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IEEE Transactions on Neural Systems and Rehabilitation Engineering

Kurt A Kaczmarek, Mitchell E Tyler, Uchechukwu O Okpara, Steven J Haase
Sensations elicited by electrical stimulation of touch are multidimensional, varying in perceived intensity and quality in response to changes in stimulus current or waveform timing. This study manipulated both current and frequency while volunteer participants estimated the dissimilarity of all nonidentical pairs of 16 stimulus conditions. Multidimensional scaling analysis revealed that a model having two perceptual dimensions was adequate in representing the electrotactile (electrocutaneous) sensations. The two dimensions were identified as perceptual frequency and intensity, and were strongly correlated with the two stimulus variables, frequency and current, although not in a 1:1 correspondence...
May 12, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Kai Gui, Honghai Liu, Dingguo Zhang
Robotic exoskeletons for physical rehabilitation have been utilized for retraining patients suffering from paraplegia and enhancing motor recovery in recent years. However, users are not voluntarily involved in most systems. This work aims to develop a locomotion trainer with multiple gait patterns, which can be controlled by the active motion intention of users. A multimodal human-robot interaction (HRI) system is established to enhance subject's active participation during gait rehabilitation, which includes cognitive human-robot interaction (cHRI) and physical human-robot interaction (pHRI)...
May 11, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Andrea Crema, Nebojsa Malesevic, Ivan Furfaro, Flavio Raschella, Alessandra Pedrocchi, Silvestro Micera
Reaching and grasping impairments significantly affect the quality of life for people who have experienced a stroke or spinal cord injury (SCI). The long-term well-being of patients varies greatly according to the restorable residual capabilities. Electrical stimulation could be a promising solution to restore motor functions in these conditions, but its use is not clinically widespread.
May 10, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Edwin Johnatan Avila Mireles, Jacopo Zenzeri, Velentina Squeri, Pietro Morasso, Dalia De Santis
It is known that physical coupling between two subjects may be advantageous in joint tasks. However, little is known about how two people mutually exchange information to exploit the coupling. Therefore we adopted a reversed, novel perspective to the standard one that focuses on the ability of physically coupled subjects to adapt to cooperative contexts that require negotiating a common plan: we investigated how training in pairs on a novel task affects the development of motor skills of each of the interacting partners...
May 8, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Xiaoli Guo, Zixuan Lin, Yuanyuan Lyu, Robin Bekrater-Bodmann, Herta Flor, Shanbao Tong
Amputation of a limb induces changes in the so-called body schema, which might be influenced by the use of prosthetic devices. Changes in the body representation associated with prosthesis use could be investigated using a hand mental rotation task. However, direct neurophysiologic evidence for the effect of prosthesis use on hand mental rotation is still lacking. In this study, we recruited two groups of unilateral upper-limb amputees, i.e., amputees using a prosthesis or with a history of prosthesis use (Pro group) and amputees without a prosthesis (non-Pro group), as well as a sample of matched healthy controls...
May 8, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Renato Watanabe, Andre Kohn
Corticomotor coherence in the beta and/or gamma bands has been described in different motor tasks but the role of descending brain oscillations on force control has been elusive. Large-scale computational models of a motoneuron pool and the muscle it innervates have been used as tools to advance the knowledge of how neural elements may influence force control. Here we present a frequency domain analysis of a NARX model fitted to a large-scale neuromuscular model by means of generalized frequency response functions (GFRF)...
May 4, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Georgios Dimitrakopoulos, Ioannis Kakkos, Zhongxiang Dai, Julian Lim, Joshua deSouza, Anastasios Bezerianos, Yu Sun
Efficient classification of mental workload, an important issue in neuroscience, is limited so far to single task, while cross-task classification remains a challenge. Furthermore, network approaches have emerged as a promising direction for studying the complex organization of the brain, enabling easier interpretation of various mental states. In this study, using two mental tasks (N-back and mental arithmetic), we present a framework for cross- as well as within-task workload discrimination by utilizing multiband EEG cortical brain connectivity...
May 4, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
J Roussel, P Ravier, M Haritopoulos, D Farina, O Buttelli
We propose a novel decomposition method for electromyographic (EMG) signals based on blind source separation. Using the cyclostationary properties of motor unit action potential trains (MUAPt), it is shown that MUAPt can be decomposed by joint diagonalization of the cyclic spatial correlation matrix of the observations. After modeling of the source signals, we provide the proof of orthogonality of the sources and of their delayed versions in a cyclostationary context. We tested the proposed method on simulated signals and showed that it can decompose up to 6 sources with a probability of correct detection and classification >95%, using only 8 recording sites...
May 3, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Kathleen Jagodnik, Philip Thomas, Antonie van den Bogert, Michael Branicky, Robert Kirsch
Functional Electrical Stimulation (FES) employs neuroprostheses to apply electrical current to the nerves and muscles of individuals paralyzed by spinal cord injury (SCI) to restore voluntary movement. Neuroprosthesis controllers calculate stimulation patterns to produce desired actions. To date, no existing controller is able to efficiently adapt its control strategy to the wide range of possible physiological arm characteristics, reaching movements, and user preferences that vary over time. Reinforcement learning (RL) is a control strategy that can incorporate human reward signals as inputs to allow human users to shape controller behavior...
May 2, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Qasem Obeidat, Tom Campbell, Jun Kong
Research into Brain-Computer Interfaces (BCIs), which spell words using brain signals, has revealed that a desktop version of such a speller, the edges paradigm, offers several advantages: This edges paradigm outperforms the benchmark row-column paradigm in terms of accuracy, bitrate, and user experience. It has remained unknown whether these advantages prevailed with a new version of the edges paradigm designed for a mobile device. This paper investigated and evaluated in a rolling wheelchair a mobile BCI, which implemented the edges paradigm on small displays with which visual crowding tends to occur...
