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This study assessed the feasibility of using multimodal data, namely ECG, ABP and PLETH for reducing the incidence of false alarms in the Intensive Care Unit (ICU) for the PhysioNet/Computing in Cardiology 2015 Challenge. Our approach relies on the annotation of heartbeats using all available channels for each alarm recording. In addition, we also combine ECG and ABP/PLETH channels to create additional signals for analysis. The heartbeat annotations are performed using the gqrs and wabp routines in the WFDB toolbox as well as our in-house algorithm. For ventricular tachycardia alarms, the morphology of the ECG signals for a specified window centered on the annotated heartbeats are also analyzed. Subsequently, the intervals between heartbeats are computed for each channel and for the combined signals. A majority voting scheme with an alarm-specified threshold optimized to the training dataset is …