Aims: Our aim is to improve the accuracy of existing heart beatdetection algorithms in order to provide reliable heart beat locations in a multi-modal beatdetectionscheme. Methods: A rhythm-based algorithm is prese...
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ISBN:
(纸本)9781479943463
Aims: Our aim is to improve the accuracy of existing heart beatdetection algorithms in order to provide reliable heart beat locations in a multi-modal beatdetectionscheme. Methods: A rhythm-based algorithm is presented which on top of a base beatdetection method processes the detected beats by rejecting annotations and filling in gaps while minimizing a deviation score. A novel beatdetection method based on rational modelling of ECG signals is also presented as a base algorithm. Results: The rhythm-correction algorithm applied to Sachin Vernekar's phase 11 entry was submitted to the third phase of the PhysioNetlCinC Challenge 2014 contest. The algorithm has 99.98% gross and average sensitivity and 99.96% gross and average positive predictivity compared to 99.92% and 99.94%, respectively, of the base algorithm. Due to run-time performance problems, the rational algorithm was not able to qualify in the contest. Conclusions: The rhythm-based method improves the results of the base algorithm on the training data set. The hidden records are not yet available at the time of writing of this paper;therefore we are not able to report the final performance of the algorithm. Run-time improvement of the rational algorithm remains future work.
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