May 2, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Yulin Zhu, Jiang Wang, Huiyan Li, Bin Deng, Chen Liu
Parkinson's disease (PD) is a degenerative disorder of central nervous system that endangers the olds' health seriously. The motor symptoms of PD can be attributed to the distorted relay reliability of thalamus to cortical sensorimotor input that results from the increase of inhibitory input from internal segment of the globus pallidum (GPi). Based on this, we construct the GPithalamocortical computational model to generate the normal and pathological firing patterns by varying GPi spike train input. A kind of closed-loop deep brain stimulation (DBS) strategy is proposed here...
May 2, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Jeffrey Lee, Luke Mooney, Elliott Rouse
The majority of commercially available passive prosthetic feet are not capable of providing joint mechanics that match that of the intact human ankle. Due to their cantilever design, their stiffness characteristics contrast with what has been observed in the biological ankle; namely, an increase in stiffness during the stance phase of walking. In this study, we introduce the design and control of a pneumatic foot-ankle prosthesis that attempts to provide biomimetic mechanics. The prosthesis is comprised of a pneumatic cylinder in series with a fiberglass leaf spring, and a solenoid valve to control the flow of air between the two sides of the cylinder...
April 28, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Dongrui Wu, Brent J Lance, Vernon J Lawhern, Stephen Gordon, Tzyy-Ping Jung, Chin-Teng Lin
Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI applications. More specifically, we propose a new feature extraction approach for EEG-based BCI regression problems: a spatial filter is first used to increase the signal quality of the EEG trials and also to reduce the dimensionality of the covariance matrices, and then Riemannian tangent space features are extracted...
April 28, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Nora Millor, Pablo Lecumberri, Marisol Gomez, Alicia Martinez-Ramirez, Ion Martinikorena, Leocadio Rodriguez-Manas, Francisco Garcia Garcia, Mikel Izquierdo
Frailty is characterized by a loss of functionality and is expected to affect 9.9% of people aged 65 and over. Here, current frailty classification is compared to a collection of selected kinematic parameters. A total of 718 elderly subjects (319 males and 399 females; age: 75.4 ± 6.1 years), volunteered to participate in this study and were classified according to Fried´s criteria. Both the 30-s chair stand test (CST) and the 3-m walking test were performed and a set of kinematic parameters were obtained from a single inertial unit...
April 27, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Joaquin Ballesteros, Cristina Urdiales, Antonio B Martinez, Marina Tirado Reyes
Patient condition during rehabilitation has been traditionally assessed using clinical scales. These scales typically require the patient and/or the clinician to rate a number of condition related items to obtain a final score. This is a timeconsuming task, specially if a large number of patients is involved. Furthermore, during rehabilitation, user condition is expected to change steadily in time, so assessment may require to run these scales several times to each user. To save time, much effort has been focused on developing clinical scales that require little time to be completed...
April 25, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Lasitha S Vidyaratne, Khan M Iftekharuddin
This work proposes a novel patient-specific real-time automatic epileptic seizure onset detection, using both scalp and intracranial EEG. The proposed technique obtains harmonic multiresolution and self-similarity-based fractal features from EEG for robust seizure onset detection. A fast wavelet decomposition method, known as harmonic wavelet packet transform (HWPT), is computed based on Fourier transform to achieve higher frequency resolutions without recursive calculations. Similarly, fractal dimension (FD) estimates are obtained to capture self-similar repetitive patterns in the EEG signal...
April 25, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Alexander Maye, Dan Zhang, Andreas Engel
In Brain Computer Interfaces (BCIs) that use the steady-state visual evoked response (SSVEP), the user selects a control command by directing attention overtly or covertly to one out of several flicker stimuli. The different control channels are encoded in the frequency, phase or time domain of the flicker signals. Here we present a new type of SSVEP BCI which uses only a single flicker stimulus and yet affords controlling multiple channels. The approach rests on the observation that the relative position between the stimulus and the foci of overt attention result in distinct topographies of the SSVEP response on the scalp...
April 25, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Jongkil Park, Gookhwa Kim, Sang-Don Jung
A multichannel neural interface system is an important tool for various types of neuroscientific studies. For the electrical interface with a biological system, high-precision highspeed data recording and various types of stimulation capability are required. In addition, real-time signal processing is an important feature in the implementation of a real-time closed-loop system without unwanted substantial delay for feedback stimulation. Online spike sorting, the process of assigning neural spikes to an identified group of neurons or clusters, is a necessary step to make a closed-loop path in real time, but massive memory-space requirements commonly limit hardware implementations...
April 24, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Radhika Menon, Gaetano Di Caterina, Heba Lakany, Lykourgos Petropoulakis, Bernard Conway, John Soraghan
Advanced forearm prosthetic devices employ classifiers to recognize different electromyography (EMG) signal patterns, in order to identify the user's intended motion gesture. The classification accuracy is one of the main determinants of real-time controllability of a prosthetic limb and hence the necessity to achieve as high an accuracy as possible. In this paper, we study the effects of the temporal and spatial information provided to the classifier on its offline performance and analyze their inter-dependencies...
April 19, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Ji Chen, Diane Nichols, Elizabeth B Brokaw, Peter S Lum
In previous work, we developed a lightweight wearable hand exoskeleton (HandSOME) that improves range of motion and function in laboratory testing. In this pilot study, we added the ability to log movement data for extended periods and recruited 10 chronic stroke subjects to use the device during reach and grasp task practice at home for 1.5 hours/day, 5 days per week, for 4 weeks. Seven subjects completed the study, performing 448 ± 651 hand movements per training day. After training, impairment was reduced (Fugl-Meyer Test; gain=4...
April 18, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
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