1,874 results match your criteria IEEE Transactions on Neural Systems and Rehabilitation Engineering [Journal]


A Single-Channel EEG-Based Approach to Detect Mild Cognitive Impairment via Speech-Evoked Brain Responses.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 18. Epub 2019 Apr 18.

Mild Cognitive Impairment (MCI) is the preliminary stage of dementia, which may lead to Alzheimer's disease (AD) in the elderly people. Therefore, early detection of MCI has the potential to minimize the risk of AD by ensuring the proper mental health care before it is too late. In this study, we demonstrate a single-channel EEG based MCI detection method, which is cost-effective and portable, and thus suitable for regular home-based patient monitoring. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911970DOI Listing
April 2019
11 Reads

Precise tubular braid structures of ultrafine microwires as neural probes: significantly reduced chronic immune response and greater local neural survival in rat cortex.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 18. Epub 2019 Apr 18.

Braided multi-electrode probes (BMEPs) for neural interfaces comprise ultrafine microwire bundles interwoven into tubular braids. BMEPs provide highly flexible probes and tethers, and an open lattice structure with up to 24 recording/stimulating channels in precise geometries, currently all within a 150~200 μm diameter footprint. This paper compares the long-term tissue effects of BMEPs (12 × 9. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911912DOI Listing

Quantitative Evaluation of Cerebellar Ataxia through Automated Assessment of Upper Limb Movements.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 16. Epub 2019 Apr 16.

Cerebellar damage can result in peripheral dysfunction manifesting as poor and inaccurate coordination, irregular movements and tremors. Conventionally, the severity assessment of Cerebellar ataxia (CA) is primarily based on expert clinical opinion and hence likely to be subjective. In order to establish inter rater concordance with enhanced reliability and effectiveness in the assessment of upper limb function, a novel automated system employing Microsoft Kinect is considered to capture the motion of the patient's finger for objective assessment. Read More

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https://ieeexplore.ieee.org/document/8692611/
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http://dx.doi.org/10.1109/TNSRE.2019.2911657DOI Listing
April 2019
1 Read

A Patient-Specific Single Sensor IoT-Based Wearable Fall Prediction and Detection System.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 16. Epub 2019 Apr 16.

Falls in! older adults are a major cause of morbidity and mortality and are a key class of preventable injuries. This paper presents a patient-specific (PS) fall prediction and detection prototype system that utilizes a single tri-axial accelerometer attached to the patient's thigh to distinguish between activities of daily living (ADL) and fall events. The proposed system consists of two modes of operation: 1) fast mode for fall predication (FMFP) predicting a fall event (300msec-700msec) before occurring, 2) slow mode for fall detection (SMFD) with a 1-sec latency for detecting a fall event. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911602DOI Listing

Adaptive Hybrid Classifier for Myoelectric Pattern Recognition Against the Interferences of Outlier Motion, Muscle Fatigue, and Electrode Doffing.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 16. Epub 2019 Apr 16.

Traditional myoelectric prostheses that employ a static pattern recognition model to identify human movement intention from surface electromyography (sEMG) signals hardly adapt to the changes in the sEMG characteristics caused by interferences from daily activities, which hinders the clinical applications of such prostheses. In this study, we focus on methods to reduce or eliminate the impacts of three types of daily interferences on myoelectric pattern recognition (MPR), i.e. Read More

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https://ieeexplore.ieee.org/document/8692622/
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http://dx.doi.org/10.1109/TNSRE.2019.2911316DOI Listing
April 2019
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Automated Fine Motor Evaluation for Developmental Coordination Disorder.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 16. Epub 2019 Apr 16.

Developmental Coordination Disorder (DCD) is a type of motor learning difficulty that affects five to six percent of school-aged children, which may have a negative impact on the life of the sufferers. Timely and objective diagnosis of DCD is important for the success of the intervention. The present evaluation methods of DCD rely heavily on observational analysis of occupational therapists and physiotherapists who score the performance when children conduct some designed tasks. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911303DOI Listing

Reduced Heat Generation During Magnetic Stimulation of Rat Sciatic Nerve Using Current Waveform Truncation.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 12. Epub 2019 Apr 12.

