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https://www.readbyqxmd.com/read/28431949/classification-of-eeg-signals-to-identify-variations-in-attention-during-motor-task-execution
#1
Susan Aliakbaryhosseinabadi, Ernest Nlandu Kamavuako, Ning Jiang, Dario Farina, Natalie Mrachacz-Kersting
BACKGROUND: Brain-computer interface (BCI) systems in neuro-rehabilitation use brain signals to control external devices. User status such as attention affects BCI performance; thus detecting the user's attention drift due to internal or external factors is essential for high detection accuracy. NEW METHOD: An auditory oddball task was applied to divert the users' attention during a simple ankle dorsiflexion movement. Electroencephalogram signals were recorded from eighteen channels...
April 18, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28420129/hand-motion-detection-in-fnirs-neuroimaging-data
#2
Mohammadreza Abtahi, Amir Mohammad Amiri, Dennis Byrd, Kunal Mankodiya
As the number of people diagnosed with movement disorders is increasing, it becomes vital to design techniques that allow the better understanding of human brain in naturalistic settings. There are many brain imaging methods such as fMRI, SPECT, and MEG that provide the functional information of the brain. However, these techniques have some limitations including immobility, cost, and motion artifacts. One of the most emerging portable brain scanners available today is functional near-infrared spectroscopy (fNIRS)...
April 15, 2017: Healthcare (Basel, Switzerland)
https://www.readbyqxmd.com/read/28410052/robust-averaging-of-covariances-for-eeg-recordings-classification-in-motor-imagery-brain-computer-interfaces
#3
Takashi Uehara, Matteo Sartori, Toshihisa Tanaka, Simone Fiori
The estimation of covariance matrices is of prime importance to analyze the distribution of multivariate signals. In motor imagery-based brain-computer interfaces (MI-BCI), covariance matrices play a central role in the extraction of features from recorded electroencephalograms (EEGs); therefore, correctly estimating covariance is crucial for EEG classification. This letter discusses algorithms to average sample covariance matrices (SCMs) for the selection of the reference matrix in tangent space mapping (TSM)-based MI-BCI...
April 14, 2017: Neural Computation
https://www.readbyqxmd.com/read/28407016/learning-from-label-proportions-in-brain-computer-interfaces-online-unsupervised-learning-with-guarantees
#4
David Hübner, Thibault Verhoeven, Konstantin Schmid, Klaus-Robert Müller, Michael Tangermann, Pieter-Jan Kindermans
OBJECTIVE: Using traditional approaches, a brain-computer interface (BCI) requires the collection of calibration data for new subjects prior to online use. Calibration time can be reduced or eliminated e.g., by subject-to-subject transfer of a pre-trained classifier or unsupervised adaptive classification methods which learn from scratch and adapt over time. While such heuristics work well in practice, none of them can provide theoretical guarantees. Our objective is to modify an event-related potential (ERP) paradigm to work in unison with the machine learning decoder, and thus to achieve a reliable unsupervised calibrationless decoding with a guarantee to recover the true class means...
2017: PloS One
https://www.readbyqxmd.com/read/28406932/a-comparison-of-stimulus-types-in-online-classification-of-the-p300-speller-using-language-models
#5
William Speier, Aniket Deshpande, Lucy Cui, Nand Chandravadia, Dustin Roberts, Nader Pouratian
The P300 Speller is a common brain-computer interface communication system. There are many parallel lines of research underway to overcome the system's low signal to noise ratio and thereby improve performance, including using famous face stimuli and integrating language information into the classifier. While both have been shown separately to provide significant improvements, the two methods have not yet been implemented together to demonstrate that the improvements are complimentary. The goal of this study is therefore twofold...
2017: PloS One
https://www.readbyqxmd.com/read/28393761/enhancing-clinical-communication-assessments-using-an-audiovisual-bci-for-patients-with-disorders-of-consciousness
#6
Fei Wang, Yanbin He, Jun Qu, Qiuyou Xie, Qing Lin, Xiaoxiao Ni, Yan Chen, Steven Laureys, Ronghao Yu, Yuanqing Li
OBJECTIVE: The JFK Coma Recovery Scale-Revised (JFK CRS-R), a behavioral observation scale, is widely used in the clinical diagnosis/assessment of patients with disorders of consciousness (DOC). However, the JFK CRS-R is associated with a high rate of misdiagnosis (approximately 40%) because DOC patients cannot provide sufficient behavioral responses. A brain-computer interface (BCI) that detects command/intention-specific changes in electroencephalography (EEG) signals without the need for behavioral expression may provide an alternative method...
