Automatic quality classification of entire electrocardiographic recordings obtained with a novel patch type recorder

Recently, new patch type electrocardiogram (ECG) recorders have reached the market. These new devices possess a number of advantages compared to the traditional Holter recorders. This forms the basis of questions related to benefits and drawbacks of different ambulatory ECG recording techniques. One of the important questions is the ability to obtain high clinical quality of the recordings during the entire monitoring period. It is thus desirable to be able to obtain an automatic estimate of the global quality of entire ECG recordings. The purpose of this pilot study is therefore to design an algorithm for automatic classification of entire ECG recordings into the groups "noisy" and "clean" recordings. This novel algorithm is based on three features and a simple Bayes classifier. The algorithm was tested on 40 ECG recordings in a five-fold cross validation scheme and it obtained an average accuracy of 90% on the test data.