scholarly journals Digital Semiology: A Prototype for Standardized, Computer-Based Semiologic Encoding of Seizures

2021 ◽  
Vol 12 ◽  
Author(s):  
Tal Benoliel ◽  
Tal Gilboa ◽  
Paz Har-Shai Yahav ◽  
Revital Zelker ◽  
Bilha Kreigsberg ◽  
...  
Keyword(s):  
Behavioral Characteristics ◽  
Treatment Gap ◽  
Video Recordings ◽  
Standardized Report ◽  
Presurgical Assessment ◽  
Computer Based ◽  
Added Benefit ◽  
Pilot Feasibility Study ◽  
Seizure Classification ◽  
Video Eeg

Video-EEG monitoring (VEM) is imperative in seizure classification and presurgical assessment of epilepsy patients. Analysis of VEM is currently performed in most institutions using a freeform report, a time-consuming process resulting in a non-standardized report, limiting the use of this essential diagnostic tool. Herein we present a pilot feasibility study of our experience with “Digital Semiology” (DS), a novel seizure encoding software. It allows semiautomated annotation of the videos of suspected events from a predetermined, hierarchal set of options, with highly detailed semiologic descriptions, somatic localization, and timing. In addition, the software's semiologic extrapolation functions identify characteristics of focal seizures and PNES, sequences compatible with a Jacksonian march, and risk factors for SUDEP. Sixty episodes from a mixed adult and pediatric cohort from one level 4 epilepsy center VEM archives were analyzed using DS and the reports were compared with the standard freeform ones, written by the same epileptologists. The behavioral characteristics appearing in the DS and freeform reports overlapped by 78–80%. Encoding of one episode using DS required an average of 18 min 13 s (standard deviation: 14 min and 16 s). The focality function identified 19 out of 43 focal episodes, with a sensitivity of 45.45% (CI 30.39–61.15%) and specificity of 87.50% (CI 61.65–98.45%). The PNES function identified 6 of 12 PNES episodes, with a sensitivity of 50% (95% CI 21.09–78.91%) and specificity of 97.2 (95% CI 88.93–99.95%). Eleven events of GTCS triggered the SUDEP risk alert. Overall, these results show that video recordings of suspected seizures can be encoded using the DS software in a precise manner, offering the added benefit of semiologic alerts. The present study represents an important step toward the formation of an annotated video archive, to be used for machine learning purposes. This will further the goal of automated VEM analysis, ultimately contributing to wider utilization of VEM and therefore to the reduction of the treatment gap in epilepsy.

Simulation in ENT medical education

2009 ◽  
Vol 124 (3) ◽  
pp. 237-241 ◽  
Author(s):  
K-E A Abou-Elhamd ◽  
A I Al-Sultan ◽  
U M Rashad
Keyword(s):  
Medical Education ◽  
Physical Models ◽  
Sinus Surgery ◽  
Medical Simulation ◽  
Bone Surgery ◽  
Surgery Training ◽  
Video Recordings ◽  
Temporal Bone Surgery ◽  
Computer Based ◽  
Surgery Simulator

AbstractObjectives:Computer-based medical simulation has recently been adopted as a new method of medical education. This paper reviews the uses of medical simulation within the ENT specialty, and reports how such simulation is used in Al-Ahsa College of Medicine, Saudi Arabia.Methods:We review our use of a simulation laboratory in ENT training. Students are taught ENT anatomy using physical models, ear diseases using physical models, and ENT examination by watching video recordings, and are taught the principles of common ENT surgery using a computerised mannequin (for laryngoscopy and bronchoscopy). A haptic temporal bone surgery simulator is used for mastoidectomy and functional endoscopic sinus surgery training, and a mannequin for cricothyrotomy and tracheotomy training.Conclusion:The use of such simulation methods has greatly improved our students' perception and comprehension.

