Literature DB >> 7686477

An automated seizure monitoring system for patients with indwelling recording electrodes.

G W Harding1.   

Abstract

An automated monitoring system has been developed to record from indwelling electrode arrays in patients undergoing evaluation for surgical treatment of intractable seizures. The functional aspects of this system's design are discussed and the range of electrical seizure patterns, other epileptiform events and artifacts that the system must handle are described. The system includes a flowing graphics image of as many as 32 channels of real-time ECoG, automatic seizure detection, recording of the ECoG for up to 6 min prior to seizure onset, and EEG for 792 clinical and subclinical seizures during 1578 h of monitoring with an artifact rate of 28% for all events recorded. However, system performance was judged upon the 86% accuracy for detection and recording of patient-specific seizure patterns (multiple seizures with the same pattern counted as 1) with 1.26 brief spike bursts and 0.67 artifacts/h.

Entities:  

Mesh:

Year:  1993        PMID: 7686477     DOI: 10.1016/0013-4694(93)90138-l

Source DB:  PubMed          Journal:  Electroencephalogr Clin Neurophysiol        ISSN: 0013-4694


  5 in total

1.  SIGNAL REGULARITY-BASED AUTOMATED SEIZURE DETECTION SYSTEM FOR SCALP EEG MONITORING.

Authors:  Deng-Shan Shiau; J J Halford; K M Kelly; R T Kern; M Inman; Jui-Hong Chien; P M Pardalos; M C K Yang; J Ch Sackellares
Journal:  Cybern Syst Anal       Date:  2010-11-01

Review 2.  Seizure detection: do current devices work? And when can they be useful?

Authors:  Xiuhe Zhao; Samden D Lhatoo
Journal:  Curr Neurol Neurosci Rep       Date:  2018-05-23       Impact factor: 5.081

3.  Feature extraction and recognition of epileptiform activity in EEG by combining PCA with ApEn.

Authors:  Chunmei Wang; Junzhong Zou; Jian Zhang; Min Wang; Rubin Wang
Journal:  Cogn Neurodyn       Date:  2010-06-26       Impact factor: 5.082

4.  Automatic seizure detection based on time-frequency analysis and artificial neural networks.

Authors:  A T Tzallas; M G Tsipouras; D I Fotiadis
Journal:  Comput Intell Neurosci       Date:  2007

5.  Classification of Normal, Ictal and Inter-ictal EEG via Direct Quadrature and Random Forest Tree.

Authors:  Enas Abdulhay; Maha Alafeef; Arwa Abdelhay; Areen Al-Bashir
Journal:  J Med Biol Eng       Date:  2017-06-19       Impact factor: 1.553

  5 in total

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