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IEEE Transactions on Neural Systems and Rehabilitation Engineering

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https://www.readbyqxmd.com/read/29053448/the-effects-of-coding-schemes-on-vibrotactile-biofeedback-for-dynamic-balance-training-in-parkinson-s-disease-and-healthy-elderly-individuals
#1
Beom-Chan Lee, Alberto Fung, Timothy A Thrasher
A coding scheme for earlier versions of vibrotactile biofeedback systems for balance-related applications was primarily binary in nature, either off or on at a given threshold (range of postural tilt), making it unable to convey information about error magnitude. The purpose of this study was to explore the effects of two coding schemes (binary vs. continuous) for vibrotactile biofeedback during dynamic weight-shifting exercises that are common physical therapists' recommended balance exercises used in clinical settings...
October 16, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/29035220/robot-training-with-vector-fields-based-on-stroke-survivors-individual-movement-statistics
#2
Zachary A Wright, Emily Lazzaro, Kelly O Thielbar, James L Patton, Felix C Huang
The wide variation in upper extremity motor impairments among stroke survivors necessitates more intelligent methods of customized therapy. However, current strategies for characterizing individual motor impairments are limited by the use of traditional clinical assessments (e.g. Fugl-Meyer) and simple engineering metrics (e.g. goal-directed performance). Our overall approach is to statistically identify the range of volitional movement capabilities, and then apply a robot-applied force vector field intervention that encourages under-expressed movements...
October 16, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/29035219/an-embedded-real-time-processing-platform-for-optogenetic-neuroprosthetic-applications
#3
Boyuan Yan, Sheila Nirenberg
Optogenetics offers a powerful new approach for controlling neural circuits. It has numerous applications in both basic and clinical science. These applications require stimulating devices with small processors that can perform real-time neural signal processing, deliver high intensity light with high spatial and temporal resolution, and do not consume a lot of power. In this paper, we demonstrate the implementation of neuronal models in a platform consisting of an embedded system module and a portable DLP projector...
October 16, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/29035218/interacting-with-robots-to-investigate-the-bases-of-social-interaction
#4
Alessandra Sciutti, Giulio Sandini
Humans show a great natural ability at interacting with each other. Such efficiency in joint actions depends on a synergy between planned collaboration and emergent coordination, a subconscious mechanism based on a tight link between action execution and perception. This link supports phenomena as mutual adaptation, synchronization and anticipation, which cut drastically the delays in the interaction and the need of complex verbal instructions and result in the establishment of joint intentions, the backbone of social interaction...
October 16, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28991746/compensation-for-magnetic-disturbances-in-motion-estimation-to-provide-feedback-to-wearable-robotic-systems
#5
Sebastjan Slajpah, Roman Kamnik, Marko Munih
The direction of the Earth's magnetic field is used as a reference vector to determine the heading in orientation estimation with wearable sensors. However, the magnetic field strength is weak and can be easily disturbed in the vicinity of ferromagnetic materials, which may result in inaccurate estimate of orientation. The paper presents a novel method for estimating and compensating for magnetic disturbances. The compensation algorithm is implemented within a kinematic-based extended Kalman filter and is based on an assessment of the magnetic disturbance and the change of orientation in each time step...
October 6, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28981420/knee-motion-generation-method-for-transfemoral-prosthesis-based-on-kinematic-synergy-and-inertial-motion
#6
Hiroshi Sano, Takahiro Wada
Previous research has shown that the effective use of inertial motion (i.e., less or no torque input at the knee joint) plays an important role in achieving a smooth gait of transfemoral prostheses in the swing phase. In our previous research, a method for generating a timed knee trajectory close to able-bodied individuals, which leads to sufficient clearance between the foot and the floor and the knee extension, was proposed using the inertial motion. Limb motions are known to correlate with each other during walking...
October 5, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28981419/automatic-implementation-of-progressive-fastica-peel-off-for-high-density-surface-emg-decomposition
#7
Maoqi Chen, Xu Zhang, Xiang Chen, Ping Zhou
This study presents automatic decomposition of high density surface electromyogram (EMG) signals through a progressive FastICA peel-off (PFP) framework. By incorporating FastICA, constrained FastICA and a peel-off strategy, the PFP can progressively expand the set of motor unit spike trains contributing to the EMG signal. A series of signal processing techniques were applied and integrated in this study to automatically implement the two tasks that often require human operator interaction during application of the PFP framework, including extraction of motor unit spike trains from FastICA outputs and reliability judgement of the extracted motor units...
