A novel robotic mirror therapy system was recently developed to provide proprioceptive stimulus to the hemiplegic arm during a mirror therapy. Validation of the robotic mirror therapy system was performed to confirm its synchronicity prior to the cli...
Diagnosis of autism spectrum disorder (ASD) currently relies on behavioral observations because brain markers are unknown. Machine learning approaches can identify patterns in imaging data that predict diagnostic status, but most studies using functi...
BACKGROUND: Current computational neuroanatomy focuses on morphological measurements of the brain using standard magnetic resonance imaging (MRI) techniques. In comparison quantitative MRI (qMRI) typically provides a better tissue contrast and also g...
OBJECTIVE: Many computer vision and robotic applications require the implementation of robust and efficient target-tracking algorithms on a moving platform. However, deployment of a real-time system is challenging, even with the computational power o...
Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest. Deep learning-based segmentation approaches for brain MRI are gaining interest due to their sel...
OBJECTIVE: Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use ...
OBJECTIVE: Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However,...
Technology and health care : official journal of the European Society for Engineering and Medicine
Jul 20, 2017
This paper presents a pattern recognition model using multiple features and the kernel extreme learning machine (ELM), improving the accuracy of automatic epilepsy diagnosis. After simple preprocessing, temporal- and wavelet-based features are extrac...
The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better ...
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