DOI: 10.5061/dryad.3bk3j9kz0
title: Data from: EEG sonification improves sleep staging performance in novice stagers

description: Sleep staging is a critical tool used in research and clinical settings to
 evaluate and diagnose sleep conditions; however, sleep staging is labor
 intensive and may be challenging for inexperienced practitioners. We
 explored whether adding an auditory representation (sonification) of the
 EEG to a standard visual representation could improve sleep staging
 performance or reduce workload. This is the first study to investigate the
 effects of sonification on sleep staging performance. We performed a
 within-subjects study in which 40 participants completed an online sleep
 staging task with and without sonified EEG. EEG was sonified by minimal
 transformation in which the raw EEG signal was played as an audio signal.
 Contrary to our hypothesis, we found that adding sonification did not
 result in improvements in accuracy, speed, or workload for the entire
 subject group. However, when we stratified participants by sleep staging
 experience, we found sonification improved accuracy for the least
 experienced participants. These findings suggest EEG sonification may be
 useful as a tool to enable novice sleep stagers to reach acceptable
 performance levels faster.This repository contains the responses given by
 participants and their accuracy, along with demogrpahic, survey
 information, and R files needed to replicate our analysis.
description: # Data from: EEG sonification improves sleep staging performance in novice
 stagers Dataset DOI: [10.5061/dryad.3bk3j9kz0](10.5061/dryad.3bk3j9kz0) ##
 Description of the data and file structure Two files are used for
 analysis. The qdf.csv file contains data collected after the end of each
 experimental block, such as the participant's accuracy and their TLX
 scores after completing the block. The rdf.csv file contains this data,
 and additionally contains a row for each individual response the
 participant gave. Missing values are represented as empty columns. Each
 participant has three rows, which contains their information for the first
 block (training block), second, and third block of the experiment Some
 information is only present for specific blocks. Block 0 is a training
 block, and participants did not complete the task load index (TLX) after
 this block; we also did not compute kappa for this block as participants
 were presented with each question until they got it correct. Some
 questions regarding overall experience were asked only after block 2.
 Columns in the qdf2 file * pid--unique ID identifying the participant
 across blocks * TLX* columns--represent scores on each axis of the NASA
 Task Load Index * heard_sounds --represents whether the participant
 reported hearing sonification sounds after the conclusion of the block
 (asked only after block 2) * sounds_useful--participant rating of whether
 the sounds were useful for sleep staging. Options include "Yes, a
 lot", "Yes, a little", "Unsure", and
 "No" (asked only after block 2) * Future_interest--whether the
 participant would be interested in trying software that sonifies sleep for
 staging in the future (asked only after block 2) * soundOrder--in which
 block did they receive sounds * block--which block does this row
 correspond to. * rts--median time (seconds) taken to score each epoch (not
 logged for some of the earliest responses) * age, gender--Age in years.
 Gender could be male, female, or non-binary. * Experience--self-described
 sleep staging experience. Options are beginner, intermediate, or
 experienced * num_staged--number of polysomnograms staged in the past
 year. Options are none, 1-10,11-20,21-40,41-80, or more than 80 *
 condition--what experimental condition does this row correspond to? Sound
 training is the initial practice blocks, the other two are assessment
 blocks in the "sound" or "visual only" condition *
 kappa--Cohen's kappa for sleep staging performance in this block The
 rdf file contains these columns, but since each row represents one sleep
 stage given by the user, it contains additional columns describing the
 staging * user_stage--the sleep stage selected by the user. 0-wake, 4=REM,
 and all others are nREM stages 1-3 * correctStage--the true sleep stage *
 timeSpent--seconds taken from when the stage was shown to when the user
 gave a stage * totalClicks--number of times the user clicked back or
 forward in time when staging * question--ID number for this specific item
 within the block * isCorrect--whether the user's response was correct
 (1=yes, 0=no) ## Code/software No special software is needed to view the
 files, but the R scripts in the rscripts folder can be used to recreate
 the analyses in the paper in R 4.4.1 The important r packages are:
 data_cleaning.R--reads the qdf2 and rdf2 files located in the same
 directory as the script and prepares data frames for analysis
 soundspindle.R--generates the graphs and analyses shown in the paper using
 the data frames created by data_cleaning.R packages.R --required
 dependencies to run the analysis and data cleaning
 SoundspindleExperiment.Rproj --R studio workspace ## Human subjects data
 We have inspected the data to ensure that no information as names, emails,
 IPs, or other identifiers are present. All participants consented to the
 following provision in the consent form: Your non-identifiable data such
 as responses to questions collected as part of the research will be
 stored, used for future research studies, and may be shared with other
 researchers for future research studies without additional informed
 consent from you or your legally authorized representative. Your data
 might be shared with academic research institutions, non-profit entities,
 and/or for-profit entities Your data may also be made publicly available
 in research data repositories such as the Open Science Framework.