural system plasticity. We pose neural stimulation as a system control problem where the system input is a multidimensional time-varying signal representing the stimulation, and the output is a set of spike trains; the goal is to drive the output such that the elicited population spiking activity is as close as possible to some desired activity, where closeness is defined by a cost function. If the neural system can be described by a time-invariant (homogeneous) model, then offline procedures can be used to derive the control procedure; however, for arbitrary neural systems this is not tractable. Furthermore, standard control methodologies are not suited to directly operate on spike trains that represent both the target and elicited system response. In this paper, we propose a multiple-input multiple-output (MIMO) adaptive inverse control scheme that operates on spike trains in a reproducing kernel Hilbert space (RKHS). The control scheme uses an inverse controller to approximate the inverse of the neural circuit. The proposed control system takes advantage of the precise timing of the neural events by using a Schoenberg kernel defined directly in the space of spike trains. The Schoenberg kernel maps the spike train to an RKHS and allows linear algorithm to control the nonlinear neural system without the danger of converging to local minima. During operation, the adaptation of the controller minimizes a difference defined in the spike train RKHS between the system and the target response and keeps the inverse controller close to the inverse of the current neural circuit, which enables adapting to neural perturbations. The results on a realistic synthetic neural circuit show that the inverse controller based on the Schoenberg kernel outperforms the decoding accuracy of other models based on the conventional rate- representation of neural signal (i.e., spikernel and generalized linear model). Moreover, after a significant perturbation of the neuron circuit, the control scheme can successfully drive the elicited responses close to the original target responses. View full abstract»

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  • A Largely Deformable Surface Type Neural Electrode Array Based on PDMS

    Publication Year: 2013 , Page(s): 544 - 553
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1724 KB) |  | HTML iconHTML  

    This paper describes a largely deformable surface type neural electrode array based on polydimethylsiloxane (PDMS) for cortical use. Noncracked and reliable metal patterns were fabricated successfully on PDMS substrate by employing an intermediate parylene layer. The mechanical and electrical stability of the fabricated electrode arrays was demonstrated by repeatable bending test using a custom-designed bending test module. Also the adhesion of the electrode structure consisting of PDMS, parylene and metal layers was proven by ASTM tape test. The electrode impedance was measured in phosphate buffered saline (PBS) solution at 37°C over three months and analyzed using equivalent circuit models. Based on these results, it is concluded that the suggested electrode array provides a largely deformable structure with mechanical integrity and electrical stability, which can withstand mechanical stresses when inserted through a small trephination hole in the skull and expanded in the small room between the cortex and the skull without damage to the electrode array. View full abstract»

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  • Regenerative Scaffold Electrodes for Peripheral Nerve Interfacing

    Publication Year: 2013 , Page(s): 554 - 566
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1849 KB) |  | HTML iconHTML  

    Advances in neural interfacing technology are required to enable natural, thought-driven control of a prosthetic limb. Here, we describe a regenerative electrode design in which a polymer-based thin-film electrode array is integrated within a thin-film sheet of aligned nanofibers, such that axons regenerating from a transected peripheral nerve are topographically guided across the electrode recording sites. Cultures of dorsal root ganglia were used to explore design parameters leading to cellular migration and neurite extension across the nanofiber/electrode array boundary. Regenerative scaffold electrodes (RSEs) were subsequently fabricated and implanted across rat tibial nerve gaps to evaluate device recording capabilities and influence on nerve regeneration. In 20 of these animals, regeneration was compared between a conventional nerve gap model and an amputation model. Characteristic shaping of regenerated nerve morphology around the embedded electrode array was observed in both groups, and regenerated axon profile counts were similar at the eight week end point. Implanted RSEs recorded evoked neural activity in all of these cases, and also in separate implantations lasting up to five months. These results demonstrate that nanofiber-based topographic cues within a regenerative electrode can influence nerve regeneration, to the potential benefit of a peripheral nerve interface suitable for limb amputees. View full abstract»

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  • Constrained Blind Source Extraction of Readiness Potentials From EEG

    Publication Year: 2013 , Page(s): 567 - 575
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2045 KB) |  | HTML iconHTML  

