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IEEE Transactions on Neural Systems and Rehabilitation Engineering

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https://www.readbyqxmd.com/read/28092567/inter-joint-coordination-deficits-revealed-in-the-decomposition-of-endpoint-jerk-during-goal-directed-arm-movement-after-stroke
#1
Jozsef Laczko, Robert Arthur Scheidt, Lucia S Simo, Davide Piovesan
It is well-documented that neurological deficits after stroke can disrupt motor control processes that affect the smoothness of reaching movements. The smoothness of hand trajectories during multi-joint reaching depends on shoulder and elbow joint angular velocities and their successive derivatives as well as on the instantaneous arm configuration and its rate of change. Right-handed survivors of unilateral hemiparetic stroke and neurologically-intact control participants held the handle of a two-joint robot and made horizontal planar reaching movements...
January 16, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28092566/wake-up-exoskeleton-to-assist-children-with-cerebral-palsy-design-and-preliminary-evaluation-in-level-walking
#2
Fabrizio Patane, Stefano Rossi, Fausto Del Sette, Juri Taborri, Paolo Cappa
This paper presents the modular design and control of a novel compliant lower limb multi-joint exoskeleton for the rehabilitation of ankle knee mobility and locomotion of pediatric patients with neurological diseases, such as Cerebral Palsy (CP). The device consists of an untethered powered knee-ankle-foot orthosis (KAFO), addressed as WAKE-up (Wearable Ankle Knee Exoskeleton), characterized by a position control and capable of operating synchronously and synergistically with the human musculoskeletal system...
January 11, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28092565/a-passive-eeg-bci-for-single-trial-detection-of-changes-in-mental-state
#3
Andrew Myrden, Tom Chau
Traditional brain-computer interfaces often exhibit unstable performance over time. It has recently been proposed that passive brain-computer interfaces may provide a way to complement and stabilize these traditional systems. In this study, we investigated the feasibility of a passive brain-computer interface that uses electroencephalography to monitor changes in mental state on a single-trial basis. We recorded cortical activity from 15 locations while 11 able-bodied adults completed a series of challenging mental tasks...
January 9, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28060708/characterization-and-decoding-the-spatial-patterns-of-hand-extension-flexion-using-high-density-ecog
#4
Tianxiao Jiang, Tao Jiang, Taylor Wang, Shanshan Mei, Qingzhu Liu, Yunlin Li, Xiaofei Wang, Sujit Prabhu, Zhiyi Sha, Nuri F Ince
During awake brain surgeries, electrocorticogram (ECoG) was recorded using a high density electrode grid from the motor cortex of two subjects while they were asked to execute spontaneous hand extension and flexion. Firstly, we characterized the spatio-spectral patterns of high-density ECoG during the hand movements. In both subjects, we observed event related desynchronization (ERD) in low frequency band (LFB:8-32Hz) and event related synchronization (ERS) in high frequency band (HFB:60-200Hz) where HFB-ERS was more spatially localized and movement specific compared to LFB-ERD...
January 4, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28055887/eeg-based-strategies-to-detect-motor-imagery-for-control-and-rehabilitation
#5
Kai Keng Ang, Cuntai Guan
Advances in Brain-Computer Interface (BCI) technology have facilitated the detection of Motor Imagery (MI) from electroencephalography (EEG). First, we present three strategies of using BCI to detect MI from EEG: operant conditioning that employed a fixed model, machine learning that employed a subject-specific model computed from calibration, and adaptive strategy that continuously compute the subjectspecific model. Second, we review prevailing works that employed the operant conditioning and machine learning strategies...
December 30, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28055886/long-term-stable-control-of-motor-imagery-bci-by-a-locked-in-user-through-adaptive-assistance
#6
Sareh Saeedi, Ricardo Chavarriaga, Jose Del R Millan
Performance variation is one of the main challenges that BCIs are confronted with, when being used over extended periods of time. Shared control techniques could partially cope with such a problem. In this paper, we propose a taxonomy of shared control approaches used for BCIs and we review some of the recent studies at the light of these approaches. We posit that the level of assistance provided to the BCI user should be adjusted in real time in order to enhance BCI reliability over time. This approach has not been extensively studied in the recent literature on BCIs...
