Literature DB >> 8631278

Spike detection. I. Correlation and reliability of human experts.

S B Wilson1, R N Harner, F H Duffy, B R Tharp, M R Nuwer, M R Sperling.   

Abstract

A panel of 5 experienced electroencephalographers detected spikes in EEG trials from 40 epilepsy patients and 10 control subjects. 1952 spikes were detected, and detailed attribute scores were recorded. Statistics from the theory of measurement error are utilized to quantify the reliability and difficulty of the study. An extension of the Pearson correlation coefficient, called the detection correlation coefficient, is derived and used in recognition of the fact that readers agree on numerous non-spike regions. Spike perception is modeled with both dichotomous and continuous values. as expected, the study reliability is higher when using the continuous values. Standard sensitivity and specificity definitions are extended and applied to continuous-valued spike perception. A database of "panel scores" was created from the 5 reader scorings by merging spikes within 75 msec on each side. The average inter-reader correlation is 0.79 with a corresponding reliability of 0.95. Average spike attributes are calculated, and the resulting database can serve as a "gold standard" for testing computer algorithms or other readers.

Entities:  

Mesh:

Year:  1996        PMID: 8631278     DOI: 10.1016/0013-4694(95)00221-9

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


  13 in total

1.  Enhanced automated sleep spindle detection algorithm based on synchrosqueezing.

Authors:  Muammar M Kabir; Reza Tafreshi; Diane B Boivin; Naim Haddad
Journal:  Med Biol Eng Comput       Date:  2015-03-17       Impact factor: 2.602

2.  High inter-reviewer variability of spike detection on intracranial EEG addressed by an automated multi-channel algorithm.

Authors:  Daniel T Barkmeier; Aashit K Shah; Danny Flanagan; Marie D Atkinson; Rajeev Agarwal; Darren R Fuerst; Kourosh Jafari-Khouzani; Jeffrey A Loeb
Journal:  Clin Neurophysiol       Date:  2011-10-26       Impact factor: 3.708

3.  Interrater Reliability of Experts in Identifying Interictal Epileptiform Discharges in Electroencephalograms.

Authors:  Jin Jing; Aline Herlopian; Ioannis Karakis; Marcus Ng; Jonathan J Halford; Alice Lam; Douglas Maus; Fonda Chan; Marjan Dolatshahi; Carlos F Muniz; Catherine Chu; Valeria Sacca; Jay Pathmanathan; WenDong Ge; Haoqi Sun; Justin Dauwels; Andrew J Cole; Daniel B Hoch; Sydney S Cash; M Brandon Westover
Journal:  JAMA Neurol       Date:  2020-01-01       Impact factor: 18.302

4.  Interictal epileptiform discharge characteristics underlying expert interrater agreement.

Authors:  Elham Bagheri; Justin Dauwels; Brian C Dean; Chad G Waters; M Brandon Westover; Jonathan J Halford
Journal:  Clin Neurophysiol       Date:  2017-07-18       Impact factor: 3.708

5.  A fast machine learning approach to facilitate the detection of interictal epileptiform discharges in the scalp electroencephalogram.

Authors:  Elham Bagheri; Jing Jin; Justin Dauwels; Sydney Cash; M Brandon Westover
Journal:  J Neurosci Methods       Date:  2019-07-13       Impact factor: 2.390

6.  Measuring expertise in identifying interictal epileptiform discharges.

Authors:  Nitish M Harid; Jin Jing; Jacob Hogan; Fábio A Nascimento; An Ouyang; Wei-Long Zheng; Wendong Ge; Sahar F Zafar; Jennifer A Kim; D Lam Alice; Aline Herlopian; Douglas Maus; Ioannis Karakis; Marcus Ng; Shenda Hong; Zhu Yu; Peter W Kaplan; Sydney Cash; Mouhsin Shafi; Gabriel Martz; Jonathan J Halford; Michael Brandon Westover
Journal:  Epileptic Disord       Date:  2022-06-01       Impact factor: 2.333

Review 7.  A Brief Introduction to Magnetoencephalography (MEG) and Its Clinical Applications.

Authors:  Alfred Lenin Fred; Subbiahpillai Neelakantapillai Kumar; Ajay Kumar Haridhas; Sayantan Ghosh; Harishita Purushothaman Bhuvana; Wei Khang Jeremy Sim; Vijayaragavan Vimalan; Fredin Arun Sedly Givo; Veikko Jousmäki; Parasuraman Padmanabhan; Balázs Gulyás
Journal:  Brain Sci       Date:  2022-06-15

8.  Characteristics of EEG Interpreters Associated With Higher Interrater Agreement.

Authors:  Jonathan J Halford; Amir Arain; Giridhar P Kalamangalam; Suzette M LaRoche; Bonilha Leonardo; Maysaa Basha; Nabil J Azar; Ekrem Kutluay; Gabriel U Martz; Wolf J Bethany; Chad G Waters; Brian C Dean
Journal:  J Clin Neurophysiol       Date:  2017-03       Impact factor: 2.177

9.  EEG spike activity precedes epilepsy after kainate-induced status epilepticus.

Authors:  Andrew White; Philip A Williams; Jennifer L Hellier; Suzanne Clark; F Edward Dudek; Kevin J Staley
Journal:  Epilepsia       Date:  2009-10-20       Impact factor: 5.864

10.  Studentized continuous wavelet transform (t-CWT) in the analysis of individual ERPs: real and simulated EEG data.

Authors:  Ruben G L Real; Boris Kotchoubey; Andrea Kübler
Journal:  Front Neurosci       Date:  2014-09-10       Impact factor: 4.677

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