    One of the changes seen in electroencephalography (EEG) data preceding human voluntary movement is a cortical potential called readiness potential (RP). Detection of this potential can benefit researchers in clinical neurosciences for rehabilitation of malfunctioning brain and those working on brain-computer interfacing to develop a suitable mechanism to detect the intention of movement. Here, a constrained blind source extraction (CBSE) is attempted for detection of RP. A suitable constraint is defined and applied. The results are also compared with those of the traditional blind source separation in terms of true positive rate, false positive rate, and computation time. The results show that the CBSE approach in overall has superior performance. View full abstract»

    Open Access
  • Exploiting the Self-Similarity in ERP Images by Nonlocal Means for Single-Trial Denoising

    Publication Year: 2013 , Page(s): 576 - 583
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1285 KB) |  | HTML iconHTML  

    Event related potentials (ERPs) represent a noninvasive and widely available means to analyze neural correlates of sensory and cognitive processing. Recent developments in neural and cognitive engineering proposed completely new application fields of this well-established measurement technique when using an advanced single-trial processing. We have recently shown that 2-D diffusion filtering methods from image processing can be used for the denoising of ERP single-trials in matrix representations, also called ERP images. In contrast to conventional 1-D transient ERP denoising techniques, the 2-D restoration of ERP images allows for an integration of regularities over multiple stimulations into the denoising process. Advanced anisotropic image restoration methods may require directional information for the ERP denoising process. This is especially true if there is a lack of a priori knowledge about possible traces in ERP images. However due to the use of event related experimental paradigms, ERP images are characterized by a high degree of self-similarity over the individual trials. In this paper, we propose the simple and easy to apply nonlocal means method for ERP image denoising in order to exploit this self-similarity rather than focusing on the edge-based extraction of directional information. Using measured and simulated ERP data, we compare our method to conventional approaches in ERP denoising. It is concluded that the self-similarity in ERP images can be exploited for single-trial ERP denoising by the proposed approach. This method might be promising for a variety of evoked and event-related potential applications, including nonstationary paradigms such as changing exogeneous stimulus characteristics or endogenous states during the experiment. As presented, the proposed approach is for the a posteriori denoising of single-trial sequences. View full abstract»

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  • Simulation of Cortico-Basal Ganglia Oscillations and Their Suppression by Closed Loop Deep Brain Stimulation

    Publication Year: 2013 , Page(s): 584 - 594
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1151 KB) |  | HTML iconHTML  

    A new model of deep brain stimulation (DBS) is presented that integrates volume conduction effects with a neural model of pathological beta-band oscillations in the cortico-basal ganglia network. The model is used to test the clinical hypothesis that closed-loop control of the amplitude of DBS may be possible, based on the average rectified value of beta-band oscillations in the local field potential. Simulation of closed-loop high-frequency DBS was shown to yield energy savings, with the magnitude of the energy saved dependent on the strength of coupling between the subthalamic nucleus and the remainder of the cortico-basal ganglia network. When closed-loop DBS was applied to a strongly coupled cortico-basal ganglia network, the stimulation energy delivered over a 480 s period was reduced by up to 42%. Greater energy reductions were observed for weakly coupled networks, as the stimulation amplitude reduced to zero once the initial desynchronization had occurred. The results provide support for the application of closed-loop high-frequency DBS based on electrophysiological biomarkers. View full abstract»

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  • Functional Alteration of the DMN by Learned Regulation of the PCC Using Real-Time fMRI

    Publication Year: 2013 , Page(s): 595 - 606
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1353 KB) |  | HTML iconHTML  

    The default mode network (DMN) is a network of brain regions that are active during rest and suppressed during a cognitively demanding task. Previous studies have shown that the DMN can be altered by development, aging, disorder, cognitive tasks and offline training. However, it's unclear whether activity in the DMN can be altered by real-time training. Recently, real-time functional magnetic resonance imaging (rtfMRI), as a novel neurofeedback technique, has been applied to train subjects to voluntarily control activities in specific brain regions. In the current study, it was found that by using rtfMRI to guide training, subjects were able to learn to decrease activity in the posterior cingulate cortex (PCC), which is a “key hub” in the DMN, using motor imagery strategy. After the real-time training, activity in the medial prefrontral cortex/ anterior cingulate cortex (MPFC/ACC) of the resting state DMN was decreased. By contrast, the control group without neurofeedback produced increased activity in the MPFC/ACC of the DMN during the post-training resting state. These findings suggest that this rtfMRI technique has great potential to be used in the regulation of the DMN and may be a novel approach for studying functional plasticity of the cortex. View full abstract»