Mental Fatigue: Impairment of Technical Performance in Small-Sided Soccer Games

2016 ◽  
Vol 11 (8) ◽  
pp. 1100-1105 ◽  
Author(s):  
Oliver O. Badin ◽  
Mitchell R. Smith ◽  
Daniele Conte ◽  
Aaron J. Coutts
Keyword(s):  
Physical Performance ◽  
Stroop Task ◽  
Perceived Exertion ◽  
Mental Fatigue ◽  
Subjective Ratings ◽  
Performance Variables ◽  
Technical Performance ◽  
Video Recordings ◽  
Before And After ◽  
Computer Based

Purpose:To assess the effects of mental fatigue on physical and technical performance in small-sided soccer games. Methods:Twenty soccer players (age 17.8 ± 1.0 y, height 179 ± 5 cm, body mass 72.4 ± 6.8 kg, playing experience 8.3 ± 1.4 y) from an Australian National Premier League soccer club volunteered to participate in this randomized crossover investigation. Participants played 15-min 5-vs-5 small-sided games (SSGs) without goalkeepers on 2 occasions separated by 1 wk. Before the SSG, 1 team watched a 30-min emotionally neutral documentary (control), while the other performed 30 min of a computer-based Stroop task (mental fatigue). Subjective ratings of mental and physical fatigue were recorded before and after treatment and after the SSG. Motivation was assessed before treatment and SSG; mental effort was assessed after treatment and SSG. Player activity profiles and heart rate (HR) were measured throughout the SSG, whereas ratings of perceived exertion (RPEs) were recorded before the SSG and immediately after each half. Video recordings of the SSG allowed for notational analysis of technical variables. Results:Subjective ratings of mental fatigue and effort were higher after the Stroop task, whereas motivation for the upcoming SSG was similar between conditions. HR during the SSG was possibly higher in the control condition, whereas RPE was likely higher in the mental-fatigue condition. Mental fatigue had an unclear effect on most physical-performance variables but impaired most technical-performance variables. Conclusions:Mental fatigue impairs technical but not physical performance in small-sided soccer games.

Anchoring Problem-Solving and Computation Instruction in Context-Rich Learning Environments

2010 ◽  
Vol 76 (4) ◽  
pp. 417-437 ◽  
Author(s):  
Brian A. Bottge ◽  
Enrique Rueda ◽  
Timothy S. Grant ◽  
Ana C. Stephens ◽  
Perry T. Laroque
Keyword(s):  
Problem Solving ◽  
Middle School Students ◽  
Students With Learning Disabilities ◽  
School Students ◽  
Problem Solving Skills ◽  
Formal Instruction ◽  
Fraction Instruction ◽  
Computer Based ◽  
Added Benefit ◽  
Instructional Formats

Middle school students with learning disabilities in math (MLD) used two versions of Enhanced Anchored Instruction (EAI). In one condition, students learned how to compute with fractions on an as-needed basis while they worked to solve the EAI problems. In the other condition, teachers used a computer-based instructional module in place of one of the EAI problems to deliver formal fraction instruction. The results indicated that students in both instructional formats improved their fraction computational skills and that formal instruction provided an added benefit. Both instructional conditions improved students' problem-solving skills by about the same amount. The findings suggest that combining formal fraction instruction with EAI is a viable way to improve the problem-solving and computational skills of students with MLD.

Mapping of Seizure Networks

2018 ◽  
pp. 511-519
Author(s):  
Olivier David
Keyword(s):  
Data Analysis ◽  
Focal Epilepsy ◽  
Seizure Onset ◽  
High Frequency Oscillations ◽  
Signal Features ◽  
Seizure Onset Zone ◽  
Presurgical Assessment ◽  
Computer Based ◽  
Intracranial Electroencephalography ◽  
Quantitative Neuroimaging

Intracranial electroencephalography (iEEG) is used to localize the seizure onset zone (SOZ) and connected neuronal networks in surgical candidates suffering from intractable focal epilepsy. Identification of the SOZ is usually based on visual inspection of iEEG signals, but new computer-based quantitative iEEG analyses are being developed to improve and expedite SOZ detection. Two main questions arise. First, which signal features are the best proxys to identify the SOZ and the propagation pathways constituting epileptic networks? Second, how can the results of data analysis be represented in a clinically useful and meaningful manner? This chapter adopts an epileptogenicity mapping approach based on maps of ictal high-frequency oscillations superimposed on neuroanatomy and illustrates the main concepts underlying mapping of seizure networks. Future quantitative iEEG approaches should complete and operationalize understanding of seizure networks. Quantitative neuroimaging of iEEG features of seizures should help provide better presurgical assessment of patients undergoing resective surgery.

