IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Aug 30, 2016
Over the past decade, with the development of machine learning, discrete wavelet transform (DWT) has been widely used in computer-aided epileptic electroencephalography (EEG) signal analysis as a powerful time-frequency tool. But some important probl...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Aug 25, 2016
In this paper, we present the design, fabrication and evaluation of a soft wearable robotic glove, which can be used with functional Magnetic Resonance imaging (fMRI) during the hand rehabilitation and task specific training. The soft wearable roboti...
Neuromorphic computing covers a diverse range of approaches to information processing all of which demonstrate some degree of neurobiological inspiration that differentiates them from mainstream conventional computing systems. The philosophy behind n...
MOTIVATION: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders with clinical heterogeneity and a substantial polygenic component. High-throughput methods for ASD risk gene identification produce numerous candidate genes that ...
Gamma-aminobutyric acid type-A receptors (GABAARs) belong to multisubunit membrane spanning ligand-gated ion channels (LGICs) which act as the principal mediators of rapid inhibitory synaptic transmission in the human brain. Therefore, the category p...
The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme lea...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Aug 3, 2016
The efficient control of our body and successful interaction with the environment are possible through the integration of multisensory information. Brain-computer interface (BCI) may allow people with sensorimotor disorders to actively interact in th...
Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine ...
BACKGROUND: Growing evidence documents the potential of machine learning for developing brain based diagnostic methods for major depressive disorder (MDD). As symptom severity may influence brain activity, we investigated whether the severity of MDD ...
Longitudinal designs are widely used in medical studies as a means of observing within-subject changes over time in groups of subjects, thereby aiming to improve sensitivity for detecting disease effects. Paralleling an increased use of such studies ...
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