High-Speed Feature Extraction in Holter Electrocardiogram Using Principal Component Analysis

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03099085" target="_blank" >RIV/68407700:21230/04:03099085 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
High-Speed Feature Extraction in Holter Electrocardiogram Using Principal Component Analysis
Original language description
Due to their long duration (up to 48 hours) and because of the enormous quantity of beats involved, it results really difficult to perform a manual inspection of HOLTER electrocardiographic signals (ECG). In the other side, we have patients with chronicheart-troubles whose heart rithm needs to be checked everytime using portable ECG recording machines. Within this scenario it would be very interesting the possibility of real-time ANALYZING and clustering ECG records in order to detect arrhythmia beatsas soon as possible, allowing the patient to realize and prevent from a critical heart attack. To achieve this goal we have designed and implemented a C++ application that is based on the Principal Component Analysis (PCA) method applied to the beats (from a portable ECG recording machine) to decompose and cluster them in real-time. At the first stage of this article we will define holter ECG records and discuss about their desirable features for processing them ensuring better results y
Czech name
Není k dispozici
Czech description
Není k dispozici

Publication year
2004
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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