Methods for automatically determining whether a patient monitor alarm will sound from a true or false signal, in particular from ventricular tachycardia (VT) and suppressing false alarms without eliminating any true alarms are presented. A multiresolution wavelet is extracted from a raw ECG waveform. Features are then extracted from the wavelets that account for summary statistics, noise, areas under the curve and summary statistics of the KL-divergence of the power spectra density between every two ECG leads. A classifier can be then be trained and its performance measured.
