TY - JFULL AU - Christer Ahlstrom and Katja H枚glund and Peter Hult and Jens H盲ggstr枚m and Clarence Kvart and Per Ask PY - 2008/7/ TI - Distinguishing Innocent Murmurs from Murmurs caused by Aortic Stenosis by Recurrence Quantification Analysis T2 - International Journal of Biomedical and Biological Engineering SP - 200 EP - 206 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/2998 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 18, 2008 N2 - It is sometimes difficult to differentiate between innocent murmurs and pathological murmurs during auscultation. In these difficult cases, an intelligent stethoscope with decision support abilities would be of great value. In this study, using a dog model, phonocardiographic recordings were obtained from 27 boxer dogs with various degrees of aortic stenosis (AS) severity. As a reference for severity assessment, continuous wave Doppler was used. The data were analyzed with recurrence quantification analysis (RQA) with the aim to find features able to distinguish innocent murmurs from murmurs caused by AS. Four out of eight investigated RQA features showed significant differences between innocent murmurs and pathological murmurs. Using a plain linear discriminant analysis classifier, the best pair of features (recurrence rate and entropy) resulted in a sensitivity of 90% and a specificity of 88%. In conclusion, RQA provide valid features which can be used for differentiation between innocent murmurs and murmurs caused by AS. ER -