| Online-Ressource |
Verfasst von: | Haghi, Mostafa [VerfasserIn]  |
| Gaiduk, Maksym [VerfasserIn]  |
| Stoffers, Marvin [VerfasserIn]  |
| Taherinejad, Nima [VerfasserIn]  |
| Penzel, Thomas [VerfasserIn]  |
| Madrid, Natividad Martínez [VerfasserIn]  |
| Seepold, Ralf [VerfasserIn]  |
Titel: | Evolution of bed-based sensor technology in unobtrusive sleep monitoring |
Titelzusatz: | a review |
Verf.angabe: | Mostafa Haghi , Member, IEEE, Maksym Gaiduk , Member, IEEE, Marvin Stoffers, Nima TaheriNejad , Member, IEEE, Thomas Penzel , Fellow, IEEE, Natividad Martínez Madrid , Senior Member, IEEE, and Ralf Seepold , Senior Member, IEEE |
E-Jahr: | 2024 |
Jahr: | 1 OCTOBER 2024 |
Umfang: | 19 S. |
Illustrationen: | Illustrationen |
Fussnoten: | Gesehen am 10.04.2025 |
Titel Quelle: | Enthalten in: Institute of Electrical and Electronics EngineersIEEE sensors journal |
Ort Quelle: | New York, NY : IEEE, 2001 |
Jahr Quelle: | 2024 |
Band/Heft Quelle: | 24(2024), 19, Seite 29545-29563 |
ISSN Quelle: | 1558-1748 |
Abstract: | With the emergence of new sensor technologies, such as fiber optic sensors (FOSs), compared to traditional mechanical sensors, unobtrusive sleep monitoring has been a research focus for decades. This work aims to provide a guide to current bed-based sensor technologies with diverse applications in various settings. We conducted a retrospective literature review, summarizing the state-of-the-art research over the past decade on non-contact bed-based sensor technology in sleep monitoring. We developed a three-category terminology: unobtrusive sensor technology, application, and subject. A total of 263 unique articles were acquired from three databases and screened for relevance, resulting in 21 papers selected for in-depth analysis. The findings revealed eight types of sensors: six mechanical sensors (pressure, accelerometer, piezoelectric, load cell, electromechanical film (EMFI), and hydraulic) and two FOSs (fiber Bragg grating and microbend FOS) that are integrated with or positioned under the bed at three levels of unobtrusiveness. We identified 15 parameters, with heart rate (HR) (14) and respiratory rate (RR) (13) being the most frequently measured. These parameters are generally categorized into three applications: disease-related diagnosis (18), general sleep analysis (9), and general well-being (11). The results indicated that sleep apnea (5) and insomnia (2) were the most frequently detected sleep disorders. Additionally, 59.1% (13) of the systems were tested in a lab environment, with only one undergoing clinical trials. In summary, there is a clear lack of convincing proof of the systems’ effectiveness in continuous in-home sleep monitoring. |
DOI: | doi:10.1109/JSEN.2024.3439743 |
URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.1109/JSEN.2024.3439743 |
| Volltext: https://ieeexplore.ieee.org/document/10640370 |
| DOI: https://doi.org/10.1109/JSEN.2024.3439743 |
Datenträger: | Online-Ressource |
Sprache: | eng |
Sach-SW: | Biomedical monitoring |
| Cardiorespiratory estimation |
| continuous monitoring |
| Diseases |
| fiber optic sensor (FOS) |
| Force |
| Immune system |
| Monitoring |
| Sensors |
| sleep |
| Sleep apnea |
| unobtrusive measurement |
K10plus-PPN: | 1922069892 |
Verknüpfungen: | → Zeitschrift |
Evolution of bed-based sensor technology in unobtrusive sleep monitoring / Haghi, Mostafa [VerfasserIn]; 1 OCTOBER 2024 (Online-Ressource)