Comparison of VHS video recording system with Apple Macintosh-based image analysis and modified CODA-3 systems in equine motion analysis

2002 ◽  
Vol 50 (2) ◽  
pp. 167-176 ◽  
Author(s):  
F. Szalay ◽  
W. Back ◽  
A. Barneveld ◽  
Keyword(s):  
Image Analysis ◽  
Motion Analysis ◽  
High Speed ◽  
Sampling Rate ◽  
Video Recording ◽  
Lateral View ◽  
Video Recordings ◽  
Artificial Illumination ◽  
Computer Based ◽  
Analysis System

A VHS video - computer-based image analysis combination is described as a low sampling rate motion analysis system. Video recordings were taken indoor without any artificial illumination at 25 fps sampling rate. The horse studied was running on a high-speed treadmill and observed at 1.6, 4 and 7 m/s velocities at walk, trot and canter, respectively. Left forelimb and hindlimb were recorded separately from lateral view. For comparison, parallel CODA-3 recordings were taken at the same time from the same position. Joint angles were expressed and compared in angle-time diagrams. Sampling of both systems has been synchronised by a timer device at ± 1/300 s error level. Results obtained with the two different recording systems were comparable in all joints measured with the exception of the fetlock. Inaccuracies in fetlock recordings are thought to be eliminated by measuring at controlled illumination. As a conclusion, the VHS-Macintosh setup appears to be promising as a simplified system for gait analysis.

Semiological Seizure Classification: Before and After Video-EEG Monitoring of Seizures

2007 ◽  
Vol 36 (4) ◽  
pp. 231-235 ◽  
Author(s):  
Tugba Hirfanoglu ◽  
Ayse Serdaroglu ◽  
Ali Cansu ◽  
Erhan Bilir ◽  
Kivilcim Gucuyener
Keyword(s):  
Eeg Monitoring ◽  
Before And After ◽  
Seizure Classification ◽  
Video Eeg

scholarly journals Identification of fidgety movements and prediction of CP by the use of computer-based video analysis is more accurate when based on two video recordings

2013 ◽  
Vol 29 (6) ◽  
pp. 469-475 ◽  
Author(s):  
Lars Adde ◽  
Jorunn Helbostad ◽  
Alexander R. Jensenius ◽  
Mette Langaas ◽  
Ragnhild Støen
Keyword(s):  
Video Analysis ◽  
Video Recordings ◽  
Computer Based

Innovations in unobtrusive methods

2018 ◽  
Author(s):  
Andrew P. Knight
Keyword(s):  
Ethical Issues ◽  
Low Cost ◽  
Wearable Sensors ◽  
The Public ◽  
Video Recordings ◽  
Personal Archives ◽  
Computer Based ◽  
Online Access ◽  
Automatic Coding ◽  
Wide Dissemination

Andrew P. Knight explores developments in unobtrusive research methods using unconventional sources of data from computer-based systems and tools. These generate novel measures of behaviour based on the digital trace data that we all generate, online access to public and personal archives, wearable sensors, and the automatic coding of text, and audio and video recordings. Smartphones and wristbands are just two of the growing range of connected devices that are capable of capturing and sharing multimedia information in real-time. Devices such as these offer new ways in which researchers can gather data at low cost, avoiding reactance effects, allowing the study of how phenomena change over time, and expanding the scale of research, given the wide dissemination of the technology. Before adopting these methods, researchers need to consider whether they have the expertise, and the ethical issues raised by using information (which may be in the public domain) without informed consent.

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.

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