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Front cover IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-11-06
Presents the front cover for this issue of the publication.
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IEEE Transactions on Neural Systems and Rehabilitation Engineering publication information IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-11-06
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Table of contents IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-11-06
Presents the table of contents for this issue of the publication.
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Reducing Calibration Efforts in RSVP Tasks With Multi-Source Adversarial Domain Adaptation IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-14 Wei Wei; Shuang Qiu; Xuelin Ma; Dan Li; Bo Wang; Huiguang He
Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface (BCI) is an efficient information detection technology by detecting event-related brain responses evoked by target visual stimuli. However, a time-consuming calibration procedure is needed before a new user can use this system. Thus, it is important to reduce calibration efforts for BCI applications. In this article, we propose
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Deep Temporal-Spatial Feature Learning for Motor Imagery-Based Brain–Computer Interfaces IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-21 Junjian Chen; Zhuliang Yu; Zhenghui Gu; Yuanqing Li
Motor imagery (MI) decoding is an important part of brain-computer interface (BCI) research, which translates the subject’s intentions into commands that external devices can execute. The traditional methods for discriminative feature extraction, such as common spatial pattern (CSP) and filter bank common spatial pattern (FBCSP), have only focused on the energy features of the electroencephalography
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A Unified Analytical Framework With Multiple fNIRS Features for Mental Workload Assessment in the Prefrontal Cortex IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-28 Lam Ghai Lim; Wei Chun Ung; Yee Ling Chan; Cheng-Kai Lu; Stephanie Sutoko; Tsukasa Funane; Masashi Kiguchi; Tong Boon Tang
Knowing the actual level of mental workload is important to ensure the efficacy of brain-computer interface (BCI) based cognitive training. Extracting signals from limited area of a brain region might not reveal the actual information. In this study, a functional near-infrared spectroscopy (fNIRS) device equipped with multi-channel and multi-distance measurement capability was employed for the development
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EEG-Based Prediction of Successful Memory Formation During Vocabulary Learning IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-10 Taeho Kang; Yiyu Chen; Siamac Fazli; Christian Wallraven
Previous Electroencephalography (EEG) and neuroimaging studies have found differences between brain signals for subsequently remembered and forgotten items during learning of items - it has even been shown that single trial prediction of memorization success is possible with a few target items. There has been little attempt, however, in validating the findings in an application-oriented context involving
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A Computerized Method for Automatic Detection of Schizophrenia Using EEG Signals IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-08 Siuly Siuly; Smith K. Khare; Varun Bajaj; Hua Wang; Yanchun Zhang
Diagnosis of schizophrenia (SZ) is traditionally performed through patient’s interviews by a skilled psychiatrist. This process is time-consuming, burdensome, subject to error and bias. Hence the aim of this study is to develop an automatic SZ identification scheme using electroencephalogram (EEG) signals that can eradicate the aforementioned problems and support clinicians and researchers. This study
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Automatic Identification of High-Risk Autism Spectrum Disorder: A Feasibility Study Using Video and Audio Data Under the Still-Face Paradigm IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-29 Chuangao Tang; Wenming Zheng; Yuan Zong; Nana Qiu; Cheng Lu; Xilei Zhang; Xiaoyan Ke; Cuntai Guan
It is reported that the symptoms of autism spectrum disorder (ASD) could be improved by effective early interventions, which arouses an urgent need for large-scale early identification of ASD. Until now, the screening of ASD has relied on the child psychiatrist to collect medical history and conduct behavioral observations with the help of psychological assessment tools. Such screening measures inevitably
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Zero-Shot Learning for EEG Classification in Motor Imagery-Based BCI System IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-28 Lili Duan; Jie Li; Hongfei Ji; Zilong Pang; Xuanci Zheng; Rongrong Lu; Maozhen Li; Jie Zhuang
A brain-computer interface (BCI) based on motor imagery (MI) translates human intentions into computer commands by recognizing the electroencephalogram (EEG) patterns of different imagination tasks. However, due to the scarcity of MI commands and the long calibration time, using the MI-based BCI system in practice is still challenging. Zero-shot learning (ZSL), which can recognize objects whose instances
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Functional Brain Connectivity Analysis in Intellectual Developmental Disorder During Music Perception IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-21 Ekansh Sareen; Lakshya Singh; Anubha Gupta; Rohit Verma; G. Krishnaveni Achary; Blessin Varkey
