Shluková analýza EKG
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU141772" target="_blank" >RIV/00216305:26220/19:PU141772 - isvavai.cz</a>
Result on the web
<a href="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf" target="_blank" >https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf</a>
DOI - Digital Object Identifier
—
Alternative languages
Result language
čeština
Original language name
Clustering of ECG cycles
Original language description
The study is focused on a design of a reliable approach for ECG cycles clustering. It would be helpful for automatic assessment of various pathological patterns in ECG. Proposed method was tested and tuned on real data from ambulatory ECG database. The algorithm comprises ECG preprocessing, adjustment of R-peak positions available in database, creation of a template cycle, computation of features mainly representing correlation between particular cycles and the template, and, clustering of cycles within ECG via k-means. The appropriate number of clusters is derived via analysis of silhouette values. Resulting success of the algorithm in comparison with available manual scoring is: Sensitivity = 0.55 and Specificity=0.94.
Czech name
Clustering of ECG cycles
Czech description
The study is focused on a design of a reliable approach for ECG cycles clustering. It would be helpful for automatic assessment of various pathological patterns in ECG. Proposed method was tested and tuned on real data from ambulatory ECG database. The algorithm comprises ECG preprocessing, adjustment of R-peak positions available in database, creation of a template cycle, computation of features mainly representing correlation between particular cycles and the template, and, clustering of cycles within ECG via k-means. The appropriate number of clusters is derived via analysis of silhouette values. Resulting success of the algorithm in comparison with available manual scoring is: Sensitivity = 0.55 and Specificity=0.94.
Classification
Type
O - Miscellaneous
CEP classification
—
OECD FORD branch
20601 - Medical engineering
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů