An expert electrocardiogram quality evaluation algorithm based on signal mobility factors.

The major concentration of this study is to describe and to develop a new electrocardiogram (ECG) signal measurement binary quality assessment (accept-reject) technique. The proposed algorithm is composed of three major stages: pre-processing, signal mobility-based quality measurement and advanced post-evaluation. The pre-processing step includes baseline wander and high-frequency disturbances removal. The signal mobility-based quality measurement routine includes two separate stages based on energy and concavity of the ECG signal. The post-evaluation quality measurement step is mainly based on the six features inferenced from heuristic experiences and human thinking models. The proposed technique was applied to the test dataset provided by the PhysioNet Computing in Cardiology (CinC) challenge 2011 and accuracy 93.40% was achieved which shows the marginal improvement in this field.