1D Convolutional Neural Networks for Detecting Nystagmus

Vertigo is a type of dizziness characterised by the subjective feeling of movement despite being stationary. One in four individuals in the community experience symptoms of dizziness at any given time, and it can be challenging for clinicians to diagnose the underlying cause. When dizziness is the r...

Full description

Bibliographic Details
Main Authors:	Cox, S.J (Author), Newman, J.L (Author), Phillips, J.S (Author)
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:	1D convolutional neural networks accuracy action potential Article artificial intelligence biomedical signal processing caloric vestibular test Clinical investigation convolutional neural network Convolutional neural networks data visualization Deep neural networks Degree of accuracy dizziness electroencephalography electronystagmography electrooculography entropy eye movement Eye movements Eye Movements F1 scores heart arrhythmia human Humans inner ear learning algorithm machine learning Medical computing Medical Devices Meniere disease Meniere Disease Network architecture Neural Networks, Computer nystagmus Nystagmus, Pathologic Occupational diseases optokinetic nystagmus Recording head sensitivity and specificity signal noise ratio support vector machine time series classification training Training data Training network Underlying cause validation process vertigo Vertigo vestibular diseases
Online Access:	View Fulltext in Publisher

Internet

View Fulltext in Publisher

1D Convolutional Neural Networks for Detecting Nystagmus

Internet

Similar Items