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Accepted (AM)Open Access (License Unspecified), Open
Journal article
SIGNAL REGULARITY-BASED AUTOMATED SEIZURE DETECTION SYSTEM FOR SCALP EEG MONITORING1
Cybernetics and systems analysis, v 46(6), pp 922-935
01 Nov 2010
PMID: 21188288
Abstract
The purpose of the present study was to build a clinically useful automated seizure detection system for scalp EEG recordings. To achieve this, a computer algorithm was designed to translate complex multichannel scalp EEG signals into several dynamical descriptors, followed by the investigations of their spatiotemporal properties that relate to the ictal (seizure) EEG patterns as well as to normal physiologic and artifact signals. This paper describes in detail this novel seizure detection algorithm and reports its performance in a large clinical dataset.
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Details
- Title
- SIGNAL REGULARITY-BASED AUTOMATED SEIZURE DETECTION SYSTEM FOR SCALP EEG MONITORING1
- Creators
- Deng-Shan Shiau - Optima NeuroscienceJ. J. Halford - Medical University of South CarolinaK. M. Kelly - Allegheny General HospitalR. T. Kern - Optima NeuroscienceM. Inman - Optima NeuroscienceJui-Hong Chien - Optima NeuroscienceP. M. Pardalos - University of FloridaM. C. K. Yang - University of FloridaJ. Ch Sackellares - Optima Neuroscience
- Publication Details
- Cybernetics and systems analysis, v 46(6), pp 922-935
- Publisher
- Springer Nature
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Neurology
- Web of Science ID
- WOS:000217672900007
- Scopus ID
- 2-s2.0-79952667362
- Other Identifier
- 991019168692304721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Cybernetics
- Mathematics, Interdisciplinary Applications