Orphanidou Christina, Drobnjak Ivana
IEEE J Biomed Health Inform. 2017 Sep;21(5):1216-1223. doi: 10.1109/JBHI.2016.2615316. Epub 2016 Oct 5.
Data in recordings obtained from ambulatory patients using wearable sensors are often corrupted by motion artefact and are, in general, noisier than the data obtained from the nonmobile patients. Identifying and ignoring erroneous measurements from these data is very important, if wearable sensors are to be incorporated into clinical practice. In this paper, we propose a novel Signal Quality Index, intended to assess whether reliable heart rates can be obtained from a single channel of ECG collected from ambulatory patients, using wearable sensors. The proposed system is based on wavelet entropy measurements of the heart rate variability signal. The system was trained and tested on expert-labeled data from a particular wearable sensor and was also tested on labeled data from a different sensor. The sensitivities and specificities achieved were 94% and 98%, respectively, on data from the same sensor as the training set, and 91% and 97%, respectively, on data from a different sensor, indicating the potential of the system to generalize across different sensors. Because the system relies on a single channel of ECG, it has the potential for inclusion in applications using wearable sensors and in the most basic clinical environments.
使用可穿戴传感器从动态患者获取的记录数据常常受到运动伪影的干扰，并且一般来说，比从非动态患者获取的数据噪声更大。如果要将可穿戴传感器纳入临床实践，识别并忽略这些数据中的错误测量值非常重要。在本文中，我们提出了一种新颖的信号质量指数，旨在评估是否可以使用可穿戴传感器从动态患者采集的单通道心电图中获得可靠的心率。所提出的系统基于心率变异性信号的小波熵测量。该系统在来自特定可穿戴传感器的专家标记数据上进行了训练和测试，并且也在来自不同传感器的标记数据上进行了测试。在与训练集相同的传感器的数据上，灵敏度和特异性分别达到了94%和98%，在来自不同传感器的数据上，灵敏度和特异性分别为91%和97%，这表明该系统具有跨不同传感器进行泛化的潜力。由于该系统依赖于单通道心电图，它有可能被纳入使用可穿戴传感器的应用以及最基本的临床环境中。