April 10, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28391211/p300-based-asynchronous-brain-computer-interface-for-environmental-control-system
#7
Eda Akman Aydin, Omer Faruk Bay, Inan Guler
An Asynchronous Brain Computer Interface (A-BCI) determines whether or not a subject is on control state, and produces control commands only in case of subject's being on control state. In this study, we propose a novel P300 based A-BCI algorithm that distinguishes control state and non-control state of users. Furthermore, A-BCI algorithm combined with a dynamic stopping function that enables users to select control command independent from a fixed number of intensification sequence. The proposed P300 based A-BCI algorithm uses classification patterns to determine control state and uses optimal operating point of receiver operating characteristics (ROC) curve for dynamic stopping function...
April 4, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28387616/long-term-clinical-and-radiographic-outcomes-of-the-prestige-lp-artificial-cervical-disc-replacement-at-2-levels-results-from-a-prospective-randomized-controlled-clinical-trial
#8
Todd H Lanman, J Kenneth Burkus, Randall G Dryer, Matthew F Gornet, Jeffrey McConnell, Scott D Hodges
OBJECTIVE The aim of this study was to assess long-term clinical safety and effectiveness in patients undergoing anterior cervical surgery using the Prestige LP artificial disc replacement (ADR) prosthesis to treat degenerative cervical spine disease at 2 adjacent levels compared with anterior cervical discectomy and fusion (ACDF). METHODS A prospective, randomized, controlled, multicenter FDA-approved clinical trial was conducted at 30 US centers, comparing the low-profile titanium ceramic composite-based Prestige LP ADR (n = 209) at 2 levels with ACDF (n = 188)...
April 7, 2017: Journal of Neurosurgery. Spine
https://www.readbyqxmd.com/read/28385624/weighted-spatial-based-geometric-scheme-as-an-efficient-algorithm-for-analyzing-single-trial-eegs-to-improve-cue-based-bci-classification
#9
Fatemeh Alimardani, Reza Boostani, Benjamin Blankertz
There is a growing interest in analyzing the geometrical behavior of electroencephalogram (EEG) covariance matrix in the context of brain computer interface (BCI). The bottleneck of the current Riemannian framework is the bias of the mean vector of EEG signals to the noisy trials, which deteriorates the covariance matrix in the manifold space. This study presents a spatial weighting scheme to reduce the effect of noisy trials on the mean vector. To assess the proposed method, dataset IIa from BCI competition IV, containing the EEG trials of 9 subjects performing four mental tasks, was utilized...
March 22, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28379187/a-novel-hybrid-mental-spelling-application-based-on-eye-tracking-and-ssvep-based-bci
#10
Piotr Stawicki, Felix Gembler, Aya Rezeika, Ivan Volosyak
Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users...
April 5, 2017: Brain Sciences
https://www.readbyqxmd.com/read/28376234/adult-mortality-in-a-low-density-tree-population-using-high-resolution-remote-sensing
#11
James R Kellner, Stephen P Hubbell
We developed a statistical framework to quantify mortality rates in canopy trees observed using time series from high-resolution remote sensing. By timing the acquisition of remote sensing data with synchronous annual flowering in the canopy tree species Handroanthus guayacan, we made 2,596 unique detections of 1,006 individual adult trees within 18,883 observation attempts on Barro Colorado Island, Panama (BCI) during an 11-year period. There were 1,057 observation attempts that resulted in missing data due to cloud cover or incomplete spatial coverage...
April 4, 2017: Ecology
https://www.readbyqxmd.com/read/28373984/evaluation-of-a-compact-hybrid-brain-computer-interface-system
#12
Jaeyoung Shin, Klaus-Robert Müller, Christoph H Schmitz, Do-Won Kim, Han-Jeong Hwang
We realized a compact hybrid brain-computer interface (BCI) system by integrating a portable near-infrared spectroscopy (NIRS) device with an economical electroencephalography (EEG) system. The NIRS array was located on the subjects' forehead, covering the prefrontal area. The EEG electrodes were distributed over the frontal, motor/temporal, and parietal areas. The experimental paradigm involved a Stroop word-picture matching test in combination with mental arithmetic (MA) and baseline (BL) tasks, in which the subjects were asked to perform either MA or BL in response to congruent or incongruent conditions, respectively...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28368689/text-entry-rate-of-access-interfaces-used-by-people-with-physical-disabilities-a-systematic-review
#13
Heidi Horstmann Koester, Sajay Arthanat
This study systematically reviewed the research on assistive technology (AT) access interfaces used for text entry, and conducted a quantitative synthesis of text entry rates (TER) associated with common interfaces. We searched 10 databases and included studies in which: typing speed was reported in words per minute (WPM) or equivalent; the access interface was available for public use; and individuals with physical impairments were in the study population. For quantitative synthesis, we used only the TER reported for individuals with physical impairments...
