A deep convolutional neural network for automated vestibular disorder classification using VNG analysis

ABSTRACT

Dizziness is a frequent syndrome of peripheral vestibular lesions. Identification of nystagmus disorder can be a useful sign to discriminate between diverse vestibular diseases. Through the use of videonystagmography (VNG) device accomplished in the clinical practice of ENT department, the assessment of the rotation eye movement response supplies objective, consistent and precise measurements in the therapeutic scheme. In fact, vestibular dysfunctions introduce an important variety in their features which includes different complications for common VNG examination method. This work introduces a new scheme to reach the classification of eye movement signals from optokinetic and caloric VNG tests. The proposed method offers quantitative assessment and uniform characteristics of recurrent-included disease. The rotation angle of eye movements is classified into two classes of vestibular diseases by the use of deep convolutional Neural Network (CNN) technique. The proposed approach is validated on three different categories: a factual incorporated meniere, neurite and healthy subjects. The employed VNG dataset contain patients admitted into both Charles Nicolle and La Rabta hospitals of Tunis. Compared to previous works, the results demonstrate that the proposed CNN-based method is efficient in enhancing dizziness analysis.

KEYWORDS:

• Nystagmus disorder
• pupil tracking
• vestibular disorder
• VNG database
• convolutional neural networks

Acknowledgments

We are grateful for the professional support of Professor Mamia Ben Salah at Charles Nicolle Hospital of Tunis, who kindly provided our team with a part of data used in this work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Amine Ben Slama

Amine Ben Slama was born in Tunis in 1987 (Tunisia). He is a PhD Doctor in Biophysics and medical imaging and member of research group in Laboratory of biophysics and medical technologies Tunis. His research interests include image and signal processing, classification using deep learning methods for VideoNystamoGraphic (VNG) analysis.

Aymen Mouelhi

Aymen Mouelhi was born in Tunis in 1981 (Tunisia). He received the B.Sc. degree in electrical engineering from the Higher School of Sciences and Techniques of Tunis (ESSTT), the M.Sc. degree in automatic control and the Ph.D. degree in signal and image processing from the same school, respectively in 2003, 2006 and 2014. He is currently an Associate Professor at the Higher Institute of Applied Science and Technology of Mateur and member of research group in Laboratory of Signal Image and Energy Mastery (SIME) at ENSIT - University of Tunis. His research interests include image processing, classification and intelligent data processing for cancer diagnosis.

Hanene Sahli

Hanene Sahli was born in 1988 in Wonfulbutel (Germany). She received the master degree in electrical engineering in 2013 from ENSIT - University of Tunis and she is PhD Student from the same school in signal and image processing and member of research group in Laboratory of Signal Image and Energy Mastery (SIME). Her research interests are focused on adaptive signal processing, classification, segmentation and intelligent techniques for the diagnosis of fetal anomalies detection.

Abderrazek Zeraii

Abderrazek Zeraii was born in Tunis in 1990 (Tunisia). He is a PhD Student in Biophysics and medical imaging and member of research group in Laboratory of biophysics and medical technologies Tunis. His research interests include MRI imaging and signal processing, neuroimaging tools for post stroke prediction.

Jihene Marrakchi

Jihene Marrakchi was born in Tunis. She is hospital-university assistant in La Rabta hospital, department of otorhinolaryngology, She is also expert in Dizziness and vertigo exploration.

Hedi Trabelsi

Hedi Trabelsi born in 1975 in Tunis (Tunisia), he received the B.Sc. degree in Biophysics from the faculty of Sciences of Tunis, He is currently Professor at the higher institute of medical technologies of Tunisia University of Tunis El Manar, member of the Laboratory of biophysics and medical technologies (BMT). Dr. Trabelsi has published over 5 research journal papers. His research interests are focused on diffuse optical Tomography and physics simulation.