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  • Inter-Trial Analysis of Post-Movement Beta Activities in EEG Signals Using Multivariate Empirical Mode Decomposition

    Publication Year: 2013 , Page(s): 607 - 615
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1858 KB) |  | HTML iconHTML  

    Event-related desynchronization/synchronization (ERD/ERS) is a technique to quantify subject's nonphase-locked neural activities underlying specific frequency bands, reactive to external/internal stimulus. However, conventional ERD/ERS studies usually utilize fixed frequency band determined from one or few channels to filter whole-head EEG/MEG data, which may inevitably include task-unrelated signals and result in underestimation of reactive oscillatory activities in multichannel studies. In this study, we adopted multivariate empirical mode decomposition (MEMD) to extract beta-related oscillatory activities in performing self-paced right and left index-finger lifting tasks. The MEMD extracts common modes from all channels in same-index intrinsic mode functions (IMFs) which allows the temporal-frequency features among different channels can be compared in each subband. The beta-band oscillatory activities were further bandpass filtered within trial-specific beta bands determined from sensorimotor-related channels (C3 and C4), and then rectified using amplitude modulation method to detect trial-by-trial beta rebound (BR) values in ERS time courses. The validity of the MEMD approach in BR values extraction has been demonstrated in multichannel EEG study which showed larger BR values than conventional ERS technique. The MEMD-based method enables the trial-by-trial extraction of sensorimotor oscillatory activities which might allow the exploration of subtle brain dynamics in future studies. View full abstract»

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  • Validation of a Selective Ensemble-Based Classification Scheme for Myoelectric Control Using a Three-Dimensional Fitts' Law Test

    Publication Year: 2013 , Page(s): 616 - 623
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1353 KB) |  | HTML iconHTML  

    When controlling a powered upper limb prosthesis it is important not only to know how to move the device, but also when not to move. A novel approach to pattern recognition control, using a selective multiclass one-versus-one classification scheme has been shown to be capable of rejecting unintended motions. This method was shown to outperform other popular classification schemes when presented with muscle contractions that did not correspond to desired actions. In this work, a 3-D Fitts' Law test is proposed as a suitable alternative to using virtual limb environments for evaluating real-time myoelectric control performance. The test is used to compare the selective approach to a state-of-the-art linear discriminant analysis classification based scheme. The framework is shown to obey Fitts' Law for both control schemes, producing linear regression fittings with high coefficients of determination (R2 > 0.936) . Additional performance metrics focused on quality of control are discussed and incorporated in the evaluation. Using this framework the selective classification based scheme is shown to produce significantly higher efficiency and completion rates, and significantly lower overshoot and stopping distances, with no significant difference in throughput. View full abstract»

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  • Quantitative Description of the Lie-to-Sit-to-Stand-to-Walk Transfer by a Single Body-Fixed Sensor

    Publication Year: 2013 , Page(s): 624 - 633
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1735 KB) |  | HTML iconHTML  

    Sufficient capacity and quality of performance of complex movement patterns during daily activity, such as standing up from a bed, is a prerequisite for independent living and also may be an indicator of fall risk. Until now, the transfer from lying-to-sit-to-stand-to-walk (LSSW) was investigated by functional testing, subjective rating or for activity classification of subtasks. The aim of this study was to use a single body-fixed inertial sensor to describe the complex movement of the LSSW transfer. Fifteen older patients of a geriatric rehabilitation clinic (median age 81 years) and ten young, healthy persons (median age 37 years) were instructed to stand up from bed in a continuous movement and to start walking. Data acquisition was performed using an inertial measurement unit worn on the lower back. Parameters extracted from the sensor outputs were able to correctly classify the subjects into a correct group with sensitivity and specificity between 90% and 100%. ICCs of the descriptive parameters ranged between 0.85 and 0.95 in the cohort of older patients. The different strategies adopted to transfer from lying to standing up were estimated through an extended Kalman filter. The results obtained in this study suggest the usability of the instrumented LSSW test in clinical settings. View full abstract»

