Video-EEG Monitoring Data

2011 ◽  
pp. 67-81
Author(s):  
Elson L. So
Keyword(s):  
Monitoring Data ◽  
Eeg Monitoring ◽  
Video Eeg

scholarly journals DETECTING EVENTS IN VIDEO SEQUENCE OF VIDEO-EEG MONITORING

2019 ◽  
Vol XLII-2/W12 ◽  
pp. 155-159
Author(s):  
D. Murashov ◽  
Y. Obukhov ◽  
I. Kershner ◽  
M. Sinkin
Keyword(s):  
Optical Flow ◽  
Clinical Data ◽  
Video Sequence ◽  
Epileptic Seizures ◽  
Monitoring Data ◽  
Video Sequences ◽  
Eeg Monitoring ◽  
Preliminary Results ◽  
Video Eeg

<p><strong>Abstract.</strong> In this paper, an algorithm for automated detecting diagnostic events in video channel of video and electroencephalographic (EEG) monitoring data is presented. The analysis of video sequences is focused on identifying a group of frames with high or very low (depending on the type of seizure) dynamics of informative areas according to a criterion calculated during processing of the optical flow. The preliminary results of the analysis of real clinical data are given and compared with data obtained from the synchronous EEG. The results showed the possibility in principle of reliable diagnosing epileptic seizures and distinguishing them from non-epileptic events.</p>

A blinded comparison of continuous versus sampled review of video-EEG monitoring data

2011 ◽  
Vol 122 (6) ◽  
pp. 1086-1090 ◽  
Author(s):  
Radwa A.B. Badawy ◽  
Neelan Pillay ◽  
Nathalie Jetté ◽  
Samuel Wiebe ◽  
Paolo Federico
Keyword(s):  
Monitoring Data ◽  
Eeg Monitoring ◽  
Video Eeg

scholarly journals FREQUENCY FEATURES FOR DETECTING EVENTS IN VIDEO SEQUENCE OF VIDEO-EEG MONITORING DATA

2021 ◽  
Vol XLIV-2/W1-2021 ◽  
pp. 163-166
Author(s):  
D. Murashov ◽  
Y. Obukhov ◽  
I. Kershner ◽  
M. Sinkin
Keyword(s):  
Optical Flow ◽  
Clustering Algorithm ◽  
Epileptic Seizures ◽  
Monitoring Data ◽  
Eeg Monitoring ◽  
Video Recordings ◽  
Video Record ◽  
Patients With Epilepsy ◽  
Frequency Features ◽  
Video Eeg

Abstract. The work is devoted to the study of the frequency features of the optical flow obtained from the video record of long-term video-electroencephalographic (video-EEG) monitoring data of patients with epilepsy. It is necessary to obtain features to recognize epileptic seizures and differentiate them from non-epileptic events. We propose to analyze the periodograms of the smoothed optical flow calculated from the fragments of the patient's video recordings. We use Welch's method to obtain periodograms. The values of the power spectral density of the optical flow at the selected frequencies will be used as features. Using the clustering algorithm, four groups of events were identified in video recordings.

THE DIAGNOSTIC UTILITY OF INPATIENT VIDEO-EEG MONITORING IN PEDIATRICS

2006 ◽  
Vol 37 (S 1) ◽  
Author(s):  
A Abdelmoity ◽  
W Graf ◽  
H Tsoi ◽  
M Wise
Keyword(s):  
Diagnostic Utility ◽  
Eeg Monitoring ◽  
Video Eeg

Psychiatric and cognitive characteristics of older adults admitted to a Video-EEG monitoring (VEM) unit

2021 ◽  
Vol 120 ◽  
pp. 107987
Author(s):  
Anthony Hew ◽  
Michael Lloyd ◽  
Genevieve Rayner ◽  
Alice Matson ◽  
Maria Rychkova ◽  
...  
Keyword(s):  
Older Adults ◽  
Eeg Monitoring ◽  
Cognitive Characteristics ◽  
Video Eeg

Affect in patients with epilepsy undergoing video/EEG monitoring: Retrospective versus momentary assessment and temporal relationship to seizures

2006 ◽  
Vol 8 (3) ◽  
pp. 625-634 ◽  
Author(s):  
Kristen S. Willard ◽  
Barbara G. Licht ◽  
Robin L. Gilmore ◽  
Mark H. Licht ◽  
J. Chris Sackellares ◽  
...  
Keyword(s):  
Temporal Relationship ◽  
Eeg Monitoring ◽  
Patients With Epilepsy ◽  
Momentary Assessment ◽  
Video Eeg

Skin Irritation during Video-EEG Monitoring

2016 ◽  
Vol 56 (3) ◽  
pp. 139-150 ◽  
Author(s):  
Cornelia Drees ◽  
Mary Beth Makic ◽  
Kristen Case ◽  
Mary P. Mancuso ◽  
Annette Hill ◽  
...  
Keyword(s):  
Skin Irritation ◽  
Eeg Monitoring ◽  
Video Eeg
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