Title | ||
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Unsupervised Artefact Detection And Screening Using Emfit Sensor In Patients With Sleep Apnea |
Abstract | ||
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Sleep apnea is one of the most common sleep disorders. As sleep apnea is associated to adverse health outcomes, early screening is promoted through unobtrusive, cheap and simple systems for sleep monitoring. A commercial pressure sensor meeting these requirements is the Emfit QS, which was integrated in a bed of a specialized sleep center. The sensor is pressure based and highly sensitive to movement. This causes artefacts of different morphologies in the signal. An unsupervised artefact detection method was developed to avoid burdensome manual labelling of artefacts in the signal and enabling further analysis. Moreover, the percentage of detected artefacts was useful for assessment of the sleep apnea severity as movements partially originate from apneic arousals. Severe sleep apnea patients could be identified with a sensitivity of 80% and a specificity of 87%.The proposed approach offers an ambivalent tool for artefact detection and unobtrusive screening of sleep apnea patients at home. |
Year | DOI | Venue |
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2018 | 10.22489/CinC.2018.186 | 2018 COMPUTING IN CARDIOLOGY CONFERENCE (CINC) |
Field | DocType | Volume |
Sleep apnea,Sleep monitoring,Physical medicine and rehabilitation,Medicine | Conference | 45 |
ISSN | Citations | PageRank |
2325-8861 | 0 | 0.34 |
References | Authors | |
0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Dorien Huysmans | 1 | 0 | 0.68 |
Bertien Buyse | 2 | 1 | 4.75 |
Dries Testelmans | 3 | 2 | 5.80 |
Sabine Van Huffel | 4 | 1058 | 149.38 |
Carolina Varon | 5 | 92 | 22.90 |