A cardiac arrhythmia monitoring platform based on feature selection and classification methods
Heart arrhythmia, also known as irregular heartbeat, affects millions of people around the world. One of the ways to detect this cardiac dysrhythmia is by performing an electrocardiogram (ECG) exam which records the electrical activity of the heart. However, this type of exam is always interpreted by a doctor. In order to provide an alternative in heart arrhythmia diagnosis, this paper aims at developing a platform based on Internet of Things infrastructure capable of automatically monitoring and identifying cardiac arrhythmia based on feature selection and classification methods.