Intellectual Developmental Disorder (IDD) is a neurodevelopmental disorder involving impairment of general cognitive abilities. This disorder impacts the conceptual, social, and practical skills adversely. There is a growing interest in exploring the neurological behavior associated with these disorders. Assessment of functional brain connectivity and graph theory measures have emerged as powerful
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Computer Vision to Automatically Assess Infant Neuromotor Risk IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-06 Claire Chambers; Nidhi Seethapathi; Rachit Saluja; Helen Loeb; Samuel R. Pierce; Daniel K. Bogen; Laura Prosser; Michelle J. Johnson; Konrad P. Kording
An infant’s risk of developing neuromotor impairment is primarily assessed through visual examination by specialized clinicians. Therefore, many infants at risk for impairment go undetected, particularly in under-resourced environments. There is thus a need to develop automated, clinical assessments based on quantitative measures from widely-available sources, such as videos recorded on a mobile device
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Multiplayer Interaction Platform With Gaze Tracking for Individuals With Autism IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-25 Pradeep Raj Krishnappa Babu; Uttama Lahiri
Deficits in interpersonal communication along with difficulty in putting oneself into the shoes of others characterizes individuals with Autism Spectrum Disorder (ASD). Additionally, they exhibit atypical looking pattern causing them to miss aspects related to understanding other’s preference for a context that is crucial for effective social communication. Prior research studies show the use of multiplayer
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The Myokinetic Control Interface: How Many Magnets Can be Implanted in an Amputated Forearm? Evidence From a Simulated Environment IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-21 Stefano Milici; Marta Gherardini; Francesco Clemente; Federico Masiero; Paolo Sassu; Christian Cipriani
We recently introduced the concept of a new human-machine interface (the myokinetic control interface ) to control hand prostheses. The interface tracks muscle contractions via permanent magnets implanted in the muscles and magnetic field sensors hosted in the prosthetic socket. Previously we showed the feasibility of localizing several magnets in non-realistic workspaces. Here, aided by a 3D CAD model
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Intrathecal Delivery of BDNF Into the Lumbar Cistern Re-Engages Locomotor Stepping After Spinal Cord Injury IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-28 Francesca Marchionne; Alexander J. Krupka; George M. Smith; Michel A. Lemay
Delivery of neurotrophins to the spinal injury site via cellular transplants or viral vectors administration has been shown to promote recovery of locomotion in the absence of locomotor training in adult spinalized animals. These delivery methods involved risks of secondary injury to the cord and do not allow for precise and controlled dosing making them unsuitable for clinical applications. The present
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A Complex Stiffness Human Impedance Model With Customizable Exoskeleton Control IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-28 Binghan He; Huang Huang; Gray Cortright Thomas; Luis Sentis
The natural impedance, or dynamic relationship between force and motion, of a human operator can determine the stability of exoskeletons that use interaction-torque feedback to amplify human strength. While human impedance is typically modelled as a linear system, our experiments on a single-joint exoskeleton testbed involving 10 human subjects show evidence of nonlinear behavior: a low-frequency asymptotic
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A Gaussian Process Model of Muscle Synergy Functions for Estimating Unmeasured Muscle Excitations Using a Measured Subset IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-01 Reed D. Gurchiek; Anna T. Ursiny; Ryan S. McGinnis
Estimation of muscle excitations from a reduced sensor array could greatly improve current techniques in remote patient monitoring. Such an approach could allow continuous monitoring of clinically relevant biomechanical variables that are ideal for personalizing rehabilitation. In this paper, we introduce the notion of a muscle synergy function which describes the synergistic relationship between a
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Automatic Diagnosis of Cerebral Palsy Gait Using Computational Intelligence Techniques: A Low-Cost Multi-Sensor Approach IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-01 Saikat Chakraborty; Anup Nandy
Automatic diagnosing of Cerebral Palsy (CP) gait is crucial in quantitative evaluation of a therapeutic intervention. Existing systems for such gait assessment are expensive and require user intervention. This study proposes a low-cost gait assessment system equipped with multiple Kinect sensors. Forty subjects (20 CP patients and 20 normal) were recruited for the experiment. To remove outlier frames
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Evaluation of the Nino® Two-Wheeled Power Mobility Device: A Pilot Study IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-02 Johanne Mattie; Jazzmin Tavares; Bryn Matheson; Emma Smith; Ian Denison; William C. Miller; Jaimie F. Borisoff
Novel technologies such as the Nino® two-wheeled powered mobility device are promoted as offering an intuitive improved experience compared to conventional wheelchair mobility use. The Nino® has a smaller footprint than a power wheelchair, a zero-degree turning radius, tiller-based steering, and relies on the user leaning forwards and back to move and brake. This study aimed to evaluate manual wheelchair
