In this paper, we describe a QRS complex detector based on the dyadic wavel
et transform (D-g WT) which is robust to time-varying QRS complex morpholog
y and to noise. We design a spline wavelet that is suitable for QRS detecti
on. The scales of this wavelet are chosen based on the spectral characteris
tics of the electrocardiogram (ECG) signal. We illustrate the performance o
f the D-y WT-based QRS detector by considering problematic ECG signals from
the American Heart Association (AHA) data base. Seventy hours of data was
considered. We also compare the performance of D-y WT-based QRS detector wi
th detectors based on Okada, Hamilton-Tompkins, and multiplication of the b
ackward difference algorithms. From the comparison, results we observed tha
t although no one algorithm exhibited superior performance in all situation
s, the D-y WT-based detector compared well with the standard techniques. Fo
r multiform premature ventricular contractions, bigeminy, and couplets tape
s, the D-y WT-based detector exhibited excellent performance.