Introduction: Current truncating circuit designs used in some controllable pulse width transcranial magnetic stimulation systems can be adapted for use with the peripheral nervous system. Such a scaled-down stimulator produces neuromuscular activation using less stimulus energy than described in previous reports of sciatic nerve stimulation.

Methods: To evaluate the energy reductions possible with current truncation, we performed six in vivoexperiments in rats where the magnetic stimulating coil abutted the sciatic nerve. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911054DOI Listing
April 2019
2 Reads

Interference Removal from Electromyography based on Independent Component Analysis.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 11. Epub 2019 Apr 11.

High-density surface electromyography (HD-EMG) provides detailed information about muscle activation. However, HD-EMG recordings can be interfered by motion artifacts and power line noise. In this study, an interference detection and removal method with minimal distortion of the EMG was developed based on independent component analysis (ICA). Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2910387DOI Listing

Real-Time Performance of a Tactile Neuroprosthesis on Awake Behaving Rats.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 11. Epub 2019 Apr 11.

With the advancement of electrode and equipment technology, neuroprosthetics have become a promising alternative to partially compensate for the loss of sensorimotor function in amputees and patients with neurological diseases. Cortical neural interfaces are suitable especially for spinal cord injuries and amyotrophic lateral sclerosis. Although considerable success has been achieved in the literature by spike decoding of motor signáis from the human brain, somatosensory feedback is essential for better motor control, interaction with objects, and the embodiment of prosthetic devices. Read More

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https://ieeexplore.ieee.org/document/8688479/
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http://dx.doi.org/10.1109/TNSRE.2019.2910320DOI Listing
April 2019
2 Reads

Prediction of Freezing of Gait in Parkinson's Disease using Statistical Inference and Lower-Limb Acceleration Data.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 11. Epub 2019 Apr 11.

Freezing of gait (FoG) is a common type of motor dysfunction in advanced Parkinson's disease (PD) associated with falls. Over the last decade, a significant amount of studies has been focused on detecting FoG episodes in clinical and home environments. Yet, there remains a paucity of techniques regarding real-time prediction of FoG before its occurrence. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2910165DOI Listing

Hand Extension Robot Orthosis (HERO) Glove: Development and Testing with Stroke Survivors with Severe Hand Impairment.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 11. Epub 2019 Apr 11.

The Hand Extension Robot Orthosis (HERO) Glove was iteratively designed with occupational therapists and stroke survivors to enable stroke survivors with severe hand impairment to grasp and stabilize everyday objects, while being portable, lightweight, and easy to set up and use. The robot consists of a batting glove with artificial tendons embedded into the glove's fingers. The tendons are pulled and pushed by a linear actuator to extend and flex the fingers. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2910011DOI Listing

Segmentation of Exercise Repetitions Enabling Real-Time Patient Analysis and Feedback Using a Single Exemplar.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 11. Epub 2019 Apr 11.

We present a segmentation algorithm capable of segmenting exercise repetitions in real-time. This approach uses subsequence dynamic time warping and requires only a single exemplar repetition of an exercise to correctly segment repetitions from other subjects, including those with limited mobility. This approach is invariant to low range of motion, instability in movements and sensor noise while remaining selective to different exercises. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2907483DOI Listing

EEG Signal Processing in MI-BCI Applications with Improved Covariance Matrix Estimators.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 11. Epub 2019 Apr 11.

In brain-computer interfaces the typical models of the EEG observations usually lead to a poor estimation of the trial covariance matrices, given the high non-stationarity of the EEG sources. We propose the application of two techniques that significantly improve the accuracy of these estimations and can be combined with a wide range of motor imagery BCI methods. The first one scales the observations in such a way that implicitly normalizes the common temporal strength of the source activities. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2905894DOI Listing
April 2019
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A CNN-based Method for Intent Recognition Using Inertial Measurement Units and Intelligent Lower Limb Prosthesis.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 9. Epub 2019 Apr 9.