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Resilient EMG Classification to Enable Reliable Upper-Limb Movement Intent Detection IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-21 Vinicius Horn Cene; Alexandre Balbinot
Reliable control of assistive devices using surface electromyography (sEMG) remains an unsolved task due to the signal’s stochastic behavior that prevents robust pattern recognition for real-time control. Non-representative samples lead to inherent class overlaps that generate classification ripples for which the most common alternatives rely on post-processing and sample discard methods that insert
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Time-Frequency Maximal Information Coefficient Method and its Application to Functional Corticomuscular Coupling IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-01 Tie Liang; Qingyu Zhang; Xiaoguang Liu; Cunguang Lou; Xiuling Liu; Hongrui Wang
An important challenge in the study of functional corticomuscular coupling (FCMC) is an accurate capture of the coupling relationship between the cerebral cortex and the effector muscle. The coherence method is a linear analysis method, which has certain limitations in further revealing the nonlinear coupling between neural signals. Although mutual information (MI) and transfer entropy (TE) based on
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Interhemispheric Functional Reorganization and its Structural Base After BCI-Guided Upper-Limb Training in Chronic Stroke IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-30 Kai Yuan; Xin Wang; Cheng Chen; Cathy Choi-Yin Lau; Winnie Chiu-Wing Chu; Raymond Kai-Yu Tong
Brain–computer interface (BCI)-guided robot-assisted upper-limb training has been increasingly applied to stroke rehabilitation. However, the induced long-term neuroplasticity modulation still needs to be further characterized. This study investigated the functional reorganization and its structural base after BCI-guided robot-assisted training using resting-state fMRI, task-based fMRI, and diffusion
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FPGA-Based Real-Time Simulation Platform for Large-Scale STN-GPe Network IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-29 Min Chen; Linlu Zu; Hong Wang; Fei Su
The real-time simulation of large-scale subthalamic nucleus (STN)-external globus pallidus (GPe) network model is of great significance for the mechanism analysis and performance improvement of deep brain stimulation (DBS) for Parkinson’s states. This paper implements the real-time simulation of a large-scale STN-GPe network containing 512 single-compartment Hodgkin-Huxley type neurons on the Altera
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Targeted Stimulation of Retinal Ganglion Cells in Epiretinal Prostheses: A Multiscale Computational Study IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-29 Javad Paknahad; Kyle Loizos; Mark Humayun; Gianluca Lazzi
Retinal prostheses aim at restoring partial sight to patients that are blind due to retinal degenerative diseases by electrically stimulating the surviving healthy retinal neurons. Ideally, the electrical stimulation of the retina is intended to induce localized, focused, percepts only; however, some epiretinal implant subjects have reported seeing elongated phosphenes in a single electrode stimulation
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Architectural Changes in Superficial and Deep Compartments of the Tibialis Anterior During Electrical Stimulation Over Different Sites IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-28 Marco Carbonaro; Olivier Seynnes; Nicola A. Maffiuletti; Chiara Busso; Marco A. Minetto; Alberto Botter
Electrical stimulation is widely used in rehabilitation to prevent muscle weakness and to assist the functional recovery of neural deficits. Its application is however limited by the rapid development of muscle fatigue due to the non-physiological motor unit (MU) recruitment. This issue can be mitigated by interleaving muscle belly (mStim) and nerve stimulation (nStim) to distribute the temporal recruitment
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Classification of Rhythmic Cortical Activity Elicited by Whole-Body Balance Perturbations Suggests the Cortical Representation of Direction-Specific Changes in Postural Stability IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-06 Teodoro Solis-Escalante; Digna De Kam; Vivian Weerdesteyn
Postural responses that effectively recover balance following unexpected postural changes need to be tailored to the characteristics of the postural change. We hypothesized that cortical dynamics involved in top-down regulation of postural responses carry information about directional postural changes (i.e., sway) imposed by sudden perturbations to standing balance (i.e., support surface translations)
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Beta-Range Corticomuscular Coupling Reflects Asymmetries in Hand Movement IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-07 Xiaoling Chen; Yuanyuan Zhang; Yinan Yang; Xiaoli Li; Ping Xie
Hand movement in humans is verified as asymmetries and lateralization, and two hemispheres make some distinct but complementary contributions in the control of hand movement. However, little research has been done on whether the information transfer of the motor system is different between left and right hand movement. Considering the importance of functional corticomuscular coupling (FCMC) between
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IEEE Transactions on Neural Systems and Rehabilitation Engineering information for authors IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-11-06
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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Front cover IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-07
Presents the front cover for this issue of the publication.
