AIMC Topic: Electroencephalography
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EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN.
BioMed research international
Apr 18, 2017
Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new c...
Learning from label proportions in brain-computer interfaces: Online unsupervised learning with guarantees.
PloS one
Apr 13, 2017
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-tr...
Progress in EEG-Based Brain Robot Interaction Systems.
Computational intelligence and neuroscience
Apr 5, 2017
The most popular noninvasive Brain Robot Interaction (BRI) technology uses the electroencephalogram- (EEG-) based Brain Computer Interface (BCI), to serve as an additional communication channel, for robot control via brainwaves. This technology is pr...
Correlates of sleep quality in midlife and beyond: a machine learning analysis.
Sleep medicine
Mar 27, 2017
OBJECTIVES: In older adults, traditional metrics derived from polysomnography (PSG) are not well correlated with subjective sleep quality. Little is known about whether the association between PSG and subjective sleep quality changes with age, or whe...
Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.
Computer methods and programs in biomedicine
Mar 21, 2017
BACKGROUND AND OBJECTIVE: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must b...
Quantitative EEG for Predicting Upper Limb Motor Recovery in Chronic Stroke Robot-Assisted Rehabilitation.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 3, 2017
Stroke is a leading cause for adult disability, which in many cases causes motor deficits. Despite the developments in motor rehabilitation techniques, recovery of upper limb functions after stroke is limited and heterogeneous in terms of outcomes, a...
Male
Middle Aged
Diagnosis, Computer-Assisted
Robotics
Aged
Aged, 80 and over
Adult
Humans
Sensitivity and Specificity
Reproducibility of Results
Upper Extremity
Stroke Rehabilitation
Electroencephalography
Motion Therapy, Continuous Passive
Equipment Design
Movement Disorders
Stroke
Equipment Failure Analysis
A convolutional neural network for steady state visual evoked potential classification under ambulatory environment.
PloS one
Feb 22, 2017
The robust analysis of neural signals is a challenging problem. Here, we contribute a convolutional neural network (CNN) for the robust classification of a steady-state visual evoked potentials (SSVEPs) paradigm. We measure electroencephalogram (EEG)...
Subject-based discriminative sparse representation model for detection of concealed information.
Computer methods and programs in biomedicine
Feb 20, 2017
BACKGROUND AND OBJECTIVES: The use of machine learning approaches in concealed information test (CIT) plays a key role in the progress of this neurophysiological field. In this paper, we presented a new machine learning method for CIT in which each s...
Diagnostic value of sleep stage dissociation as visualized on a 2-dimensional sleep state space in human narcolepsy.
Journal of neuroscience methods
Feb 20, 2017
BACKGROUND: Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Movement (REM) sleep stage dissociations, occurrences where features of wake and REM sleep are intermingled, resulting in a mixed state. We hypothesized ...
Classifier transfer with data selection strategies for online support vector machine classification with class imbalance.
Journal of neural engineering
Feb 13, 2017
OBJECTIVE: Classifier transfers usually come with dataset shifts. To overcome dataset shifts in practical applications, we consider the limitations in computational resources in this paper for the adaptation of batch learning algorithms, like the sup...
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