December 28, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28026777/local-and-remote-cooperation-with-virtual-and-robotic-agents-a-p300-bci-study-in-healthy-and-people-living-with-spinal-cord-injury
#7
Emmanuele Tidoni, Mohammad Abu-Alqumsan, Daniele Leonardis, Christoph Kapeller, Gabriele Fusco, Christoph Guger, Cristoph Hintermueller, Angelika Peer, Antonio Frisoli, Franco Tecchia, Massimo Bergamasco, Salvatore M Aglioti
The development of technological applications that allow people to control and embody external devices within social interaction settings represents a major goal for current and future brain-computer interface (BCI) systems.
December 23, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28026779/combining-improved-gray-level-co-occurrence-matrix-with-high-density-grid-for-myoelectric-control-robustness-to-electrode-shift
#8
Jiayuan He, Xiangyang Zhu
Pattern recognition-based myoelectric control is greatly influenced by electrode shift, which is inevitable during prosthesis donning and doffing. This study used gray-level co-occurrence matrix (GLCM) to represent the spatial distribution among high density (HD) electrodes and improved its calculation based on the using condition of myoelectric system, proposing a new feature, iGLCM, to improve the robustness of the system. The effects of its two parameters, quantization level and input data, were first evaluated and it was found that improved discrete Fourier transform (iDFT) performed better than the other three (time-domain, autoregressive, root mean square) as the input data of iGLCM, and increasing quantization level did not significantly decrease the error rate of iGLCM when it was above 8...
December 22, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28026778/proactive-selective-inhibition-targeted-at-the-neck-muscles-this-proximal-constraint-facilitates-learning-and-regulates-global-control
#9
Ian Loram, Brian Bate, Peter Harding, Ryan Cunningham, Alison Loram
While individual muscle function is known, the sensory and motor value of muscles within the whole-body sensorimotor network is complicated. Specifically, the relationship between neck muscle action and distal muscle synergies is unknown. This work demonstrates a causal relationship between regulation of the neck muscles and global motor control. Studying violinists performing unskilled and skilled manual tasks, we provided ultrasound feedback of the neck muscles with instruction to minimize neck muscle change during task performance and observed the indirect effect on whole-body movement...
December 21, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28029625/comparison-of-classifier-architectures-for-online-neural-spike-sorting
#10
Maryam Saeed, Amir A Khan, Awais M Kamboh
High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach...
December 19, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28092564/static-vs-dynamic-decoding-algorithms-in-a-non-invasive-body-machine-interface
#11
Ismael Seanez-Gonzalez, Camilla Pierella, Ali Farshchiansadegh, Elias Barry Thorp, Farnaz Abdollahi, Jessica P Pedersen, Ferdinando A Mussa-Ivaldi
In this study, we consider a non-invasive bodymachine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare the effectiveness of two decoding algorithms that transform a highdimensional body-signal vector into a lower dimensional control vector on 6 subjects with high-level SCI and 8 controls. One algorithm is based on a static map from current body signals to the current value of the control vector set through principal component analysis (PCA), the other on dynamic mapping a segment of body signals to the value and the temporal derivatives of the control vector set through a Kalman filter...
December 15, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27992345/continuous-estimation-of-human-multi-joint-angles-from-semg-using-a-state-space-model
#12
Qichuan Ding, Jianda Han, Xingang Zhao
Due to the couplings among joint-relative muscles, it is a challenge to accurately estimate continuous multi-joint movements from multi-channel sEMG signals. Traditional approaches always build a nonlinear regression model, such as artificial neural network, to predict the multi-joint movement variables using sEMG as inputs. However, the redundant sEMGdata are always not distinguished; the prediction errors cannot be evaluated and corrected online as well. In this work, a correlation-based redundancy-segmentation method is proposed to segment the sEMG-vector including redundancy into irredundant and redundant subvectors...
December 14, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27992344/brain-machine-interface-control-algorithms
#13
Maryam M Shanechi
Motor brain-machine interfaces (BMI) allow subjects to control external devices by modulating their neural activity. BMIs record the neural activity, use a mathematical algorithm to estimate the subject's intended movement, actuate an external device, and provide visual feedback of the generated movement to the subject. A critical component of a BMI system is the control algorithm, termed decoder. Significant progress has been made in the design of BMI decoders in recent years resulting in proficient control in non-human primates and humans...
