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Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems

机译:重新审视便携式,可穿戴式,电池供电和无线ECG系统的QRs检测方法

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摘要

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices.
机译:心血管疾病是全球范围内第一大死亡原因。当前,诸如带有无线ECG传感器的手机之类的便携式电池供电系统具有用于连续心脏功能评估的潜力,该评估可以轻松地融入日常生活。因此,这些便携式即时诊断系统可以帮助揭示和治疗心血管疾病。 ECG分析的基础是对突出的QRS复合信号以及其他ECG信号特征的可靠检测。但是,从文献中尚不清楚哪种ECG分析算法适合在移动设备上实现。我们基于三个评估标准研究当前的QRS检测算法:1)抗噪声的鲁棒性; 2)参数选择; 3)数值效率,以针对通用的快速鲁棒检测器。此外,现有的QRS检测算法可以仅在一定幅度范围内或在特定类型的心律不齐和/或噪声之中的ECG信号的小片段上提供可接受的解决方案。在与最常规算法进行比较的背景下讨论了这些问题,随后提出了开发适用于电池供电的移动设备的可靠QRS检测方案的未来建议。

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