five

EEG sonification improves sleep staging performance in novice stagers

收藏
DataONE2025-08-13 更新2025-08-23 收录
下载链接:
https://search.dataone.org/view/sha256:52a8de77d82a76619e06d9a92564f3188b3ed5793a6c205638785cde2c2f4cef
下载链接
链接失效反馈
官方服务:
资源简介:
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 ex..., , # 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 q..., 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.
创建时间:
2025-08-14
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作