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IEEE Transactions on Neural Systems and Rehabilitation Engineering publication information IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-07
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Table of contents IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-07
Presents the table of contents for this issue of the publication.
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Enhanced Performance of a Brain Switch by Simultaneous Use of EEG and NIRS Data for Asynchronous Brain-Computer Interface IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-17 Chang-Hee Han; Klaus-Robert Müller; Han-Jeong Hwang
Previous studies have shown the superior performance of hybrid electroencephalography (EEG)/ near-infrared spectroscopy (NIRS) brain-computer interfaces (BCIs). However, it has been veiled whether the use of a hybrid EEG/NIRS modality can provide better performance for a brain switch that can detect the onset of the intention to turn on a BCI. In this study, we developed such a hybrid EEG/NIRS brain
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The EEG Signal Analysis for Spatial Cognitive Ability Evaluation Based on Multivariate Permutation Conditional Mutual Information-Multi-Spectral Image IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-24 Dong Wen; Jingpeng Yuan; Yanhong Zhou; Jian Xu; Haiqing Song; Yijun Liu; Yuchen Xu; Tzyy-Ping Jung
This study aims to find an effective method to evaluate the efficacy of cognitive training of spatial memory under a virtual reality environment, by classifying the EEG signals of subjects in the early and late stages of spatial cognitive training. This study proposes a new EEG signal analysis method based on Multivariate Permutation Conditional Mutual Information-Multi-Spectral Image (MPCMIMSI). This
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Inter- and Intra-Subject Transfer Reduces Calibration Effort for High-Speed SSVEP-Based BCIs IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-25 Chi Man Wong; Ze Wang; Boyu Wang; Ka Fai Lao; Agostinho Rosa; Peng Xu; Tzyy-Ping Jung; C. L. Philip Chen; Feng Wan
Objective: Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) that can deliver a high information transfer rate (ITR) usually require subject’s calibration data to learn the class- and subject-specific model parameters (e.g. the spatial filters and SSVEP templates). Normally, the amount of the calibration data for learning is proportional to the number of classes (or
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W:Ti Flexible Transversal Electrode Array for Peripheral Nerve Stimulation: A Feasibility Study IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-13 Carolina Silveira; Emma Brunton; Enrique Escobedo-Cousin; Gaurav Gupta; Roger Whittaker; Anthony O’Neill; Kianoush Nazarpour
The development of hardware for neural interfacing remains a technical challenge. We introduce a flexible, transversal intraneural tungsten:titanium electrode array for acute studies. We characterize the electrochemical properties of this new combination of tungsten and titanium using cyclic voltammetry and electrochemical impedance spectroscopy. With an in-vivo rodent study, we show that the stimulation
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Optimal Control Perspective on Parkinson’s Disease: Increased Delay Between State Estimator and Controller Produces Tremor IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-21 Christopher R. Kelley; Jeffrey L. Kauffman
Parkinson’s disease produces tremor in a large subset of patients despite generally inhibiting movement. The pathophysiology of parkinsonian tremor is unclear, leading to uncertainty in how and why treatments reduce tremor with varying effectiveness. Models for parkinsonian tremor attempt to explain the underlying principles of tremor generation in the central nervous system, often focusing on neural
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Bispectrum-Based Channel Selection for Motor Imagery Based Brain-Computer Interfacing IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-01 Jing Jin; Chang Liu; Ian Daly; Yangyang Miao; Shurui Li; Xingyu Wang; Andrzej Cichocki
The performance of motor imagery (MI) based Brain-computer interfacing (BCI) is easily affected by noise and redundant information that exists in the multi-channel electroencephalogram (EEG). To solve this problem, many temporal and spatial feature based channel selection methods have been proposed. However, temporal and spatial features do not accurately reflect changes in the power of the oscillatory
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Topological Network Analysis of Early Alzheimer’s Disease Based on Resting-State EEG IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-07 Feng Duan; Zihao Huang; Zhe Sun; Yu Zhang; Qibin Zhao; Andrzej Cichocki; Zhenglu Yang; Jordi Solé-Casals