October 4, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28981418/covert-verb-reading-contributes-to-signal-classification-of-motor-imagery-in-bci
#8
Hong Zhang, Yaoru Sun, Jie Li, Fang Wang, Zijian Wang
Motor imagery is widely used in the brain-computer interface (BCI) systems that can help people actively control devices to directly communicate with the external world, but its training and performance effect is usually poor for normal people. To improve operators' BCI performances, here we proposed a novel paradigm, which combined the covert verb reading in the traditional motor imagery paradigm. In our proposed paradigm, participants were asked to covertly read the presented verbs during imagining right hand or foot movements referred by those verbs...
October 4, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28976318/mechanical-impedance-of-the-ankle-during-the-terminal-stance-phase-of-walking
#9
Amanda L Shorter, Elliott J Rouse
Human joint impedance describes the dynamic relationship between perturbation induced change in position and the resulting response torque. Understanding the natural regulation of ankle impedance during locomotion is necessary to discern how humans interact with their environments, and provide a foundation for the design of biomimetic assistive devices and their control systems. This study estimates ankle impedance during terminal stance phase of walking using a parametric model consisting of stiffness, damping, and inertia...
September 29, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28961119/filter-bank-regularized-common-spatial-pattern-ensemble-for-small-sample-motor-imagery-classification
#10
Sang-Hoon Park, David Lee, Sang-Goog Lee
For the last few years, many feature extraction methods have been proposed based on biological signals. Among these, brain signals have the advantage that they can be obtained, even by people with peripheral nervous system damage. Motor imagery electroencephalograms (EEG) are inexpensive to measure, offer a high temporal resolution, and are intuitive. Therefore, these have received a significant amount of attention in various fields, including signal processing, cognitive science, and medicine. The common spatial pattern (CSP) algorithm is a useful method for feature extraction from motor imagery EEG...
September 28, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28961118/advanced-boundary-electrode-modeling-for-tes-and-parallel-tes-eeg
#11
S Pursiainen, B Agsten, S Wagner, C H Wolters
This paper explores advanced electrode modeling in the context of separate and parallel transcranial electrical stimulation (tES) and electroencephalography (EEG) measurements.We focus on boundary condition based approaches that do not necessitate adding auxiliary elements, e.g. sponges, to the computational domain. In particular, we investigate the complete electrode model (CEM) which incorporates a detailed description of the skin-electrode interface including its contact surface, impedance and normal current distribution...
September 28, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28961117/high-frequency-ssvep-bci-with-hardware-stimuli-control-and-phase-synchronized-comb-filter
#12
Anna Chabuda, Piotr Durka, Jaroslaw Zygierewicz
We present an efficient implementation of braincomputer interface (BCI) based on high-frequency steady state visually evoked potentials (SSVEP). Individual shape of the SSVEP response is extracted by means of a feedforward comb filter, which adds delayed versions of the signal to itself. Rendering of the stimuli is controlled by specialized hardware (BCI Appliance). Out of 15 participants of the study, 9 were able to produce stable response in at least 8 out of 10 frequencies from the 30-39 Hz range. They achieved on average 96±4% accuracy and 47±5 bit/min information transfer rate (ITR) for an optimized simple 7-letter speller, while generic full-alphabet speller allowed in this group for 89±9% accuracy and 36±9 bit/min ITR...
September 28, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28952946/model-based-dynamic-control-allocation-in-a-hybrid-neuroprosthesis
#13
Nicholas A Kirsch, Xuefeng Bao, Naji A Alibeji, Brad E Dicianno, Nitin Sharma
A hybrid neuroprosthesis that combines human muscle power, elicited through functional electrical stimulation (FES), with a powered orthosis may be advantageous over a sole FES or a powered exoskeleton-based rehabilitation system. The hybrid system can conceivably overcome torque reduction due to FESinduced muscle fatigue by complementarily using torque from the powered exoskeleton. The second advantage of the hybrid system is that the use of human muscle power can supplement the powered exoskeleton's power (motor torque) requirements; thus, potentially reducing the size and weight of a walking restoration system...
September 22, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28952945/detection-of-interictal-discharges-with-convolutional-neural-networks-using-discrete-ordered-multichannel-intracranial-eeg
#14
Andreas Antoniades, Loukianos Spyrou, David Martin-Lopez, Antonio Valentin, Gonzalo Alarcon, Saeid Sanei, Clive Cheong Took
Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditionally employed handcrafted features which utilised specific characteristics of neural responses. Although these algorithms achieve high accuracy, mere detection of an IED holds little clinical significance. In this work, we consider deep learning for epileptic subjects to accommodate automatic feature generation from intracranial EEG data, while also providing clinical insight...
