An algorithm for sleep apnea detection from single-lead ECG using Hermite basis functions

On the other hand, an accuracy of about 97.14% is achieved for per-recording classification using the SVM, and LS-SVM classifiers. From the results, it is observed that the proposed methodology provides comparable accuracy with the methods existing in the literature at reduced computational cost due to the lesser number of features selected for the classification.