Han Ning, Lan Ke, Zhang Yuezhou, Wan Tao, Zhang Zhengbo, Cao Deshen, Yan Wei
Department of Biomedical Engineering, Chinese PLA General Hospital, Beijing 100853, P.R.China.
SensEcho Co, Ltd, Beijing 110000, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Feb 25;38(1):131-137. doi: 10.7507/1001-5515.201909012.
As a novel technology, wearable physiological parameter monitoring technology represents the future of monitoring technology. However, there are still many problems in the application of this kind of technology. In this paper, a pilot study was conducted to evaluate the quality of electrocardiogram (ECG) signals of the wearable physiological monitoring system (SensEcho-5B). Firstly, an evaluation algorithm of ECG signal quality was developed based on template matching method, which was used for automatic and quantitative evaluation of ECG signals. The algorithm performance was tested on a randomly selected 100 h dataset of ECG signals from 100 subjects (15 healthy subjects and 85 patients with cardiovascular diseases). On this basis, 24-hour ECG data of 30 subjects (7 healthy subjects and 23 patients with cardiovascular diseases) were collected synchronously by SensEcho-5B and ECG Holter. The evaluation algorithm was used to evaluate the quality of ECG signals recorded synchronously by the two systems. Algorithm validation results: sensitivity was 100%, specificity was 99.51%, and accuracy was 99.99%. Results of controlled test of 30 subjects: the median (Q1, Q3) of ECG signal detected by SensEcho-5B with poor signal quality time was 8.93 (0.84, 32.53) minutes, and the median (Q1, Q3) of ECG signal detected by Holter with poor signal quality time was 14.75 (4.39, 35.98) minutes (Rank sum test, =0.133). The results show that the ECG signal quality algorithm proposed in this paper can effectively evaluate the ECG signal quality of the wearable physiological monitoring system. Compared with signal measured by Holter, the ECG signal measured by SensEcho-5B has the same ECG signal quality. Follow-up studies will further collect physiological data of large samples in real clinical environment, analyze and evaluate the quality of ECG signals, so as to continuously optimize the performance of the monitoring system.
作为一项新技术，可穿戴生理参数监测技术代表了监测技术的未来。然而，这类技术在应用中仍存在许多问题。本文进行了一项初步研究，以评估可穿戴生理监测系统（SensEcho - 5B）的心电图（ECG）信号质量。首先，基于模板匹配方法开发了一种ECG信号质量评估算法，用于对ECG信号进行自动定量评估。该算法性能在从100名受试者（15名健康受试者和85名心血管疾病患者）中随机选取的100小时ECG信号数据集上进行了测试。在此基础上，通过SensEcho - 5B和心电图动态监测仪同步采集了30名受试者（7名健康受试者和23名心血管疾病患者）的24小时ECG数据。使用该评估算法对两个系统同步记录的ECG信号质量进行评估。算法验证结果：灵敏度为100%，特异性为99.51%，准确率为99.99%。30名受试者的对照测试结果：信号质量差时SensEcho - 5B检测到的ECG信号时间中位数（Q1，Q3）为8.93（0.84，32.53）分钟，心电图动态监测仪检测到的信号质量差时的ECG信号时间中位数（Q1，Q3）为14.75（4.39，35.98）分钟（秩和检验， =0.133）。结果表明，本文提出的ECG信号质量算法能够有效评估可穿戴生理监测系统的ECG信号质量。与心电图动态监测仪测量的信号相比，SensEcho - 5B测量的ECG信号具有相同的ECG信号质量。后续研究将在真实临床环境中进一步收集大样本生理数据，分析和评估ECG信号质量，以便不断优化监测系统的性能。
