INNATE: Intelligent Non-invasive Nocturnal epilepsy Assistive TEchnology

Date

2016-01-01

Advisors

Journal Title

Journal ISSN

ISSN

DOI

Volume Title

Publisher

The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp)

Type

Conference

Peer reviewed

Abstract

Epilepsy is a neurological disease that affects the brain and is characterised by repeated seizures. Generalised, focal and unknown are three major types of seizures. Each type has several subgroups. For this reason, seizure detection and classification are expensive and erroneous. Other factors can also affect the detection. For example, patients can have a combination of different seizures or start with one type and finish with another. Nocturnal epilepsy can be prominent in many sufferers of this disease. This displays seizures that occur during the sleep cycle. The nature of such seizures makes the gathering of data and the subsequent detection and classification complex and costly. The current standard for seizure detection is the invasive use of electroencephalogram (EEG) monitoring. Both medical and research communities have expressed a large interest in the detection and classification of seizures automatically and non-invasively. This project proposes the use of 3D computer vision and pattern recognition techniques to detect seizures non-invasively.

Description

Keywords

Epilepsy, Seizure, Kinect 2, Surface normals, PCL

Citation

Malekmohamadi, H., Shell, J. and Coupland, S., (2016) INNATE: Intelligent Non-invasive Nocturnal epilepsy Assistive TEchnology. In Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV) (p. 351). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp).

Rights

Research Institute

Institute of Artificial Intelligence (IAI)