The Mobile Medical Service Based on the Analysis of Automatic Diagnosis of Holter Electrocardiogram Data

In this paper, we consider the mobile medical service from the perspective of diagnosis of electrocardiogram (ECG) signal, and expect to promote the development of mobile medical service through the implementation of automatic diagnosis of ECG. We focus on the main problem during the procedure of implementing the automatic diagnosis, which is illustrated with ECG clinical data. And we propose a hierarchical clustering method based on tree structure to improve the results of ECG pattern classification. The simulation results on clinical data collected by smart device such as Holter, reveal that the tree-like hierarchical clustering method can effectively detect abnormal heart beat from ECG data set.