Wu Shan, Chen Mingjing, Wei Keming, Liu Guanzheng
School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China.
Comput Methods Programs Biomed. 2021 Nov;211:106442. doi: 10.1016/j.cmpb.2021.106442. Epub 2021 Sep 29.
Sleep apnea (SA) is a common sleep disorder in daily life and is also an aggravating factor for various diseases. Having the potential to replace traditional but complicated diagnostic equipment, portable medical devices are receiving increasing attention, and thus, the demand for supporting algorithms is growing. This study aims to identify SA with wearable devices.
Static information-based similarity (sIBS) and dynamic information-based similarity (dIBS) were proposed to analyze short-term fluctuations in heart rate (HR) with wearable devices. This study included overnight photoplethysmography (PPG) signals from 92 subjects obtained from wearable bracelets.
The results showed that sIBS achieved the highest correlation coefficient with the apnea-hypopnea index (R=-0.653, p=0). dIBS showed a good balance in sensitivity and specificity (75.0% and 72.1%, respectively). Combining sIBS and dIBS with other classical time-frequency domain indices could simultaneously achieve good accuracy and balance (84.7% accuracy, 76.7% sensitivity and 89.6% specificity).
This research showed that both classic time-frequency domain indices and IBS indices changed significantly only in the severe SA group. This novel method could serve as an effective way to assess SA and provide new insight into its pathophysiology.
睡眠呼吸暂停（SA）是日常生活中常见的睡眠障碍，也是多种疾病的加重因素。便携式医疗设备有可能取代传统但复杂的诊断设备，因此受到越来越多的关注，对支持算法的需求也在不断增长。本研究旨在通过可穿戴设备识别SA。
提出基于静态信息的相似度（sIBS）和基于动态信息的相似度（dIBS），以分析可穿戴设备记录的心率（HR）短期波动情况。本研究纳入了92名受试者通过可穿戴手环获得的夜间光电容积脉搏波描记法（PPG）信号。
结果显示，sIBS与呼吸暂停低通气指数的相关系数最高（R=-0.653，p=0）。dIBS在敏感性和特异性方面表现出良好的平衡（分别为75.0%和72.1%）。将sIBS和dIBS与其他经典的时频域指标相结合，可同时实现良好的准确性和平衡性（准确率84.7%，敏感性76.7%，特异性89.6%）。
本研究表明，经典的时频域指标和IBS指标仅在重度SA组中发生显著变化。这种新方法可作为评估SA的有效手段，并为其病理生理学提供新的见解。
