Academic Journal
Overnight Sleep Staging Using Chest-Worn Accelerometry
| Τίτλος: | Overnight Sleep Staging Using Chest-Worn Accelerometry |
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| Συγγραφείς: | Schipper, Fons, Grassi, Angela, Ross, Marco, Cerny, Andreas, Anderer, Peter, Hermans, Lieke, van Meulen, Fokke, Leentjens, Mickey, Schoustra, Emily, Bosschieter, Pien, van Sloun, Ruud J.G., Overeem, Sebastiaan, Fonseca, Pedro |
| Πηγή: | Schipper, F, Grassi, A, Ross, M, Cerny, A, Anderer, P, Hermans, L, van Meulen, F, Leentjens, M, Schoustra, E, Bosschieter, P, van Sloun, R J G, Overeem, S & Fonseca, P 2024, 'Overnight Sleep Staging Using Chest-Worn Accelerometry', Sensors, vol. 24, no. 17, 5717. https://doi.org/10.3390/s24175717 |
| Έτος έκδοσης: | 2024 |
| Θεματικοί όροι: | Humans, Middle Aged, Adult, Aged, Accelerometry/instrumentation, Male, Female, Adolescent, 80 and over, Polysomnography/methods, Sleep Stages/physiology, Young Adult, Algorithms, Thorax |
| Περιγραφή: | Overnight sleep staging is an important part of the diagnosis of various sleep disorders. Polysomnography is the gold standard for sleep staging, but less-obtrusive sensing modalities are of emerging interest. Here, we developed and validated an algorithm to perform "proxy" sleep staging using cardiac and respiratory signals derived from a chest-worn accelerometer. We collected data in two sleep centers, using a chest-worn accelerometer in combination with full PSG. A total of 323 participants were analyzed, aged 13-83 years, with BMI 18-47 kg/m 2. We derived cardiac and respiratory features from the accelerometer and then applied a previously developed method for automatic cardio-respiratory sleep staging. We compared the estimated sleep stages against those derived from PSG and determined performance. Epoch-by-epoch agreement with four-class scoring (Wake, REM, N1+N2, N3) reached a Cohen's kappa coefficient of agreement of 0.68 and an accuracy of 80.8%. For Wake vs. Sleep classification, an accuracy of 93.3% was obtained, with a sensitivity of 78.7% and a specificity of 96.6%. We showed that cardiorespiratory signals obtained from a chest-worn accelerometer can be used to estimate sleep stages among a population that is diverse in age, BMI, and prevalence of sleep disorders. This opens up the path towards various clinical applications in sleep medicine. |
| Τύπος εγγράφου: | article in journal/newspaper |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | English |
| ISSN: | 1424-8220 |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/39275628; info:eu-repo/semantics/altIdentifier/pissn/1424-8220 |
| DOI: | 10.3390/s24175717 |
| Διαθεσιμότητα: | https://research.tue.nl/en/publications/3d0bb6d0-e2c0-4962-8e9f-f615032e3859 https://doi.org/10.3390/s24175717 https://pure.tue.nl/ws/files/340773822/sensors-24-05717.pdf https://www.scopus.com/pages/publications/85203872704 |
| Rights: | info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/ |
| Αριθμός Καταχώρησης: | edsbas.289219A |
| Βάση Δεδομένων: | BASE |
| ISSN: | 14248220 |
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| DOI: | 10.3390/s24175717 |