Aim: The aim of this study was the reduction of false arrhythmia alarms and improvement in the accuracy of calculated heart rates (HR) in real-time patient monitors by the fusion of information from ECG and SpO2 signals. Methods: ECG and SpO2 signals were independently analyzed to derive features for use in the fusion analysis. Information regarding the detection and classification of QRSs, signal quality, HR and arrhythmia alarms were obtained from the ECG. Pulses, signal quality, pulse rate (PR) and hemodynamic parameters were obtained from SpO2. Independent results from each signal were confirmed by the fusing features from both. When an arrhythmia alarm was triggered, corresponding SpO2 features were checked to determine whether the alarm should be accepted or rejected. HR and PR reliability was estimated using signal quality while QRSs and SpO2 pulses were matched to exclude spurious beats due to motion or other artifacts. Thus, calculated HR and PR were more accurate and false HRs from noisy ECG signals could be supplanted by the pulse rate if noise free. Results: Adult, pediatric and neonate ECG signals were collected to make up training and test databases. The false alarm suppression was over 50% for all arrhythmia calls while it was over 60% for life threatening alarms. No life-threatening arrhythmia alarm was mistakenly rejected by fusion analysis. The HR and PR became more reliable and accurate HRs could be made available even when noise and artifact completely corrupted the ECG signals while clean SpO2 signals existed. False HR/PR were reduced by 80%. Conclusion: The fusion analysis of ECG and SpO2 signals, effectively reduced false arrhythmia alarms and enhanced the accuracy of HR and PR thus increased the quality of clinical monitoring. Since the fusion analysis used was a real-time dynamic process, it can easily be used in multi-parameter patient monitors.