September 22, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28952944/automated-evaluation-of-upper-limb-motor-function-impairment-using-fugl-meyer-assessment
#15
Seunghee Lee, Yang-Soo Lee, Jonghyun Kim
The Fugl-Meyer assessment (FMA) is the most popular instrument for evaluating upper extremity motor function in stroke patients. However, it is a labor-intensive and timeconsuming method. This paper proposes a novel automated FMA system to overcome these limitations of the FMA. For automation, we used Kinect v2 and force sensing resistor sensors owing to their convenient installation as compared with body-worn sensors. Based on the linguistic guideline of the FMA, a rule-based binary logic classification algorithm was developed to assign FMA scores using the extracted features obtained from the sensors...
September 22, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28945598/double-errp-detection-for-automatic-error-correction-in-an-erp-based-bci-speller
#16
Aniana Cruz, Gabriel Pires, Urbano J Nunes
Brain-computer interface (BCI) is a useful device for people with severe motor disabilities. However due to its low speed and low reliability, BCI still has a very limited application in daily real-world tasks. This paper proposes a P300-based BCI speller combined with a double error-related potential (ErrP) detection to automatically correct erroneous decisions. This novel approach introduces a second error detection to infer whether wrong automatic correction also elicits a second ErrP. Thus, two single-trial responses, instead of one, contribute to the final selection, improving the reliability of error detection...
September 21, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28945597/motor-task-detection-from-human-stn-using-interhemispheric-connectivity
#17
Soroush Niketeghad, Adam O Hebb, Joshua Nedrud, Sara J Hanrahan, Mohammad H Mahoor
Deep Brain Stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson's disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient's behavior. Subthalamic Nucleus (STN) Local field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors...
September 21, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28920904/modeling-the-nonlinear-cortical-response-in-eeg-evoked-by-wrist-joint-manipulation
#18
Martijn P Vlaar, Georgios Birpoutsoukis, John Lataire, Maarten Schoukens, Alfred C Schouten, Johan Schoukens, Frans C T van der Helm
Joint manipulation elicits a response from the sensors in the periphery which, via the spinal cord, arrives in the cortex. The average evoked cortical response recorded using electroencephalography was shown to be highly nonlinear; a linear model can only explain 10% of the variance of the evoked response, and over 80% of the response is generated by nonlinear behavior. The goal of this study is to obtain a nonparametric nonlinear dynamic model, which can consistently explain the recorded cortical response requiring little a priori assumptions about model structure...
September 13, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28920903/brain-control-of-an-external-device-by-extracting-the-highest-force-related-contents-of-local-field-potentials-in-freely-moving-rats
#19
Abed Khorasani, Reza Foodeh, Vahid Shalchyan, Mohammad Reza Daliri
A local field potential (LFP) signal is an alternative source to neural action potentials for decoding kinematic and kinetic information from the brain. Here we demonstrate that better extraction of force-related features from multichannel LFPs improves the accuracy of force decoding. We propose that applying canonical correlation analysis (CCA) filter on the envelopes of separate frequency bands (band-specific CCA) seperates non- task related information from the LFPs. The decoding accuracy of the continuous force signal based on the proposed method were compared with three feature reduction methods: 1) Band-specific principal component analysis (bandspecific PCA) method that extract the components which leads to maximum variance from envelopes of different frequency bands, 2) Correlation coefficient-based (CC-based) feature reduction that selects the best features from the envelopes sorted based on the absolute correlation coefficient between each envelope and the target force signal and 3) Mutual information -based (MI-based) feature reduction that selects the best features from the envelopes sorted based on the mutual information between each envelope and output force signal...
September 12, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28885156/the-vspa-foot-a-quasi-passive-ankle-foot-prosthesis-with-continuously-variable-stiffness
#20
Max K Shepherd, Elliott J Rouse
Most commercially available prosthetic feet do not exhibit a biomimetic torque-angle relationship, and are unable to modulate their mechanics to assist with other mobility tasks, such as stairs and ramps. In this work, we present a quasi-passive ankle-foot prosthesis with a customizable torque-angle curve and an ability to quickly modulate ankle stiffness between tasks. The customizable torque-angle curve is obtained with a cam-based transmission and a fiberglass leaf spring. To achieve variable stiffness, the leaf spring's support conditions can be actively modulated by a small motor, shifting the torque-angle curve to be more or less stiff...
September 7, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
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