TY - JOUR
T1 - Innovative Sleep Monitoring
T2 - A Non-Invasive Approach Using Force-Sensing Resistors for Analyzing Sleep Quality and Detecting Sleep-Related Breathing Disorders
AU - Lokavee, S.
AU - Pengjiam, J.
AU - Tantrakul, V.
AU - Kerdcharoen, T.
N1 - Publisher Copyright:
© Geoinformatics International.
PY - 2024/3
Y1 - 2024/3
N2 - 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.
AB - 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.
KW - Polysomnography
KW - Respiratory Rhythm
KW - Sleep Apnea
KW - Sleep Efficiency
KW - Sleep-Related Breathing Disorders
UR - https://www.scopus.com/pages/publications/85193032692
U2 - 10.52939/ijg.v20i3.3123
DO - 10.52939/ijg.v20i3.3123
M3 - Article
AN - SCOPUS:85193032692
SN - 1686-6576
VL - 20
SP - 17
EP - 27
JO - International Journal of Geoinformatics
JF - International Journal of Geoinformatics
IS - 3
ER -