Powered intelligent lower limb prosthesis can actuate the knee and ankle joints, allowing transfemoral amputees to perform seamless transitions between locomotion states with the help of an intent recognition system. However, prior intent recognition studies often installed multiple sensors on the prosthesis, and they employed machine learning techniques to analyze time-series data with empirical features. We alternatively propose a novel method for training an intent recognition system that provides natural transitions between level walk, stair ascent / descent, and ramp ascent / descent. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2909585DOI Listing

Design of virtual guiding tasks with haptic feedback for assessing the wrist motor function of patients with upper motor neuron lesions.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 9. Epub 2019 Apr 9.

Impaired motor function is a common consequence of upper motor neuron lesions (UMNLs). Fine motor skills involved in small movements occurring in the fingers, hand and wrist are usually regained by patient self-training at home. Most studies focus on rehabilitation of the fingers but ignore recovery of wrist motor function. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2909287DOI Listing

A Carbon Slurry Separated Interface Nerve Electrode (CSINE) for Electrical Block of Nerve Conduction.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 4. Epub 2019 Apr 4.

Direct current (DC) nerve block has been shown to provide a complete block of nerve conduction without unwanted neural firing. Previous work shows that high capacitance electrodes can be used to safely deliver DC block. Another way of delivering DC safely is through a separated interface nerve electrode (SINE) such that any reactive species that are generated by the passage of DC are contained in a vessel away from the nerve. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2909165DOI Listing
April 2019
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A Dementia Classification Framework using Frequency and Time-frequency Features based on EEG signals.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 4. Epub 2019 Apr 4.

Alzheimer's Disease (AD) accounts for 60-70% of all dementia cases, and clinical diagnosis at its early stage is extremely difficult. As several new drugs aiming to modify disease progression or alleviate symptoms are being developed, to assess their efficacy, novel robust biomarkers of brain function are urgently required. This study aims to explore a routine to gain such biomarkers using the quantitative analysis of Electroencephalography (QEEG). Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2909100DOI Listing

On the Vulnerability of CNN Classifiers in EEG-Based BCIs.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 2. Epub 2019 Apr 2.

Deep learning has been successfully used in numerous applications because of its outstanding performance and the ability to avoid manual feature engineering. One such application is electroencephalogram (EEG) based brain-computer interface (BCI), where multiple convolutional neural network (CNN) models have been proposed for EEG classification. However, it has been found that deep learning models can be easily fooled with adversarial examples, which are normal examples with small deliberate perturbations. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2908955DOI Listing

Wavelet-based Muscle Artifact Noise Reduction for Short Latency rTMS Evoked Potentials.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 2. Epub 2019 Apr 2.

This paper presents a new method of reducing the noise in the EEG response signal recorded during repetitive transcranial magnetic stimulation (rTMS). This noise is principally composed of the residual stimulus artifact and mV amplitude compound muscle action potentials (CMAP) recorded from the scalp muscles and precludes analysis of the cortical evoked potentials, especially during the first 20 ms post stimulus. The proposed method uses the wavelet transform with a fourth order Daubechies mother wavelet and a novel coefficient reduction algorithm based on cortical amplitude thresholds. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2908951DOI Listing
April 2019
3 Reads

Virtual Reality Provides an Effective Platform for Functional Evaluations of Closed-loop Neuromyoelectric Control.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 2. Epub 2019 Apr 2.

