Journal article
An emerging technology for the identification and characterization of postural-dependent obstructive sleep apnea
Journal of clinical sleep medicine, Vol.16(2), pp.309-318
2020
PMID: 31992410
Abstract
Study Objectives: Body posture has a significant impact on the presence and severity of obstructive sleep apnea (OSA). The majority of polysomnography
(PSG) systems have the capacity to categorize body (torso) posture as supine, left-lateral, right-lateral or prone, each within a 90-degree range. However, such
broad categorization may limit the identification of subtle relationships between posture and OSA severity. The aim of this study was to quantify sleeping posture as
a continuous variable; and to develop an intuitive tool for visualizing the relationship between body posture and OSA severity.
Methods: A customized triaxial accelerometer-based posture sensor which quantifies torso posture as a continuous variable was developed. 38 participants attending
the sleep laboratory for suspected OSA were recruited. Each participant underwent a diagnostic PSG with an additional customized posture sensor securely attached to
the sternum. Individual data were presented using a novel circular histogram-based visualization which displays sleeping position and position-specific OSA severity.
Results: Acceptable measurements were obtained in 21 participants. The mean ± standard deviation percentage of total sleep time spent within ± 15 degrees of
the center of supine, left-lateral, right-lateral and prone was 59.7 ± 26.0%. A further 40.3 ± 26.0% of sleep time was spent in intermediate positions outside these
traditional categorizations. The novel visualization revealed a wide variety of positional OSA phenotypes.
Conclusions: Quantification of torso posture as a continuous variable and analysis of these data using a novel visualization enables the identification of subtle
relationships between body posture and OSA severity that are not apparent using standard clinical sensors and summary statistics
Details
- Title
- An emerging technology for the identification and characterization of postural-dependent obstructive sleep apnea
- Authors/Creators
- Albert Tate - Queensland University of TechnologyJennifer Walsh - The University of Western AustraliaVeena Kurup - The University of Western AustraliaBindiya Shenoy - The University of Western AustraliaDwayne Mann - Queensland University of TechnologyCraig Freakley - Queensland University of TechnologyPeter Eastwood - The University of Western AustraliaPhilip Terrill - Queensland University of Technology
- Publication Details
- Journal of clinical sleep medicine, Vol.16(2), pp.309-318
- Publisher
- Amer Acad Sleep Medicine
- Number of pages
- 10
- Grant note
- Hull Family Donation at the Faculty of Engineering, Architecture and Information Technology at the University of Queensland 1136548 / National Health and Medical Research Council Senior Research Fellowship; National Health and Medical Research Council (NHMRC) of Australia University of Queensland Early Career Researcher Grant Sir Charles Gardiner Hospital Research Advisory Committee Grant
- Identifiers
- 991005592762607891
- Copyright
- © 2020 American Academy of Sleep Medicine
- Murdoch Affiliation
- Vice Chancellery
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Metrics
39 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Citation topics
- 1 Clinical & Life Sciences
- 1.137 Sleep Science & Circadian Systems
- 1.137.382 Obstructive Sleep Apnea
- Web Of Science research areas
- Clinical Neurology
- ESI research areas
- Neuroscience & Behavior