Isolation of F-Wave From Electrocardiogram Using New LMS Algorithm

Abstract

The electrocardiogram F-wave arising from atrial electrical activity is an important global measure for assessment of atrial¯brillation (AF). However, successful F-wave extraction from the ventricular waveform can be problematic. Herein, a new F-wave isolation technique is introduced. For analysis, electrocardiogram lead I (termed un¯ltered or UNF-signals) was retrospectively analyzed (39 AF patients, 8.4-s recordings, 8192 sample points, 96 recordings in total). To measure the e±cacy of isolation techniques, a synthetic F-wave (7.29 Hz) and an interference were added to each electrocardiogram signal. In the resulting composite signals, the average electrocardiogram QRST complex template was subtracted from each actual QRST (AVG-isolation). The QRST template was also adjusted using a new adaptive least mean-squares (LMS) algorithm, and subtracted from each actual QRST (termed LMS-isolation). Four spectral parameters were measured to assess isolated F-wave quality: the dominant amplitude (DA), dominant frequency (DF) and mean/standard deviation in spectral pro¯le (MP/SP). Signi¯cant parameter di®erences between UNF/LMS and between AVG/LMS were determined. The electrocardiogram F-wave spectral parameters were sig-ni¯cantly improved by incorporating LMS-isolation as compared to no isolation ( p < 0:001). The F-wave spectral parameters were also signi¯cantly improved using LMS-isolation as compared with AVG-isolation (DA/MP/SP: p < 0:001; DF: p < 0:05). The DF was correctly identi¯ed as 7:29 AE 0:10 Hz using ensemble spectral analysis with the following percentages (UNF: 24.0%, AVG: 69.8%, LMS: 80.2%), and Fourier spectral analysis with the following percentages (UNF: 15.6%, AVG: 60.4%, LMS: 75.0%). The LMS algorithm is helpful to isolate the electrocardiogram F-wave from the ventricular component as measured by spectral analysis, when compared to the use of an average QRST subtraction template.