Jin et al., 2009 - Google Patents
Predicting cardiovascular disease from real-time electrocardiographic monitoring: An adaptive machine learning approach on a cell phoneJin et al., 2009
- Document ID
- 10981805283948171914
- Author
- Jin Z
- Sun Y
- Cheng A
- Publication year
- Publication venue
- 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
External Links
Snippet
To date, cardiovascular disease (CVD) is the leading cause of global death. The Electrocardiogram (ECG) is the most widely adopted clinical tool that measures the electrical activities of the heart from the body surface. However, heart rhythm irregularities cannot …
- 208000008787 Cardiovascular Disease 0 title abstract description 25
Classifications
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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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- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
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