December 14, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27992343/comparison-of-constant-posture-force-varying-emg-force-dynamic-models-about-the-elbow
#14
Chenyun Dai, Berj Bardizbanian, Edward A Clancy
Numerous techniques have been used to minimize error in relating the surface electromyogram (EMG) to elbow joint torque. We compare the use of three techniques to further reduce error. First, most EMG-torque models only use estimates of EMG standard deviation as inputs. We studied the additional features of average waveform length, slope sign change rate and zero crossing rate. Second, multiple channels of EMG from the biceps, and separately from the triceps, have been combined to produce two low-variance model inputs...
December 14, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27992342/representation-learning-based-assistive-system-for-persons-with-dysarthria
#15
S Chandrakala, N Rajeswari
An assistive system for persons with vocal impairment due to dysarthria converts dysarthric speech to normal speech or text. Because of the articulatory deficits, dysarthric speech recognition needs a robust learning technique. Representation learning is significant for complex tasks such as dysarthric speech recognition. We focus on robust representation for dysarthric speech recognition that involves recognizing sequential patterns of varying length utterances. We propose a hybrid framework that uses a generative learning based data representation with a discriminative learning based classifier...
December 13, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27959816/a-real-time-gait-event-detection-for-lower-limb-prosthesis-control-and-evaluation
#16
Hafiz Farhan Maqbool, Muhammad Afif Bin Husman, Mohammed I Awad, Alireza Abouhossein, Nadeem Iqbal, Abbas A Dehghani-Sanij
Lower extremity amputees suffer from mobility limitations which will result in a degradation of their quality of life. Wearable sensors are frequently used to assess spatio-temporal, kinematic and kinetic parameters providing the means to establish an interactive control of the amputee-prosthesis-environment system. Gait events and the gait phase detection of an amputee's locomotion are vital for controlling lower limb prosthetic devices. The paper presents an approach to real-time gait event detection for lower limb amputees using a wireless gyroscope attached to the shank when performing level ground and ramp activities...
December 7, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27959815/ventral-tegmental-area-dopamine-neurons-firing-model-reveals-prenatal-nicotine-induced-alterations
#17
Andrei Dragomir, Yasemin M Akay, Die Zhang, Metin Akay
The dopamine (DA) neurons found in the Ventral Tegmental Area (VTA) are widely involved in the addiction and natural reward circuitry of the brain. Their firing patterns were shown to be important modulators of dopamine release and repetitive burst-like firing activity was highlighted as a major firing pattern of DA neurons in the VTA. In the present study we use a state space model to characterize the DA neurons firing patterns, and trace transitions of neural activity through bursting and non-bursting states...
December 6, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27925591/kinesthetic-feedback-during-2dof-wrist-movements-via-a-novel-mr-compatible-robot
#18
Andrew Erwin, Marcia O'Malley, David Ress, Fabrizio Sergi
We demonstrate the interaction control capabilities of the MR-SoftWrist, a novel MR-compatible robot capable of applying accurate kinesthetic feedback to wrist pointing movements executed during fMRI. The MR-SoftWrist, based on a novel design that combines parallel piezoelectric actuation with compliant force feedback, is capable of delivering 1.5 N·m of torque to the wrist of an interacting subject about the flexion/extension and radial/ulnar axes. The robot workspace, defined by admissible wrist rotation angles, fully includes a circle with a 20 deg radius...
December 1, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27913354/a-novel-elastic-force-field-to-influence-mediolateral-foot-placement-during-walking
#19
Elizabeth Nyberg, Jordan Broadway, Christian Finetto, Jesse Dean
Bipedal gait can be stabilized through mechanically-appropriate mediolateral foot placement, although this strategy is disrupted in a subset of neurologically injured individuals with balance deficits. The goal of the present work was to develop a device to influence mediolateral foot placement during treadmill walking. We created a novel force-field using a combination of passive elasticity and active control; wires in series with extension springs run parallel to the treadmill belts and can be rapidly repositioned to exert mediolateral forces on the legs of users...
December 1, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/27913353/embroidered-electromyography-a-systematic-design-guide
#20
Ali Shafti, Roger Ribas Manero, Amanda Borg, Kaspar Althoefer, Matthew Howard
Muscle activity monitoring or Electromyography (EMG) is a useful tool. However, EMG is typically invasive, expensive and difficult to use for untrained users. A possible solution is textile-based surface EMG (sEMG) integrated into clothing as a wearable device. This is, however, challenging due to (i) uncertainties in the electrical properties of conductive threads used for electrodes, (ii) imprecise fabrication technologies (e.g., embroidery, sewing), and (iii) lack of standardization in design variable selection...
December 1, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
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