On the generalizability of ECG-based obstructive sleep apnea monitoring: merits and limitations of the Apnea-ECG database

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Abstract

Obstructive sleep apnea syndrome (OSAS) is a sleep disorder that affects a large part of the population and the development of algorithms using cardiovascular features for OSAS monitoring has been an extensively researched topic in the last two decades. Several studies regarding automatic apneic event classification using ECG derived features are based on the public Apnea-ECG database available on PhysioNet. Although this database is an excellent starting point for apnea topic investigations, in our study we show that algorithms for apneic-epochs classification that are successfully trained on this database (sensitivity < 85%, false detection rate <20%) perform poorly (sensitivity\textit<55%, false detection rate < 40%) in other databases which include patients with a broader spectrum of apneic events and sleep disorders. The reduced performance can be related to the complexity of breathing events, the increased number of non-breathing related sleep events, and the presence of non-OSAS sleep pathologies.

Original languageEnglish
Title of host publication40th International Engineering in Medicine and Biology Conference
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages6022-6025
Number of pages4
ISBN (Electronic)978-1-5386-3646-6
DOIs
Publication statusPublished - 22 Jul 2018
Event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society= (EMBC 2018) - Hawaii Convention Center, Honolulu, United States
Duration: 18 Jul 201821 Jul 2018
Conference number: 40
https://embc.embs.org/2018/

Conference

Conference40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society= (EMBC 2018)
Abbreviated titleEMBC 2018
CountryUnited States
CityHonolulu
Period18/07/1821/07/18
Other"Learning from the Past, Looking to the Future"
Internet address

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