Previous studies made progress in the early diagnosis of Alzheimer’s disease (AD) using electroencephalography (EEG) without considering EEG connectivity. To fill this gap, we explored significant differences between early AD patients and controls based on frequency domain and spatial properties using functional connectivity in mild cognitive impairment (MCI) and mild AD datasets. Four global metrics
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Model Predictive Control for Seizure Suppression Based on Nonlinear Auto-Regressive Moving-Average Volterra Model IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-07 Siyuan Chang; Xile Wei; Fei Su; Chen Liu; Guosheng Yi; Jiang Wang; Chunxiao Han; Yanqiu Che
This article investigates a closed-loop brain stimulation method based on model predictive control strategy to suppress epileptic seizures. A neural mass model (NMM), exhibiting the normal and various epileptic seizures by changing physiologically meaningful parameters, is used as a black-box model of the brain. Based on system identification, an auto-regressive moving-average Volterra model is established
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Targeted Pelvic Constraint Force Induces Enhanced Use of the Paretic Leg During Walking in Persons Post-Stroke IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-20 Seoung Hoon Park; Jui-Te Lin; Weena Dee; Chao-Jung Hsu; Elliot J. Roth; William Z. Rymer; Ming Wu
The purpose of this study was to determine whether activation of muscles in the paretic leg, particularly contributing to propulsion, and gait symmetry can be improved by applying a targeted resistance force to the pelvis in the backward direction during stance phase while walking in individuals post-stroke. Thirteen individuals post-stroke participated in two experimental sessions, which consisted
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Effects of Varying Plantarflexion Stiffness of Ankle-Foot Orthosis on Achilles Tendon and Propulsion Force During Gait IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-31 Masataka Yamamoto; Koji Shimatani; Masaki Hasegawa; Yuichi Kurita
An ankle-foot orthosis (AFO) with a plantarflexion resistance function, improves post-stroke gait. An AFO with a plantarflexion resistance function not only affects the first rocker function and the weight acceptance but also the late stance phase. Achilles tendon extension is important for ankle joint function and for forward propulsion during the late stance phase; however, the effect of an AFO with
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Adapting to the Mechanical Properties and Active Force of an Exoskeleton by Altering Muscle Synergies in Chronic Stroke Survivors IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-17 Linda Rinaldi; Ling-Fung Yeung; Patrick Chi-Hong Lam; Marco Y. C. Pang; Raymond Kai-Yu Tong; Vincent C. K. Cheung
Chronic stroke survivors often suffer from gait impairment resistant to intervention. Recent rehabilitation strategies based on gait training with powered exoskeletons appear promising, but whether chronic survivors may benefit from them remains controversial. We evaluated the potential of exoskeletal gait training in restoring normal motor outputs in chronic survivors (N = 10) by recording electromyographic
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Preliminary Assessment of a Hand and Arm Exoskeleton for Enabling Bimanual Tasks for Individuals With Hemiparesis IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-21 Benjamin W. Gasser; Andrés Martínez; Elizabeth Sasso-Lance; Casey Kandilakis; Christina M. Durrough; Michael Goldfarb
The design and preliminary assessment of a semi-powered hand and arm exoskeleton is described. The exoskeleton is designed to enable bimanual activities of daily living for individuals with chronic, upper-limb hemiparesis resulting from stroke. Specifically, the device augments the user’s grasp strength and ability to extend the affected hand for bimanual tasks and supplements wrist and elbow stability
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Multi-Directional Ankle Impedance During Standing Postures IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-21 Guilherme A. Ribeiro; Lauren N. Knop; Mo Rastgaar
In this study, we estimated the multi-directional ankle mechanical impedance in two degrees-of-freedom (DOF) during standing, and determined how the stiffness, damping, and inertia vary with ankle angle and ankle torque at different postures. Fifteen subjects stood on a vibrating instrumented platform in four stationary postures, while subjected to pulse train perturbations in both the sagittal and
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Characterization of the Time-Varying Nature of Electromechanical Delay During FES-Cycling IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-17 Brendon C. Allen; Kimberly J. Stubbs; Warren E. Dixon
Functional electrical stimulation (FES) induced cycling is a common rehabilitative technique for people with neuromuscular disorders. A challenge for closed-loop FES control is that there exists a potentially destabilizing time-varying input delay, termed electromechanical delay (EMD), between the application of the electric field and the corresponding muscle contraction. In this article, the FES-induced