Although recent advances in neuroprostheses offer opportunities for improved and intuitive control of advanced motorized and sensorized robotic arms, practical complications associated with such hardware can impede the research necessary for clinical translation. These hurdles potentially can be reduced with virtual reality environments (VREs) with embedded physics engines using virtual models of physical robotic hands. These software suites offer several advantages over physical prototypes, including high repeatability, reduced human error, elimination of many secondary sensory cues, and others. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2908817DOI Listing
April 2019
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Designing and Implementing a Novel Transcranial Electrostimulation System for Neuroplastic Applications: A Preliminary Study.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 2. Epub 2019 Apr 2.

Recently, a specific repetitive transcranial magnetic stimulation (rTMS) waveform, namely the theta burst stimulation (TBS) protocol, has been proposed for more efficiently inducing neuroplasticity for various clinic rehabilitation purposes. However, few studies have explored the feasibility of using the TBS combined with direct current (DC) waveform for brain neuromodulation; this waveform is transcranially delivered using electrical current power rather than magnetic power. This study implemented a prototype of a novel transcranial electrostimulation device that can flexibly output a waveform that combined DC and the TBS-like protocol and assessed the effects of the novel combinational waveform on neuroplasticity. Read More

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https://ieeexplore.ieee.org/document/8680031/
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http://dx.doi.org/10.1109/TNSRE.2019.2908674DOI Listing
April 2019
6 Reads

Brain-Machine Interface Driven Post-stroke Upper-limb Functional Recovery Correlates with Beta-band Mediated Cortical Networks.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 1. Epub 2019 Apr 1.

Brain-machine interface (BMI) driven robot-assisted neurorehabilitation intervention has demonstrated improvement in upper-limb (UL) motor function, specifically, with post-stroke hemiparetic patients. However, neurophysiological patterns related to such interventions are not well understood. This study examined the longitudinal changes in band-limited resting-state (RS) functional connectivity (FC) networks in association with post-stroke UL functional recovery achieved by a multimodal intervention involving motor attempt (MA) based BMI and robotic hand-exoskeleton. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2908125DOI Listing
April 2019
2 Reads

Estimating Multiscale Direct Causality Graphs in Neural Spike-Field Networks.

IEEE Trans Neural Syst Rehabil Eng 2019 Mar 28. Epub 2019 Mar 28.

Neural representations span various spatiotemporal scales of brain activity, from the spiking activity of single neurons to field activity measuring large-scale networks. Simultaneous analyses of spikes and fields to uncover causal interactions in multiscale networks could help understand neural mechanisms. However, assessing causality within spike-field networks is challenging as spikes are binary-valued with a fast timescale while fields are continuous-valued with slower timescales. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2908156DOI Listing

Simulating Hemiparetic Gait in Healthy Subjects using TPAD with a Closed-loop Controller.

IEEE Trans Neural Syst Rehabil Eng 2019 Mar 27. Epub 2019 Mar 27.

Hemiparetic gait is abnormal asymmetric walking, often observed among patients with cerebral palsy or stroke. One of the major features of asymmetric gait is excessive reliance on the healthy leg, which results in improper load shift, slow walking speed, higher metabolic cost, and weakness of the unused leg. Hence, clinically it is desirable to promote gait symmetry to improve walking. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2907683DOI Listing
March 2019
2 Reads

Neurophysiological Muscle Activation Scheme for Controlling Vocal Fold Models.

IEEE Trans Neural Syst Rehabil Eng 2019 Mar 18. Epub 2019 Mar 18.

A physiologically-based scheme that incorporates inherent neurological fluctuations in the activation of intrinsic laryngeal muscles into a lumped-element vocal fold model is proposed. Herein, muscles are activated through a combination of neural firing rate and recruitment of additional motor units, both of which have stochastic components. The mathematical framework and underlying physiological assumptions are described, and the effects of the fluctuations are tested via a parametric analysis using a body-cover model of the vocal folds for steady-state sustained vowels. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2906030DOI Listing
March 2019
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Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning.

IEEE Trans Neural Syst Rehabil Eng 2019 Mar 25. Epub 2019 Mar 25.

