Optimising arrhythmia detection for exercise sessions of cardiac patients

Lifestyle management, and especially exercise, is central in cardiac disease management and in well-being for the elder population. In the case of cardiac patients, exercise within a beneficial zone is recommended, while safety should be also ensured. This work focuses on complication detection during exercise, to be used in pervasive applications monitoring vitals during activity. A lightweight RR-based arrhythmia detector is employed. Taking into account the modified dynamics of heart rate during exercise, adaptations are proposed corresponding to changes in activity levels. ECG beats are characterized as normal or arrhythmic, allowing the screening of subject´s condition and the further offline analysis of the annotated beats. This approach constitutes a step towards enabling context based adaptations in the patient monitoring algorithms.