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Adding Haptic Feedback to Virtual Environments With a Cable-Driven Robot Improves Upper Limb Spatio-Temporal Parameters During a Manual Handling Task IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-02 Céline Faure; Alexis Fortin-Côté; Nicolas Robitaille; Philippe Cardou; Clément Gosselin; Denis Laurendeau; Catherine Mercier; Laurent Bouyer; Bradford J. McFadyen
Physical interactions within virtual environments are often limited to visual information within a restricted workspace. A new system exploiting a cable-driven parallel robot to combine visual and haptic information related to environmental physical constraints (e.g. shelving, object weight) was developed. The aim of this study was to evaluate the impact on user movement patterns of adding haptic feedback
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Portable Gait Lab: Tracking Relative Distances of Feet and CoM Using Three IMUs IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-20 Mohamed Irfan Mohamed Refai; Bert-Jan F. van Beijnum; Jaap H. Buurke; Peter H. Veltink
Ambulatory estimation of gait and balance parameters requires knowledge of relative feet and centre of mass (CoM) positions. Inertial measurement units (IMU) placed on each foot, and on the pelvis are useful in tracking these segments over time, but cannot track the relative distances between these segments. Further, drift due to strapdown inertial navigation results in erroneous relative estimates
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User-Driven Functional Movement Training With a Wearable Hand Robot After Stroke IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-04 Sangwoo Park; Michaela Fraser; Lynne M. Weber; Cassie Meeker; Lauri Bishop; Daniel Geller; Joel Stein; Matei Ciocarlie
We studied the performance of a robotic orthosis designed to assist the paretic hand after stroke. It is wearable and fully user-controlled, serving two possible roles: as a therapeutic tool that facilitates device-mediated hand exercises to recover neuromuscular function or as an assistive device for use in everyday activities to aid functional use of the hand. We present the clinical outcomes of
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Design and Experimental Evaluation of a Semi-Passive Upper-Limb Exoskeleton for Workers With Motorized Tuning of Assistance IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-05 Lorenzo Grazi; Emilio Trigili; Giulio Proface; Francesco Giovacchini; Simona Crea; Nicola Vitiello
This article presents the H-PULSE, a novel semi-passive upper-limb exoskeleton for worker assistance, with motorized tuning of the assistive level. The H-PULSE presents novel design features compared to other passive industrial exoskeletons for the upper limbs, namely joint angle sensors for measuring shoulder flexion/extension and a novel active mechanism for regulating the assistance level. These
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Evaluation of a Simultaneous Myoelectric Control Strategy for a Multi-DoF Transradial Prosthesis IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-17 Cristina Piazza; Matteo Rossi; Manuel G. Catalano; Antonio Bicchi; Levi J. Hargrove
While natural movements result from fluid coordination of multiple joints, commercial upper-limb prostheses are still limited to sequential control of multiple degrees of freedom (DoFs), or constrained to move along predefined patterns. To control multiple DoFs simultaneously, a probability-weighted regression (PWR) method has been proposed and has previously shown good performance with intramuscular
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Stiffness-Optimized Ankle-Foot Orthoses Improve Walking Energy Cost Compared to Conventional Orthoses in Neuromuscular Disorders: A Prospective Uncontrolled Intervention Study IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-24 Niels F. J. Waterval; Merel-Anne Brehm; Viola C. Altmann; Fieke S. Koopman; Jasper J. Den Boer; Jaap Harlaar; Frans Nollet
In persons with calf muscle weakness, walking energy cost is commonly increased due to persistent knee flexion and a diminished push-off. Provided ankle-foot orthoses (AFOs) usually lower walking energy cost. To maximize the reduction in energy cost, AFO bending stiffness should be individually optimized, but this is not common practice. Therefore, we aimed to evaluate whether individually stiffness-optimized
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Toward Predicting Infant Developmental Outcomes From Day-Long Inertial Motion Recordings IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-17 Naomi T. Fitter; Rebecca Funke; José Carlos Pulido; Maja J. Matarić; Beth A. Smith