Research on machine learning approaches for upper limb prosthesis control has shown impressive progress. However, translating these results from the lab to patient's everyday lives remains a challenge, because advanced control schemes tend to break down under everyday disturbances, such as electrode shifts. Recently, it has been suggested to apply adaptive transfer learning to counteract electrode shifts using as little newly recorded training data as possible. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2907200DOI Listing

Transfer spectral entropy and application to functional corticomuscular coupling.

IEEE Trans Neural Syst Rehabil Eng 2019 Mar 25. Epub 2019 Mar 25.

Functional corticomuscular coupling (FCMC) with different rhythmic oscillations plays different roles in neural communication and interaction between the central nervous system and the peripheral system. Larger methods, such as coherence and Granger causality (GC), have been used to describe the frequency band characteristics in the frequency domain, but they fail to account for the inherent complexity. Considering that the transfer entropy (TE) method as an information theory has advantages in complexity and direction, we extended it and proposed a novel method named transfer spectral entropy (TSE) to explore the local frequency band characteristics between two coupling signals. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2907148DOI Listing

Comparison of the Use of Blink Rate and Blink Rate Variability for Mental State Recognition.

IEEE Trans Neural Syst Rehabil Eng 2019 Mar 20. Epub 2019 Mar 20.

Recent research has unearthed that blink rate variability (BRV) can be employed as a psychophysiological measure. However, its efficiency for mental state recognition (MSR) has not been investigated yet. Because BRV can indicate dynamics inherent in eye blinks, we conjectured that BRV might exhibit stronger abilities for the MSR if compared with blink rate (BR), known as the leading indicator derived from eye blinks for MSR. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2906371DOI Listing
March 2019
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Proportional Joint-Moment Control for Instantaneously Adaptive Ankle Exoskeleton Assistance.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 19;27(4):751-759. Epub 2019 Mar 19.

Lower-limb exoskeletons used to improve free-living mobility for individuals with neuromuscular impairment must be controlled to prescribe assistance that adapts to the diverse locomotor conditions encountered during daily life, including walking at different speeds and across varied terrain. The goal of this paper is to design and establish clinical feasibility of an ankle exoskeleton control strategy that instantly and appropriately adjusts assistance to the changing biomechanical demand during variable walking. To accomplish this goal, we developed a proportional joint-moment control strategy that prescribes assistance as a function of the instantaneous estimate of the ankle joint moment and conducted a laboratory-based feasibility study. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2905979DOI Listing
April 2019
2 Reads

Hand Gesture Recognition and Finger Angle Estimation via Wrist-Worn Modified Barometric Pressure Sensing.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 18;27(4):724-732. Epub 2019 Mar 18.

This paper presents a new approach to wearable hand gesture recognition and finger angle estimation based on the modified barometric pressure sensing. Barometric pressure sensors were encased and injected with VytaFlex rubber such that the rubber directly contacted the sensing element allowing pressure change detection when the encasing rubber was pressed. A wearable prototype consisting of an array of ten modified barometric pressure sensors around the wrist was developed and validated with experimental testing for three different hand gesture sets and finger flexion/extension trials for each of the five fingers. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2905658DOI Listing

The SonicHand Protocol for Rehabilitation of Hand Motor Function: A Validation and Feasibility Study.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 14;27(4):664-672. Epub 2019 Mar 14.

Musical sonification therapy is a new technique that can reinforce conventional rehabilitation treatments by increasing therapy intensity and engagement through challenging and motivating exercises. The aim of this paper is to evaluate the feasibility and validity of the SonicHand protocol, a new training and assessment method for the rehabilitation of hand function. The study was conducted in 15 healthy individuals and 15 stroke patients. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2905076DOI Listing

Design of a Low Profile, Unpowered Ankle Exoskeleton That Fits Under Clothes: Overcoming Practical Barriers to Widespread Societal Adoption.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 14;27(4):712-723. Epub 2019 Mar 14.