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  • Evaluation of Feedforward and Feedback Contributions to Hand Stiffness and Variability in Multijoint Arm Control

    Publication Year: 2013 , Page(s): 634 - 647
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2117 KB) |  | HTML iconHTML  

    The purpose of this study is to validate a neuromechanical model of the virtual arm (VA) by comparing emerging behaviors of the model to those of experimental observations. Hand stiffness of the VA model was obtained by either theoretical computation or simulated perturbations. Variability in hand position of the VA was generated by adding signal dependent noise (SDN) to the motoneuron pools of muscles. Reflex circuits of Ia, Ib and Renshaw cells were included to regulate the motoneuron pool outputs. Evaluation of hand stiffness and variability was conducted in simulations with and without afferent feedback under different patterns of muscle activations during postural maintenance. The simulated hand stiffness and variability ellipses captured the experimentally observed features in shape, magnitude and orientation. Steady state afferent feedback contributed significantly to the increase in hand stiffness by 35.75 ± 16.99% in area, 18.37 ± 7.80% and 16.15 ± 7.15% in major and minor axes; and to the reduction of hand variability by 49.41 ± 21.19% in area, 36.89 ± 12.78% and 18.87 ± 23.32% in major and minor axes. The VA model reproduced the neuromechanical behaviors that were consistent with experimental data, and it could be a useful tool for study of neural control of posture and movement, as well as for application to rehabilitation. View full abstract»

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  • Multi-Pad Electrode for Effective Grasping: Design

    Publication Year: 2013 , Page(s): 648 - 654
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (920 KB) |  | HTML iconHTML  

    We designed a new surface multi-pad electrode for the electrical stimulation of the forearm that is effective in controlling functional grasp in hemiplegic patients. The electrode shape and size were designed on the basis of the surface stimulation map of the forearm, determined from measurements in seven hemiplegic patients who had limited or absent voluntary movements of the fingers, thumb and wrist. The stimulation map for each patient was assessed with a conventional set of single pad Pals Platinum electrodes. Since the sites for the stimulation varied greatly between patients, the end result was a rather large multi-pad electrode. Modulating multi-pad electrode size, shape, position and individual pad stimulation parameters allows us to accommodate the diversity of the neural tissues in patients that need to be activated for functional grasp. This also allows asynchronous activation of different portions of the muscle and dynamic adaptation of the stimulation sites to appropriate underlying tissues during functional use. The validity of the determined stimulation map was tested in the same group of hemiplegic patients. The selected set of active pads resulted in fully functional and reproducible palmar and lateral grasps similar to healthy-like grasps. View full abstract»

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  • Intuitive Tactile Zooming for Graphics Accessed by Individuals Who are Blind and Visually Impaired

    Publication Year: 2013 , Page(s): 655 - 663
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1366 KB) |  | HTML iconHTML  

    One possibility of providing access to visual graphics for those who are visually impaired is to present them tactually: unfortunately, details easily available to vision need to be magnified to be accessible through touch. For this, we propose an “intuitive” zooming algorithm to solve potential problems with directly applying visual zooming techniques to haptic displays that sense the current location of a user on a virtual diagram with a position sensor and, then, provide the appropriate local information either through force or tactile feedback. Our technique works by determining and then traversing the levels of an object tree hierarchy of a diagram. In this manner, the zoom steps adjust to the content to be viewed, avoid clipping and do not zoom when no object is present. The algorithm was tested using a small, “mouse-like” display with tactile feedback on pictures representing houses in a community and boats on a lake. We asked the users to answer questions related to details in the pictures. Comparing our technique to linear and logarithmic step zooming, we found a significant increase in the correctness of the responses (odds ratios of 2.64:1 and 2.31:1, respectively) and usability (differences of 36% and 19%, respectively) using our “intuitive” zooming technique. View full abstract»

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  • Quantification of Motor Impairment in Parkinson's Disease Using an Instrumented Timed Up and Go Test

    Publication Year: 2013 , Page(s): 664 - 673
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2272 KB) |  | HTML iconHTML  

