Document
type: Class

Continuant
type: Class

Entity
type: Class

International Journal of Modern Physics C
type: Continuant
type: Information Content Entity
publication venue for: Spectral properties of the respiratory signal during sleep apnea events: Obtrusive and unobtrusive measurements
type: Journal
type: Collection
type: Generically Dependent Continuant
type: Thing
type: Entity
type: Periodical
type: Document

Generically Dependent Continuant
type: Class

RDF description of Spectral properties of the respiratory signal during sleep apnea events: Obtrusive and unobtrusive measurements - http://orbis.uaslp.mx/vivo/individual/scopus5937
rights: termsOfUse
date: 2026-08-27T04:47:53
publisher: vivo
type: Document

Spectral properties of the respiratory signal during sleep apnea events: Obtrusive and unobtrusive measurements
artnum: 1950030
type: Generically Dependent Continuant
issue: 5
related by: authorship_37843
type: Document
most specific type: Document
related by: authorship_37839
type: Information Content Entity
related by: authorship_37840
related by: authorship_37844
type: Thing
related by: authorship_37841
type: Entity
related by: authorship_37845
freetext keyword: entropy; Fourier transform; instantaneous frequency; PBS; respiratory efforts; sleep; sleep apnea
most specific type: Article
abstract: People with obstructive sleep apnea hypopnea syndrome (OSAHS) are affected by disruption in normal breathing patterns during sleep. In the literature, it is common to find acquisition of Thoracic (THO) and abdominal (ABD) movements with piezo-electric bands included in a full polysomnography. These movements convey valuable information related to sleep apnea events, and for this reason, contactless methods, such as the Pressure Bed Sensor (PBS), have been developed to extract this information. The main goal of this study is to analyze apnea and hypopnea fluctuations based on the spectral analysis of nasal airflow measure (as a reference signal), thoraco-abdominal effort and PBS respiration signal. To this end, features from the respiratory spectrum such as entropy, Gaussian modeling and instantaneous frequency were computed. These spectral properties were evaluated in three windows for each sensor: control point (CP) which is a window randomly extracted for the sleep time without apnea event, before event (BE) a window before an apnea episode and during event (DE) a window during an apnea episode. Apnea and hypopnea events were analyzed separately. According to a database of seventeen subjects, DE windows showed significant differences with respect to the CP window in most of the computed indices for both apnea and hypopnea events for all sensors. Significant differences were also found when DE and BE windows were compared in the case of apnea for all the sensors. In conclusion, the analyzed spectral characteristics could be a good tool to detect apnea and hypopnea. Finally, PBS signal which is a unobtrusive sensor, maintains the spectral properties of the standard respiratory effort measurements, and the use of this sensor could be useful for the monitoring outside of a clinical environment, simplifying the acquisition process. © 2019 World Scientific Publishing Company.
doi: 10.1142/S012918311950030X
crisid: 5938
estado: published
date time value: article date 5938
e iscopus: 2-s2.0-85066064262
type: Article
origen: scopus
volume: 30
type: Continuant
related by: authorship_37842
has publication venue: International Journal of Modern Physics C
related by: authorship_37846

Article
type: Class

Information Content Entity
type: Class