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Subtraction of 16.67 Hz railroad net interference from the electrocardiogram: application for automatic external
Irena Jekova1, Vessela Krasteva
1Centre of Biomedical Engineering Prof. Ivan Daskalov, Bulgarian Academy of Science, Acad G Bonchev str Bl105, 1113 Sofia, Bulgaria. irena@clbme.bas.bg
Abstract:
The widespread application of automatic external defibrillators (AEDs) for treating out-of-hospital cardiac arrest incidents and their particular use at railway stations defines the task for 16.67 Hz power line interference elimination from the electrocardiogram (ECG). Although this problem exists only in five European countries, it has to be solved in all AEDs, which must comply with the European standard for medical equipment requirements for interchangeability and compatibility between rail systems. The elimination of the railroad interference requires a specific approach, since its frequency band overlaps with a significant part of the frequencies in the QRS spectra. We present a method based only on one channel ECG signal processing, which effectively subtracts the interference components. The computation procedure is based on simple signal processing tools, which include: (i) bi-directional band-pass filtering (13-23 Hz) of the analyzed ECG segment; (ii) estimation of adequate linearity thresholds; (iii) frequency measurement and calculation of dynamic interference buffer in linear segments and (iv) phase synchronization and subtraction technique in nonlinear segments. The developed method has proved advantageous in providing sufficient quality of the output interference free ECG signal for seven defined arrhythmia types (normal sinus rhythm, normal rhythm, supraventricular tachicardia, slow/rapid ventricular tachycardia, and coarse/fine ventricular fibrillation), and simulated interferences with constant or variable frequencies and amplitudes, which cover the entire amplitude range of the input channel. The procedure is suitable to be embedded in AEDs as a preprocessing branch, which proves reliable for analysis of ECG signals, thus guaranteeing the specified accuracy of the AED automatic rhythm analysis algorithms.
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