Non-contact sleep atrial fibrillation monitoring using fiber optic sensors

This study presents a fiber optic monitoring pillow (FOMP) designed for non-contact sleep monitoring of patients with atrial fibrillation (AF). The FOMP employs fiber optic sensors to capture respiratory and cardiac waveforms, enabling the extraction of physiological parameters such as heart rate and respiratory rate. In a clinical trial involving AF patients, the FOMP successfully detected effective ballistocardiogram signals using a non-contact approach for the first time, demonstrating a high correlation with electrocardiogram data, as evidenced by a Pearson's correlation coefficient of 0.984. Additionally, the FOMP effectively identified abnormal respiration patterns indicative of sleep apnea. This non-invasive monitoring technique offers a valuable tool for the early detection and continuous assessment of cardiovascular health, underscoring its potential for integration into routine health monitoring protocols.

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Publication Details

Published
2025-05-22
DOI
https://doi.org/10.1117/12.3061070
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
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article

Non-contact sleep atrial fibrillation monitoring using fiber optic sensors

Z W Wang, Feng Wang, Zhuoxian Chen, Weijian Hang et al.
Non-Invasive Vital Sign Monitoring
article

Non-contact sleep atrial fibrillation monitoring using fiber optic sensors

Z W Wang, Feng Wang, Zhuoxian Chen, Weijian Hang, Chengjuan Fan, Qiu Sun, Chen Chen, Hao Li, Zhijun Yan, Hao Jin, Kai Zhou
article en

Abstract

This study presents a fiber optic monitoring pillow (FOMP) designed for non-contact sleep monitoring of patients with atrial fibrillation (AF). The FOMP employs fiber optic sensors to capture respiratory and cardiac waveforms, enabling the extraction of physiological parameters such as heart rate and respiratory rate. In a clinical trial involving AF patients, the FOMP successfully detected effective ballistocardiogram signals using a non-contact approach for the first time, demonstrating a high correlation with electrocardiogram data, as evidenced by a Pearson's correlation coefficient of 0.984. Additionally, the FOMP effectively identified abnormal respiration patterns indicative of sleep apnea. This non-invasive monitoring technique offers a valuable tool for the early detection and continuous assessment of cardiovascular health, underscoring its potential for integration into routine health monitoring protocols.

Huazhong University of Science and Technology (CN), Wuxi Institute of Technology (CN)
Openalex Percentile: Top 90%
Non-Invasive Vital Sign Monitoring
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