Here, we present the design of a novel unpowered ankle exoskeleton that is low profile, lightweight, quiet, and low cost to manufacture, intrinsically adapts to different walking speeds, and does not restrict non-sagittal joint motion; while still providing assistive ankle torque that can reduce demands on the biological calf musculature. This paper is an extension of the previously-successful ankle exoskeleton concept by Collins, Wiggin, and Sawicki. We created a device that blends the torque assistance of the prior exoskeleton with the form-factor benefits of clothing. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2904924DOI Listing
April 2019
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On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-Based Bio-Signal Decoding in BCI Speller Applications.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 13;27(4):611-618. Epub 2019 Mar 13.

Brain-computer interfaces (BCI) harnessing steady state visual evoked potentials (SSVEPs) manipulate the frequency and phase of visual stimuli to generate predictable oscillations in neural activity. For BCI spellers, oscillations are matched with alphanumeric characters allowing users to select target numbers and letters. Advances in BCI spellers can, in part, be accredited to subject-specific optimization, including; 1) custom electrode arrangements; 2) filter sub-band assessments; and 3) stimulus parameter tuning. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2904791DOI Listing

Recognition of Multiclass Epileptic EEG Signals Based on Knowledge and Label Space Inductive Transfer.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 13;27(4):630-642. Epub 2019 Mar 13.

Electroencephalogram (EEG) signal recognition based on machine learning models is becoming more and more attractive in epilepsy detection. For multiclass epileptic EEG signal recognition tasks including the detection of epileptic EEG signals from different blends of different background data and epilepsy EEG data and the classification of different types of seizures, we may perhaps encounter two serious challenges: (1) a large amount of EEG signal data for training are not available and (2) the models for epileptic EEG signal recognition are often so complicated that they are not as easy to explain as a linear model. In this paper, we utilize the proposed transfer learning technique to circumvent the first challenge and then design a novel linear model to circumvent the second challenge. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2904708DOI Listing

Online Learning of Gait Models From Older Adult Data.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 12;27(4):733-742. Epub 2019 Mar 12.

This paper proposes a novel approach for online, individualized gait analysis, based on an adaptive periodic model of any gait signal. The proposed method learns a model of the gait cycle during online measurement, using a continuous representation that can adapt to inter- and intra-personal variability by creating an individualized model. Once the algorithm has converged to the input signal, key gait events can be identified based on the estimated gait phase and amplitude. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2904477DOI Listing
April 2019
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The Step Response in Isometric Grip Force Tracking: A Model to Characterize Aging- and Stroke-Induced Changes.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 12;27(4):673-681. Epub 2019 Mar 12.

This paper aimed to construct a model to represent dynamic motor behavior to quantitatively investigate aging- and stroke-induced changes and, thus, to explore the underlying mechanisms of grip control. Grip force tracking tasks were conducted by stroke patients, age-matched healthy controls, and healthy young adults at 25%, 50%, and 75% maximum voluntary contractions (MVC), respectively. Sensorimotor control of the tracking task was modeled as the step response of a second-order system. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2904251DOI Listing

Age-Related Changes in Vibro-Tactile EEG Response and Its Implications in BCI Applications: A Comparison Between Older and Younger Populations.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 12;27(4):603-610. Epub 2019 Mar 12.

The rapid increase in the number of older adults around the world is accelerating research in applications to support age-related conditions, such as brain-computer interface (BCI) applications for post-stroke neurorehabilitation. The signal processing algorithms for electroencephalogram (EEG) and other physiological signals that are currently used in BCI have been developed on data from much younger populations. It is unclear how age-related changes may affect the EEG signal and therefore the use of BCI by older adults. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2890968DOI Listing

Neurogaming With Motion-Onset Visual Evoked Potentials (mVEPs): Adults Versus Teenagers.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 11;27(4):572-581. Epub 2019 Mar 11.

