Date

2006

Author

Tanrıverdi, Volkan

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ECG measures electrical potentials on the body surface via contact electrodes. Conditions such as movement of the patient, breathing, and interaction between the electrodes and skin cause baseline wandering of the ECG signal. Baseline wandering noise can mask some important features of the ECG signal; hence it is desirable to remove this noise for proper analysis of the ECG signal. This study includes an implementation and evaluation of methods to remove this noise, such as finite impulse response filters, infinite impulse response filters, interpolation filters and adaptive filters. These filters are first applied offline to simulated ECG data. The filter outputs and their frequency spectra are compared to the pure ECG signal and its frequency spectrum using visual inspection and numerical evaluation criteria such as root mean squared error and percentage root relative squared error. The best filters are then selected and applied online to the same simulated data. Finally, these best methods are used to suppress the baseline wandering noise in real ECG recordings using both offline and online filtering. In the offline application, windowing type filters were found to be the most successful filters among the implemented filters. However, a high filter order should be used to produce such good results, which increases the computation time, thus it may not be the best method for online filtering, in which fast computation is essential. Butterworth bidirectional type is preferred for online filtering since it has lower computational complexity, and it produces acceptable results.

Subject Keywords

Electrical Engineering., Electronics., Nuclear Engineering.

URI

http://etd.lib.metu.edu.tr/upload/12607687/index.pdf
https://hdl.handle.net/11511/16033

Collections

Graduate School of Natural and Applied Sciences, Thesis