Systematic Comparison of Respiratory Signals for the Automated Detection of Sleep Apnea.
Annu Int Conf IEEE Eng Med Biol Soc
; 2018: 449-452, 2018 Jul.
Article
em En
| MEDLINE
| ID: mdl-30440431
ABSTRACT
Sleep apnea is one of the most common sleep disorders. It is characterized by the cessation of breathing during sleep due to airway blockages (obstructive sleep apnea) or disturbances in the signals from the brain (central sleep apnea). The gold standard for diagnosing sleep apnea is performing an overnight polysomnography recording which contains, among others, a wide array of respiratory signals. Respiration information can also be extracted from other physiological signals such as an electrocardiogram or from a bio-impedance measurement on the chest. Studies have shown that algorithms can be developed for automated sleep apnea detection using one of these many respiratory signals. In this work, the predictive power of these different respiratory signals is analyzed and compared. The results provide useful insights into the comparative predictive power of the different respiratory signals in a realistic setting for automated sleep apnea detection and provide a basis for the development of less obtrusive measurement techniques.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Síndromes da Apneia do Sono
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Polissonografia
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Adult
/
Aged
/
Female
/
Humans
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Male
/
Middle aged
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article