Motion-onset visually evoked potentials (mVEPs) are neural potentials that are time-locked to the onset of motion of evoking stimuli. Due to their visually elegant properties, mVEP stimuli may be suited to video game control given gaming's inherent demand on the users' visual attention and the requirement to process rapidly changing visual information. Here, we investigate mVEPs associated with five different stimuli to control the position of a car in a visually rich 3D racing game in a group of 15 BCI naïve teenagers and compared with 19 BCI naive adults. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2904260DOI Listing

Feature Selection and Non-Linear Classifiers: Effects on Simultaneous Motion Recognition in Upper Limb.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 8;27(4):743-750. Epub 2019 Mar 8.

Myoelectric signals are a standard input for volitional control of prosthetic devices. As an information-rich signal, feature selection plays a decisive role in the performance of motion classification. In this paper, we evaluate feature selection in the classification of simultaneous motions produced from combinations of wrist and elbow flexion/extension, radio-ulnar pronation/supination, and hand opening/closing aiming to determine a common set of recommendations for the implementation of motion classification from EMG signals for prosthetic control. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2903986DOI Listing

Consistent Gradient of Performance and Decoding of Stimulus Type and Valence From Local and Network Activity.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 8;27(4):619-629. Epub 2019 Mar 8.

The individual differences approach focuses on the variation of behavioral and neural signatures across subjects. In this context, we searched for intracranial neural markers of performance in three individuals with distinct behavioral patterns (efficient, borderline, and inefficient) in a dual-valence task assessing facial and lexical emotion recognition. First, we performed a preliminary study to replicate well-established evoked responses in relevant brain regions. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2903921DOI Listing

An Event-driven AR-process Model for EEG-based BCIs with Rapid Trial Sequences.

IEEE Trans Neural Syst Rehabil Eng 2019 Mar 8. Epub 2019 Mar 8.

Electroencephalography (EEG) is an effective noninvasive measurement method to infer user intent in braincomputer interface (BCI) systems for control and communication, however these systems often lack sufficient accuracy and speed due to low separability of class-conditional EEG feature distributions. Many factors impact system performance, including inadequate training datasets and models' ignorance of the temporal dependency of brain responses to serial stimuli. Here, we propose a signal model for event-related responses in EEG evoked with a rapid sequence of stimuli in BCI applications. Read More

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https://ieeexplore.ieee.org/document/8663441/
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http://dx.doi.org/10.1109/TNSRE.2019.2903840DOI Listing
March 2019
8 Reads

Asymmetry Index in Muscle Activations.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 7;27(4):772-779. Epub 2019 Mar 7.

Gait asymmetry is typically evaluated using spatio-temporal or joint kinematics parameters. Only a few studies addressed the problem of defining an asymmetry index directly based on muscle activity, extracting parameters from surface electromyography (sEMG) signals. Moreover, no studies used the extraction of the muscle principal activations (activations that are necessary for accomplishing a specific motor task) as the base to construct an asymmetry index, less affected by the variability of sEMG patterns. Read More

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https://ieeexplore.ieee.org/document/8662716/
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http://dx.doi.org/10.1109/TNSRE.2019.2903687DOI Listing
April 2019
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BCI Monitor Enhances Electroencephalographic and Cerebral Hemodynamic Activations During Motor Training.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 7;27(4):780-787. Epub 2019 Mar 7.

Motor imagery-based brain-computer interface (MI-BCI) controlling functional electrical stimulation (FES) is promising for disabled patients to restore their motor functions. However, it remains unclear how much the BCI part can contribute to the functional coupling between the brain and muscle. Specifically, whether it can enhance the cerebral activation for motor training? Here, we investigate the electroencephalographic and cerebral hemodynamic responses for MI-BCI-FES training and MI-FES training, respectively. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2903685DOI Listing

Impact of Different Acoustic Components on EEG-Based Auditory Attention Decoding in Noisy and Reverberant Conditions.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 7;27(4):652-663. Epub 2019 Mar 7.

