Data Driven Approach to ECG Signal Quality Assessment using Multistep SVM Classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00182536" target="_blank" >RIV/68407700:21230/11:00182536 - isvavai.cz</a>
Result on the web
<a href="http://www.cinc.org/2011/preprints/69.pdf" target="_blank" >http://www.cinc.org/2011/preprints/69.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Data Driven Approach to ECG Signal Quality Assessment using Multistep SVM Classification
Original language description
In response to the PhysioNet/CinC Challenge 2011: Improving the quality of ECGs collected using mobile phones we have developed an algorithm based on a decision support system. It combines couple of simple rules - in order to discard recordings of obviously low quality (i.e. highamplitude noise, detached electrodes) with more sophisticated support vector machine (SVM) classification that deals with more difficult cases where simple rules are inefficient. It turns out that complicatedly computed featuresprovide only small information gain and we used for SVM classifier only time-lagged covariance matrix elements, which provides useful information about signal structure in time.Our results are 0.836.
Czech name
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Czech description
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Project
<a href="/en/project/1ET201210527" target="_blank" >1ET201210527: Knowledge-based support of diagnostics and prediction in cardiology</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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