Inter-expert and intra-expert reliability in sleep spindle scoring.

ABSTRACT:

Objectives

To measure the inter-expert and intra-expert agreement in sleep spindle scoring, and to quantify how many experts are needed to build a reliable dataset of sleep spindle scorings.

Methods

The EEG dataset was comprised of 400 randomly selected 115s segments of stage 2 sleep from 110 sleeping subjects in the general population (57±8, range: 42-72 years). To assess expert agreement, a total of 24 Registered Polysomnographic Technologists (RPSGTs) scored spindles in a subset of the EEG dataset at a single electrode location (C3-M2). Intra-expert and inter-expert agreements were calculated as F1-scores, Cohen's kappa (κ), and intra-class correlation coefficient (ICC).

Results

We found an average intra-expert F1-score agreement of 72±7% (κ: 0.66±0.07). The averag

SUBMITTER: Wendt SL 

PROVIDER: S-EPMC4426257 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature