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Wang et al., 2020 - Google Patents

Application of multi-feature fusion and random forests to the automated detection of myocardial infarction

Wang et al., 2020

Document ID
7795943474847957338
Author
Wang Z
Qian L
Han C
Shi L
Publication year
Publication venue
Cognitive Systems Research

External Links

Snippet

Myocardial infarction (MI) was one of the most threatening cardiovascular diseases due to its suddenness and high mortality. Electrocardiography (ECG) reflected the electrophysiological activity of the heart which was widely used for the diagnosis of MI. The …
Continue reading at www.sciencedirect.com (other versions)

Classifications

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    • A61B5/7235—Details of waveform analysis
    • A61B5/7253—Details of waveform analysis characterised by using transforms
    • A61B5/726—Details of waveform analysis characterised by using transforms using Wavelet transforms
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    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402—Electrocardiography, i.e. ECG
    • A61B5/0452—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/0468—Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
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    • A61B5/046—Detecting fibrillation
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    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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