Shafi et al., 2022 - Google Patents
Reduced features set neural network approach based on high-resolution time-frequency images for cardiac abnormality detectionShafi et al., 2022
- Document ID
- 1685527292396247974
- Author
- Shafi I
- Aziz A
- Din S
- Ashraf I
- Publication year
- Publication venue
- Computers in biology and medicine
External Links
Snippet
A suitable temporal and spectral processing of the electrocardiogram (ECG) signals can facilitate the visual interpretation and discrimination between known patterns for classification. This paper proposes a non-invasive hybrid neural network and time-frequency …
- 238000001514 detection method 0 title abstract description 43
Classifications
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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- G—PHYSICS
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- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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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
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- A—HUMAN NECESSITIES
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