    The Timed Up and Go (TUG) test is a clinical test to assess mobility in Parkinson's disease (PD). It consists of rising from a chair, walking, turning, and sitting. Its total duration is the traditional clinical outcome. In this study an instrumented TUG (iTUG) was used to supplement the quantitative information about the TUG performance of PD subjects: a single accelerometer, worn at the lower back, was used to record the acceleration signals during the test and acceleration-derived measures were extracted from the recorded signals. The aim was to select reliable measures to identify and quantify the differences between the motor patterns of healthy and PD subjects; in order to do so, besides comparing each measure individually to find significant group differences, feature selection and classification were used to identify the distinctive motor pattern of PD subjects. A subset of three features (two from Turning, one from the Sit-to-Walk component), combined with an easily-interpretable classifier (Linear Discriminant Analysis), was found to have the best accuracy in discriminating between healthy and early-mild PD subjects. These results suggest that the proposed iTUG can characterize PD motor impairment and, hence, may be used for evaluation, and, prospectively, follow-up, and monitoring of disease progression. View full abstract»

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  • Real-Time Evaluation of a Noninvasive Neuroprosthetic Interface for Control of Reach

    Publication Year: 2013 , Page(s): 674 - 683
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1300 KB) |  | HTML iconHTML  

    Injuries of the cervical spinal cord can interrupt the neural pathways controlling the muscles of the arm, resulting in complete or partial paralysis. For individuals unable to reach due to high-level injuries, neuroprostheses can restore some of the lost function. Natural, multidimensional control of neuroprosthetic devices for reaching remains a challenge. Electromyograms (EMGs) from muscles that remain under voluntary control can be used to communicate intended reach trajectories, but when the number of available muscles is limited control can be difficult and unintuitive. We combined shoulder EMGs with target estimates obtained from gaze. Natural gaze data were integrated with EMG during closed-loop robotic control of the arm, using a probabilistic mixture model. We tested the approach with two different sets of EMGs, as might be available to subjects with C4and C5-level spinal cord injuries. Incorporating gaze greatly improved control of reaching, particularly when there were few EMG signals. We found that subjects naturally adapted their eye-movement precision as we varied the set of available EMGs, attaining accurate performance in both tested conditions. The system performs a near-optimal combination of both physiological signals, making control more intuitive and allowing a natural trajectory that reduces the burden on the user. View full abstract»

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  • Improved Perception of Music With a Harmonic Based Algorithm for Cochlear Implants

    Publication Year: 2013 , Page(s): 684 - 694
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2000 KB) |  | HTML iconHTML  

    The lack of fine structure information in conventional cochlear implant (CI) encoding strategies presumably contributes to the generally poor music perception with CIs. To improve CI users' music perception, a harmonic-single-sideband-encoder (HSSE) strategy was developed [1]-[3], which explicitly tracks the harmonics of a single musical source and transforms them into modulators conveying both amplitude and temporal fine structure cues to electrodes. To investigate its effectiveness, vocoder simulations of HSSE and the conventional continuous-interleaved-sampling (CIS) strategy were implemented. Using these vocoders, live normal-hearing subjects' melody and timbre recognition performance were evaluated: a significant benefit of HSSE to both melody (p <; 0.002) and timbre (p <; 0.026) recognition was found. Additionally, HSSE was acutely tested in eight CI subjects. On timbre recognition, a significant advantage of HSSE over the subjects' clinical strategy was demonstrated: the largest improvement was 35% and the mean 17% (p <; 0.013). On melody recognition, two subjects showed 20% improvement with HSSE; however, the mean improvement of 7% across subjects was not significant (p > 0.090). To quantify the temporal cues delivered to the auditory nerve, the neural spike patterns evoked by HSSE and CIS for one melody stimulus were simulated using an auditory nerve model. Quantitative analysis demonstrated that HSSE can convey temporal pitch cues better than CIS. The results suggest that HSSE is a promising strategy to enhance music perception with CIs. View full abstract»

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  • Open Access

    Publication Year: 2013 , Page(s): 695
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  • IEEE Xplore Digital Library

    Publication Year: 2013 , Page(s): 696
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  • IEEE Transactions on Neural Systems and Rehabilitation Engineering information for authors

    Publication Year: 2013 , Page(s): C3
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  • [Blank page - back cover]

    Publication Year: 2013 , Page(s): C4
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Aims & Scope

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

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Meet Our Editors

Editor-in-Chief
Paul Sajda
Columbia University