Neural networks : the official journal of the International Neural Network Society
Jun 25, 2020
Electroencephalogram (EEG) signals accumulate the brain's spiking activities using standardized electrodes placed at the scalp. These cumulative brain signals are chaotic in nature and vary depending upon current physical and/or mental activities. Th...
IEEE transactions on biomedical circuits and systems
Jun 24, 2020
Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique dec...
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disease characterized by intracellular α-synuclein (α-Syn) deposition. Alternation of the α-Syn expression level in plasma or erythrocytes may be used as a potential PD biomarker. However, n...
Glioblastoma is a heterogeneous lethal disease, regulated by a stem-cell hierarchy and the neurotransmitter microenvironment. The identification of chemotherapies targeting individual cancer stem cells is a clinical need. A robotic workstation was ...
BACKGROUND: Manual annotation of initial contact (IC) and end contact (EC) is a time consuming process. There are currently no robust techniques available to automate this process for Parkinson's disease (PD) patients with freezing of gait (FOG).
This note describes the development of a mixed-reality assistive robotic wheel chair simulator for testing of Parkinson's tremor mitigation and operator assistance. It consists of a power chair (PCh), roller dynamometer, head mounted virtual reality ...
PURPOSE: The aim of the study was to assess the feasibility of an approach combining computational methods and pharmacoepidemiology to identify potentially disease-modifying drugs in Parkinson's disease (PD).
BACKGROUND: Parkinson's disease is one of the most frequent causes of disability among the older adults. It is a chronic-progressive neuro-degenerative disease, characterized by several motor disorders. Balance disorders are a symptom that involves t...
This paper proposes two new data augmentation approaches based on Deep Convolutional Generative Adversarial Networks (DCGANs) and Style Transfer for augmenting Parkinson's Disease (PD) electromyography (EMG) signals. The experimental results indicate...
BACKGROUND: Parkinson's disease (PD) ranks as the second most frequently occurring neurodegenerative disease. The precise pathogenic mechanism of this disease remains unknown. The aim of the present study was to identify the biomarkers in PD and clas...
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