Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia, Canada.
Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, British Columbia, Canada.
Sci Rep. 2017 Mar 28;7(1):459. doi: 10.1038/s41598-017-00540-x.
Current medical screening and diagnostic procedures have shifted toward recording longer electrocardiogram (ECG) signals, which have traditionally been processed on personal computers (PCs) with high-speed multi-core processors and efficient memory processing. Battery-driven devices are now more commonly used for the same purpose and thus exploring highly efficient, low-power alternatives for local ECG signal collection and processing is essential for efficient and convenient clinical use. Several ECG compression methods have been reported in the current literature with limited discussion on the performance of the compressed and the reconstructed ECG signals in terms of the QRS complex detection accuracy. This paper proposes and evaluates different compression methods based not only on the compression ratio (CR) and percentage root-mean-square difference (PRD), but also based on the accuracy of QRS detection. In this paper, we have developed a lossy method (Methods III) and compared them to the most current lossless and lossy ECG compression methods (Method I and Method II, respectively). The proposed lossy compression method (Method III) achieves CR of 4.5×, PRD of 0.53, as well as an overall sensitivity of 99.78% and positive predictivity of 99.92% are achieved (when coupled with an existing QRS detection algorithm) on the MIT-BIH Arrhythmia database and an overall sensitivity of 99.90% and positive predictivity of 99.84% on the QT database.
目前的医学筛查和诊断程序已经转向记录更长的心电图 (ECG) 信号，这些信号传统上是在具有高速多核处理器和高效内存处理能力的个人计算机 (PC) 上进行处理的。现在，电池驱动的设备更常用于相同的目的，因此探索高效、低功耗的本地 ECG 信号采集和处理替代方案对于高效、方便的临床应用至关重要。目前文献中已经报道了几种 ECG 压缩方法，但很少讨论压缩和重建 ECG 信号在 QRS 复合波检测精度方面的性能。本文提出并评估了基于不同压缩方法的方案，不仅基于压缩比 (CR) 和均方根差百分比 (PRD)，还基于 QRS 检测的准确性。本文提出了一种有损方法（方法 III），并将其与最新的无损和有损 ECG 压缩方法（方法 I 和方法 II）进行了比较。在所提出的有损压缩方法（方法 III）中，在 MIT-BIH 心律失常数据库上实现了 4.5×的压缩比、0.53 的 PRD，以及 99.78%的整体灵敏度和 99.92%的阳性预测率（与现有的 QRS 检测算法相结合），在 QT 数据库上实现了 99.90%的整体灵敏度和 99.84%的阳性预测率。
