Patients undergoing non-cardiac surgery can have an elevated risk of cardiac complication. Myocardial ischemia, a lack of oxygen in the heart tissue, can precede these complications and is detectable via changes in a patient`s electrocardiogram (ECG). Excessive noise during mobile ECG monitoring can result in frequent false detection of ischemia, rendering mobile ischemia detection clinically impractical. This thesis investigates modification of alarms on the basis of signal quality to increase the positive predictive value (PPV) of mobile ischemia detection. First, methods are presented and
validated to automatically quantify ECG signal quality in a single ECG lead via a signal quality index (SQI). This thesis then proposes and evaluates three system approaches to modifying alarms using this SQI. Resulting modified alarms reveal increased PPV from 0.41 to 0.85 while maintaining sensitivity. These results indicate that these methods could help provide for practical mobile monitoring ischemia monitoring.