Literature DB >> 26737662

An open-source toolbox for standardized use of PhysioNet Sleep EDF Expanded Database.

Syed Anas Imtiaz, Esther Rodriguez-Villegas.   

Abstract

PhysioNet Sleep EDF database has been the most popular source of data used for developing and testing many automatic sleep staging algorithms. However, the recordings from this database has been used in an inconsistent fashion. For example, arbitrary selection of start and end times from long term recordings, data-hypnogram mismatches, different performance metrics and hypnogram conversion from R&K to AASM. All these differences result in different data sections and performance metrics being used by researchers thereby making any direct comparison between algorithms very difficult. Recently, a superset of this database has been made available on PhysioNet, known as the Sleep EDF Expanded Database which includes 61 recordings. This provides an opportunity to standardize the way in which signals from this database should be used. With this goal in mind, we present in this paper a toolbox for automatically downloading and extracting recordings from the Sleep EDF Expanded database and converting them to a suitable format for use in MATLAB. This toolbox contains functions for selecting appropriate data for sleep analysis (based on our previous recommendations for sleep staging), hypnogram conversion and computation of performance metrics. Its use makes it simpler to start using the new sleep database and also provides a foundation for much-needed standardization in this research field.

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Year:  2015        PMID: 26737662     DOI: 10.1109/EMBC.2015.7319762

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging.

Authors:  Huy Phan; Fernando Andreotti; Navin Cooray; Oliver Y Chen; Maarten De Vos
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2019-01-31       Impact factor: 3.802

2.  Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification.

Authors:  Huy Phan; Fernando Andreotti; Navin Cooray; Oliver Y Chen; Maarten De Vos
Journal:  IEEE Trans Biomed Eng       Date:  2018-10-22       Impact factor: 4.538

3.  Publicly Available Health Research Datasets: Opportunities and Responsibilities.

Authors:  Ahmed S BaHammam; Michael W L Chee
Journal:  Nat Sci Sleep       Date:  2022-09-27

Review 4.  SleepOMICS: How Big Data Can Revolutionize Sleep Science.

Authors:  Nicola Luigi Bragazzi; Ottavia Guglielmi; Sergio Garbarino
Journal:  Int J Environ Res Public Health       Date:  2019-01-21       Impact factor: 3.390

  4 in total

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