April 3, 2017: Assistive Technology: the Official Journal of RESNA
https://www.readbyqxmd.com/read/28367834/electroencephalographic-identifiers-of-motor-adaptation-learning
#14
Ozan Ozdenizci, Mustafa Yalcin, Ahmetcan Erdogan, Volkan Patoglu, Moritz Grosse-Wentrup, Mujdat Cetin
OBJECTIVE: Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. APPROACH: Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle...
April 3, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28358916/classifying-three-imaginary-states-of-the-same-upper-extremity-using-time-domain-features
#15
Mojgan Tavakolan, Zack Frehlick, Xinyi Yong, Carlo Menon
Brain-computer interface (BCI) allows collaboration between humans and machines. It translates the electrical activity of the brain to understandable commands to operate a machine or a device. In this study, we propose a method to improve the accuracy of a 3-class BCI using electroencephalographic (EEG) signals. This BCI discriminates rest against imaginary grasps and elbow movements of the same limb. This classification task is challenging because imaginary movements within the same limb have close spatial representations on the motor cortex area...
2017: PloS One
https://www.readbyqxmd.com/read/28357991/a-new-multivariate-empirical-mode-decomposition-method-for-improving-the-performance-of-ssvep-based-brain-computer-interface
#16
Yi-Feng Chen, Kiran Atal, Shengquan Xie, Quan Liu
OBJECTIVE: Accurate and efficient detection of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG) is essential for the related brain-computer interface (BCI) applications. APPROACH: Although the canonical correlation analysis (CCA) has been applied extensively and successfully to SSVEP recognition, the spontaneous EEG activities and artifacts that often occur during data recording can deteriorate the recognition performance. Therefore, it is meaningful to extract a few frequency sub-bands of interest to avoid or reduce the influence of unrelated brain activity and artifacts...
March 30, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28348648/regularized-common-spatial-patterns-with-subject-to-subject-transfer-of-eeg-signals
#17
Minmin Cheng, Zuhong Lu, Haixian Wang
In the context of brain-computer interface (BCI) system, the common spatial patterns (CSP) method has been used to extract discriminative spatial filters for the classification of electroencephalogram (EEG) signals. However, the classification performance of CSP typically deteriorates when a few training samples are collected from a new BCI user. In this paper, we propose an approach that maintains or improves the recognition accuracy of the system with only a small size of training data set. The proposed approach is formulated by regularizing the classical CSP technique with the strategy of transfer learning...
April 2017: Cognitive Neurodynamics
https://www.readbyqxmd.com/read/28348527/tuning-up-the-old-brain-with-new-tricks-attention-training-via-neurofeedback
#18
REVIEW
Yang Jiang, Reza Abiri, Xiaopeng Zhao
Neurofeedback (NF) is a form of biofeedback that uses real-time (RT) modulation of brain activity to enhance brain function and behavioral performance. Recent advances in Brain-Computer Interfaces (BCI) and cognitive training (CT) have provided new tools and evidence that NF improves cognitive functions, such as attention and working memory (WM), beyond what is provided by traditional CT. More published studies have demonstrated the efficacy of NF, particularly for treating attention deficit hyperactivity disorder (ADHD) in children...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28346712/comparison-of-three-methods-to-analyze-detrusor-contraction-during-micturition-in-men-over-50-years-of-age
#19
Celine Ten Donkelaar S, Peter Rosier, Laetitia de Kort
AIMS: To grade detrusor voiding contraction three parameters are used: the Schäfer pressure-flow nomogram (LinPURR), the bladder contractility index (BCI) and the maximum Watt factor (Wmax ). Because these methods to quantify detrusor contraction and/or to diagnose detrusor underactivity (DU) have not yet been mutually compared, this study compares these three methods of grading detrusor contraction. MATERIALS AND METHODS: Evaluated were 1420 urodynamic pressure-flow studies from 1222 men (aged >50 years) with lower urinary tract symptoms (LUTS)...
March 27, 2017: Neurourology and Urodynamics
https://www.readbyqxmd.com/read/28343333/use-of-phase-locking-value-in-sensorimotor-rhythm-based-brain-computer-interface-zero-phase-coupling-and-effects-of-spatial-filters
#20
Wenjuan Jian, Minyou Chen, Dennis J McFarland
Phase-locking value (PLV) is a potentially useful feature in sensorimotor rhythm-based brain-computer interface (BCI). However, volume conduction may cause spurious zero-phase coupling between two EEG signals and it is not clear whether PLV effects are independent of spectral amplitude. Volume conduction might be reduced by spatial filtering, but it is uncertain what impact this might have on PLV. Therefore, the goal of this study was to explore whether zero-phase PLV is meaningful and how it is affected by spatial filtering...
March 25, 2017: Medical & Biological Engineering & Computing
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