Automatic Electrocardiogram Detection of Suspected Hypertrophic Cardiomyopathy: Application to Wearable Heart Monitors

In this work, an automatic detection algorithm for hypertrophic cardiomyopathy (HCM) is presented. Of particular interest is the algorithm’s ability to differentiate HCM subjects and healthy volunteers from a single lead ECG dataset. Suspected HCM subjects are identified by the primary clinical abnormality associated with HCM, left ventricular hypertrophy (LVH). In total, n =43 human subjects ECG datasets are investigated: n =21 healthy volunteers and n =22 left ventricular hypertrophy (LVH) patients. Significant differences of p -value 0.01 and 0.04 were found for the respective ECG parameters, S-wave amplitude and ST-segment, when differentiating between the LVH patients and healthy human volunteers.