Classification of Heart Sound Recordings With Continuous Wavelet Transform Based Algorithm
Tarih
2018Yazar
Karaca, Busra Kubra
Oltu, Burcu
Kantar, Tugce
Kilic, Erkin
Aksahin, Mehmet Feyzi
Erdamar, Aykut
Üst veri
Tüm öğe kaydını gösterÖzet
Cardiovascular diseases are the major cause of death in the world. Early diagnosis of heart diseases provide an effective treatment. Heart diseases can be diagnosed using data obtained from heart sounds. Heart sounds are listened by a physician with auscultation method and the disease diagnosis can vary depending on the physician's experience and hearing ability. For this reason, automatic detection of anomalies in heart sounds can give more objective results. In this study, features were obtained by processing phonocardiogram signals taken from Physionet database. The heart sounds are classified as normal and abnormal using these features and the k - nearest neighbor method. As a result, sensitivity, specificity and accuracy were determined as 100%, 96.1% and 98.2%, respectively.