Identifying the target speaker in hearing aid applications is an essential ingredient to improve speech intelligibility. Recently, a least-squares-based method has been proposed to identify the attended speaker from single-trial EEG recordings for an acoustic scenario with two competing speakers. This least-squares-based auditory attention decoding (AAD) method aims at decoding auditory attention by reconstructing the attended speech envelope from the EEG recordings using a trained spatio-temporal filter. Read More

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https://ieeexplore.ieee.org/document/8662636/
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http://dx.doi.org/10.1109/TNSRE.2019.2903404DOI Listing
April 2019
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Improving Reliability of Myocontrol Using Formal Verification.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 5;27(4):564-571. Epub 2019 Mar 5.

In the context of assistive robotics, myocontrol is one of the so-far unsolved problems of upper-limb prosthetics. It consists of swiftly, naturally, and reliably converting biosignals, non-invasively gathered from an upper-limb disabled subject, into control commands for an appropriate self-powered prosthetic device. Despite decades of research, traditional surface electromyography cannot yet detect the subject's intent to an acceptable degree of reliability, that is, enforce an action exactly when the subject wants it to be enforced. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2893152DOI Listing
April 2019
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Temporal-Spatial Patterns in Dynamic Functional Brain Network for Self-Paced Hand Movement.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 26;27(4):643-651. Epub 2019 Feb 26.

Dynamic functional connectivity is attracting a growing interest as it has been suggested to be a more accurate representation of functional brain networks compared to traditional functional connectivity. It is believed that the functional connectivity fluctuations result from the transitions among different brain states other than continuous changes in the brain. In this paper, we aim to investigate the spatial-temporal changes in the interactions between different brain regions during a self-paced hand movement with EEG signals. Read More

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https://ieeexplore.ieee.org/document/8653420/
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http://dx.doi.org/10.1109/TNSRE.2019.2901888DOI Listing
April 2019
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Self-Help Devices for Quadriplegic Population: A Systematic Literature Review.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 25;27(4):692-701. Epub 2019 Feb 25.

This systematic literature review collects and discusses the main needs, expectations, and barriers of people with quadriplegia and caregivers in relation to the self-help devices that are currently used for daily tasks. The major advantages, disadvantages, and challenges of the existing assistive technology are exposed and discussed in order to evaluate whether an existing technology could be combined with others to expand its scope, enhance its performance, or solve its limitations improving the adherence of quadriplegic population to these technologies and enhancing their quality of life. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2901399DOI Listing
April 2019
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Differentiation of Schizophrenia by Combining the Spatial EEG Brain Network Patterns of Rest and Task P300.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 22;27(4):594-602. Epub 2019 Feb 22.

The P300 is regarded as a psychosis endophenotype of schizophrenia and a putative biomarker of risk for schizophrenia. However, the brain activity (i.e. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2900725DOI Listing
April 2019
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Arbitrary-Waveform Electro-Optical Intracranial Neurostimulator With Load-Adaptive High-Voltage Compliance.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 21;27(4):582-593. Epub 2019 Feb 21.

A hybrid 16-channel current-mode and the 8-channel optical implantable neurostimulating system is presented. The system generates arbitrary-waveform charge-balanced current-mode electrical pulses with an amplitude ranging from 50 [Formula: see text] to 10 mA. An impedance monitoring feedback loop is employed to automatically adjust the supply voltage, yielding a load-optimized power dissipation. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2900455DOI Listing
April 2019
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Modeling Trans-Spinal Direct Current Stimulation in the Presence of Spinal Implants.

IEEE Trans Neural Syst Rehabil Eng 2019 Feb 22. Epub 2019 Feb 22.

Trans-spinal Direct Current Stimulation (tsDCS) is a technique considered for the treatment of corticospinal damage or dysfunction. TsDCS aims to induce functional modulation in the corticospinal circuitry via a direct current (DC) generated electric field. To ensure subject safety, subjects with metallic implants are generally excluded from receiving neural DC stimulation. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2900377DOI Listing
February 2019