阻塞性睡眠呼吸暂停
睡眠呼吸暂停
事件(粒子物理)
睡眠(系统调用)
计算机科学
陶瓷
材料科学
医学
心脏病学
物理
复合材料
操作系统
量子力学
作者
Yi Liu,Zhengdong Li,Xiaomao Fan,Yingying Shao,Dikun Hu,Rong Huang,Yi Xiao,Boxuan Lv,Liang Zhu,Zhaoyang Liu,Weidong Gao
标识
DOI:10.1109/jbhi.2025.3564838
摘要
Obstructive sleep apnea (OSA) is one of the major sleep disorders, which has been demonstrated to be a high-risk factor for cardiovascular disease, hypertension, and motor vehicle accidents. Pressure sensors in a contactless manner are a promising way to monitor sleep conditions outside of the hospital. However, previous studies mainly based on limited sensors are often subjected to noise contamination and constrained by the sleeper position to pressure sensors. The acquired pressure signals are of poor quality or even lost, which are not appropriate for the downstream task of OSA event detection. To address this issue, we designed a sensitive piezoelectric ceramic sensor array (PCSA) by aligning sixteen sensors embedded into a mat covering the chest and abdomen area, which can capture the changes of weak pressure signals under a sleeping mattress with a thickness of up to 30 cm. Based on PCSA, we recruited 36 adult volunteers from the Peking Union Medical College Hospital and conducted a pilot study to acquire overnight pressure signals along with polysomnography recordings. Subsequently, we developed an automated OSA event detection method named DRFNet. The main advantage of DRFNet is that it can well capture the time-domain and frequency-domain features from different views by fusing ResNet18 and DenseNet121 networks. Experiment results showed that DRFNet can achieve 75.19 % sensitivity, 87.78 % specificity, and 81.48 % accuracy, which is competitive with existing state-of-the-art methods. Combined with PCSA, it can be potentially deployed into an embedded device and provide contactless sleep monitoring service in home settings.
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