As improvements in medicine lower infant mortality rates, more infants with neuromotor challenges survive past birth. The motor, social, and cognitive development of these infants are closely interrelated, and challenges in any of these areas can lead to developmental differences. Thus, analyzing one of these domains - the motion of young infants - can yield insights on developmental progress to help
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Region Based Parallel Hierarchy Convolutional Neural Network for Automatic Facial Nerve Paralysis Evaluation IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-03 Xin Liu; Yifan Xia; Hui Yu; Junyu Dong; Muwei Jian; Tuan D. Pham
In this article, we propose a parallel hierarchy convolutional neural network (PHCNN) combining a Long Short-Term Memory (LSTM) network structure to quantitatively assess the grading of facial nerve paralysis (FNP) by considering the region-based asymmetric facial features and temporal variation of the image sequences. FNP, such as Bell’s palsy, is the most common facial symptom of neuromotor dysfunctions
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Dynamic Bayesian Adjustment of Dwell Time for Faster Eye Typing IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-08-14 Jimin Pi; Paul A. Koljonen; Yong Hu; Bertram E. Shi
Eye typing is a hands-free method of human computer interaction, which is especially useful for people with upper limb disabilities. Users select a desired key by gazing at it in an image of a keyboard for a fixed dwell time. There is a tradeoff in selecting the dwell time; shorter dwell times lead to errors due to unintentional selections, while longer dwell times lead to a slow input speed. We propose
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Online Grasp Force Estimation From the Transient EMG IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-07 Itzel Jared Rodríguez Martínez; Andrea Mannini; Francesco Clemente; Christian Cipriani
Myoelectric upper limb prostheses are controlled using information from the electrical activity of residual muscles (i.e. the electromyogram, EMG). EMG patterns at the onset of a contraction (transient phase) have shown predictive information about upcoming grasps. However, decoding this information for the estimation of the grasp force was so far overlooked. In a previous offline study, we proved
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Ieee transactions on neural systems and rehabilitation engineering information for authors IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-10-07
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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Special Issue on Wearable Robotics and Assistive Technology IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-09-09 Daniel P. Ferris; Kara Mcarthur
This special issue highlights some of the best work presented at the 4th International Symposium on Wearable Robotics (WeRob2018), held October 16–20, 2018, in Pisa, Italy. The papers focus on new technologies in the areas of neural interfaces, soft wearable robots, sensor and actuator technologies, and robotic exoskeletons. Based on the quality and significance of presentations at the conference,
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A Backpack Minimizing the Vertical Acceleration of the Load Improves the Economy of Human Walking IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-07-27 Lei He; Caihua Xiong; Qinhao Zhang; Wenbin Chen; Chenglong Fu; Kok-Meng Lee
Loaded walking with a rucksack results in both gravitational and inertial forces of the load that must be borne by human carriers. The inertial force may be the source of metabolic burden and musculoskeletal injuries. This paper presents a lightweight backpack with a disturbance observer-based acceleration control to minimize the inertial force. The backpack was evaluated by seven participants walking
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Modeling of Human Operator Behavior for Brain-Actuated Mobile Robots Steering IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-07-15 Hongqi Li; Luzheng Bi; Haonan Shi
Human operator control of brain-actuated robot steering based on electroencephalograph (EEG)-signals is a complex behavior consisting of surroundings perceiving, decision making, and commands issuing and differs among individual operators. However, no existing models allow decoupling the user from the loop to improve the system design and testing process, which can capture such behavior of a brain-actuated
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Iterative Filtering Decomposition Based Early Dementia Diagnosis Using EEG With Cognitive Tests IEEE Trans. Netural Syst. Rehabil. Eng. (IF 3.34) Pub Date : 2020-07-08 Neelam Sharma; Maheshkumar H. Kolekar; Kamlesh Jha
Objective : There has been a constant increase in life expectancy with the advancement of modern medicine. Likewise, dementia has also increased and projected to elevate in the coming decades with the higher expenditure on healthcare. Consequently, it is essential to identify early dementia, e.g., a patient suffering from mild cognitive impairment who is highly vulnerable to developing dementia soon