Intra- and Inter-Rater Reliability of Manual Feature Extraction Methods in Movement Related Cortical Potential Analysis.
electroencephalography (EEG) processing
event related potential (ERP)
inter-rater reliability
intra-rater reliability
movement related cortical potential (MRCP)
stroke
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
24 Apr 2020
24 Apr 2020
Historique:
received:
02
03
2020
revised:
16
04
2020
accepted:
20
04
2020
entrez:
30
4
2020
pubmed:
30
4
2020
medline:
5
2
2021
Statut:
epublish
Résumé
Event related potentials (ERPs) provide insight into the neural activity generated in response to motor, sensory and cognitive processes. Despite the increasing use of ERP data in clinical research little is known about the reliability of human manual ERP labelling methods. Intra-rater and inter-rater reliability were evaluated in five electroencephalography (EEG) experts who labelled the peak negativity of averaged movement related cortical potentials (MRCPs) derived from thirty datasets. Each dataset contained 50 MRCP epochs from healthy people performing cued voluntary or imagined movement, or people with stroke performing cued voluntary movement. Reliability was assessed using the intraclass correlation coefficient and standard error of measurement. Excellent intra- and inter-rater reliability was demonstrated in the voluntary movement conditions in healthy people and people with stroke. In comparison reliability in the imagined condition was low to moderate. Post-hoc secondary epoch analysis revealed that the morphology of the signal contributed to the consistency of epoch inclusion; potentially explaining the differences in reliability seen across conditions. Findings from this study may inform future research focused on developing automated labelling methods for ERP feature extraction and call to the wider community of researchers interested in utilizing ERPs as a measure of neurophysiological change or in the delivery of EEG-driven interventions.
Identifiants
pubmed: 32344692
pii: s20082427
doi: 10.3390/s20082427
pmc: PMC7219488
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
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