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Irena Jekova

Researcher at Bulgarian Academy of Sciences

Publications -  86
Citations -  1556

Irena Jekova is an academic researcher from Bulgarian Academy of Sciences. The author has contributed to research in topics: Cardiopulmonary resuscitation & QRS complex. The author has an hindex of 20, co-authored 82 publications receiving 1337 citations.

Papers
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Comparative study of morphological and time-frequency ECG descriptors for heartbeat classification.

TL;DR: A comparative study of the heartbeat classification abilities of two techniques for extraction of characteristic heartbeat features from the ECG: QRS pattern recognition method for computation of a large collection of morphological QRS descriptors and Matching Pursuits algorithm for calculation of expansion coefficients, which represent the time-frequency correlation of the heartbeats with extracted learning basic waveforms.
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Premature ventricular contraction classification by the Kth nearest-neighbours rule.

TL;DR: An analysis of electrocardiographic pattern recognition parameters for premature ventricular contraction (PVC) and normal (N) beat classification is presented and the achieved specificity and sensitivity are comparable with, and greater than, the results reported in the literature.
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Assessment and comparison of different methods for heartbeat classification.

TL;DR: A comparative study of the learning capacity and the classification abilities of four classification methods--Kth nearest neighbour rule, neural networks, discriminant analysis and fuzzy logic is presented.
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QRS template matching for recognition of ventricular ectopic beats.

TL;DR: The provided computationally efficient techniques enable the fast post-recording analysis of lengthy Holter-monitor ECG recordings, as well as they can serve as a quasi real-time detection method embedded into surface ECG monitors.
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Real time detection of ventricular fibrillation and tachycardia.

TL;DR: An algorithm for VF/VT detection is proposed using a band-pass digital filter with integer coefficients, which is very simple to implement in real-time operation and tested with ECG records from the widely recognized databases.