Innovative Sleep Monitoring: A Non-Invasive Approach Using Force-Sensing Resistors for Analyzing Sleep Quality and Detecting Sleep-Related Breathing Disorders
3
Issued Date
2024-03-01
Resource Type
ISSN
16866576
eISSN
26730014
Scopus ID
2-s2.0-85193032692
Journal Title
International Journal of Geoinformatics
Volume
20
Issue
3
Start Page
17
End Page
27
Rights Holder(s)
SCOPUS
Bibliographic Citation
International Journal of Geoinformatics Vol.20 No.3 (2024) , 17-27
Suggested Citation
Lokavee S., Pengjiam J., Tantrakul V., Kerdcharoen T. Innovative Sleep Monitoring: A Non-Invasive Approach Using Force-Sensing Resistors for Analyzing Sleep Quality and Detecting Sleep-Related Breathing Disorders. International Journal of Geoinformatics Vol.20 No.3 (2024) , 17-27. 27. doi:10.52939/ijg.v20i3.3123 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/98415
Title
Innovative Sleep Monitoring: A Non-Invasive Approach Using Force-Sensing Resistors for Analyzing Sleep Quality and Detecting Sleep-Related Breathing Disorders
Author(s)
Author's Affiliation
Corresponding Author(s)
Other Contributor(s)
Abstract
This study presents an innovative, non-invasive sleep monitoring system that employs force-sensing resistors (FSRs) embedded in a pillow sheet to analyze sleep quality and detect sleep-related breathing disorders (SDB), offering an alternative to conventional polysomnography (PSG). We employed a comprehensive methodology, integrating FSRs with a wireless network device and dedicated software for real-time, precise data analysis and storage. The FSRs, calibrated to measure biomechanical signals associated with body movement, are integrated with a wireless network device. The experiment involved twenty-seven subjects diagnosed with sleep apnea, and the results were compared with PSG recordings. The intelligent sleep application recorded various sleep metrics, including sleep efficiency (SE), and respiratory rhythm. A regression analysis revealed a strong correlation (R2 = 0.96) between the SE measured by the PSG device and the pillow-sheet sensor systems, confirming the reliability of the latter. The Bland-Altman plot further supported this consistency. In conclusion, the pillow-sheet embedded with FSR sensors is a promising tool for unobtrusive sleep monitoring and SDB detection. It offers comparable accuracy to PSG, with the added benefits of being user-friendly and nonrestrictive, making it suitable for clinical and home settings. The system’s ability to provide insights into sleep patterns, detect apnea episodes, and analyze sleep postures presents a significant advancement in sleep research and medicine, with potential applications in personalized sleep health management.