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Titlebook: Computational Pulse Signal Analysis; David Zhang,Wangmeng Zuo,Peng Wang Book 2018 Springer Nature Singapore Pte Ltd. 2018 Computational Pu

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發(fā)表于 2025-3-23 13:34:11 | 只看該作者
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發(fā)表于 2025-3-23 13:58:57 | 只看該作者
Detection of Saturation and Artifact. Some of the corrupted pulse signals can be recovered via preprocessing, but several types of corrupted pulse signals would be difficult to recover and should be removed from the pulse signal dataset. Therefore, low-quality pulse signal detection plays an important role in computational pulse diagn
13#
發(fā)表于 2025-3-23 19:56:31 | 只看該作者
14#
發(fā)表于 2025-3-23 22:16:33 | 只看該作者
Arrhythmic Pulse Detection two rules, which are the results of heuristic approach, are presented. This approach is applied on 140 clinic pulses for detecting 7 pulse patterns, not only achieving a recognition accuracy of 97.1% as assessed by experts in TCM but also correctly extracting the periodical unit of the intermittent
15#
發(fā)表于 2025-3-24 05:25:38 | 只看該作者
Spatial and Spectrum Feature Extractionlected using Doppler ultrasound device and preprocessed. Then, by locating the fiducial points, we extract the spatial features of blood flow velocity signal and further present a Hilbert-Huang transform-based method for spectrum feature extraction. Finally, support vector machine is applied for com
16#
發(fā)表于 2025-3-24 10:08:59 | 只看該作者
17#
發(fā)表于 2025-3-24 11:58:34 | 只看該作者
18#
發(fā)表于 2025-3-24 15:37:16 | 只看該作者
Edit Distance for Pulse Diagnosise two novel ERP-based KNN classifiers. Taking advantage of the metric property of ERP, we first develop an ERP-induced inner product and a Gaussian ERP kernel, then embed them into difference-weighted KNN classifiers, and finally develop two novel classifiers for pulse waveform classification. The e
19#
發(fā)表于 2025-3-24 22:45:49 | 只看該作者
20#
發(fā)表于 2025-3-25 01:23:54 | 只看該作者
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