A Robust Beat-to-Beat Artifact Detection Algorithm for Pulse Wave

Hu Qihan; Deng Xintao; Liu XinWang AiguoYang Cuiwei

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A Robust Beat-to-Beat Artifact Detection Algorithm for Pulse Wave

机译：A Robust Beat-to-Beat Artifact Detection Algorithm for Pulse Wave

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With the rise of the concept of smart cities and healthcare, artificial intelligence helps people pay increasing attention to the health of themselves. People can wear a variety of wearable devices to monitor their physiological conditions. The pulse wave is a kind of physiological signal which is widely applied in the physiological monitoring system. However, the pulse wave is susceptible to artifacts, which prevents its popularization. In this work, we propose a novel beat-to-beat artifact detection algorithm, which performs pulse wave segmentation based on wavelet transform and then detects artifacts beat by beat based on the decision list. We verified our method on data acquired from different databases and compared with experts' annotations. The segmentation algorithm achieved an accuracy of 96.13%. When it is applied to detect main peaks, the performance achieved an accuracy of 99.11%. After the previous segmentation algorithm, the artifact detection algorithm can detect beat-to-beat pulse waves and artifacts with an accuracy of 98.11%. The result indicated that the proposed method is robust for pulse waves of different patterns and could effectively detect the artifact without the complex algorithm. In summary, our proposed algorithm is capable of annotating pulse waves of various patterns and determining pulse wave quality. Since our method is developed and evaluated on the transmission-mode PPG data, it is more suitable for the devices and applications inside the hospitals instead of reflectance-mode PPG.

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《Mathematical Problems in Engineering: Theory, Methods and Applications》 |2020年第41期|5691805.1-5691805.8|共8页
作者
Hu Qihan; Deng Xintao; Liu XinWang AiguoYang Cuiwei;
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作者单位

Fudan Univ, Dept Elect Engn, Shanghai 200433, Peoples R China;

Xinghua City Peoples Hosp, Dept Cardiol, Changzhou 225700, Jiangsu, Peoples R China;

Fudan Univ, Dept Elect Engn, Shanghai 200433, Peoples R China|Shanghai Engn Res Ctr Cardiac Electrophysiol, Key Lab Med Imaging Comp & Comp Assisted Interven, Shanghai 201318, Peoples R China;

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A Robust Beat-to-Beat Artifact Detection Algorithm for Pulse Wave

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