Title: Heart Sounds Analysis and Classification Based on Long-Short Term Memory

Abstract: In this study, the development of an algorithm for the classification of heart sound phonocardiogram waveforms such as Normal, Murmur, Extrasystole, Artifact. By presenting the approach used for classification from a general machine learning application point of view, the types of classifiers used were detailed by comparing their features and their performance. The Long-Short Term Memory method which supports the classification of each cardiac cycle in sound recordings. In addition to the LSTM-based features, our method incorporates spectral features to summarize the characteristics of the entire sound recording.

Keywords: Heart sounds; classification; LSTM; RNN

Başlık: Uzun-Kısa Vade Hafıza Tabanlı Kalp Ritmi Analizi ve Sınıflandırması

Özet: Bu çalışmada, kalp sesi fonokardiyogram dalga formlarının Normal, Hırıltılı, Ekstrasistol ve Yapay gibi kategorilere sınıflandırılma çalışması yapılmıştır. Sınıflandırma için kullanılan yaklaşımı genel bir makine öğrenimi uygulama bakış açısından sunarak, özellik çıkarma, performanslarını karşılaştırarak kullanılan sınıflandırıcıların türleri detaylandırıldı. Çalışmada kullanılan Uzun-Kısa Vadeli Hafıza (LSTM) metodu, ses kayıtlarındaki her bir kardiyak döngünün sınıflandırılmasını destekler. LSTM tabanlı özelliklere ek olarak, yöntemimiz tüm ses kayıtlarının özelliklerini özetlemek için spektral özellikler içerir.

Anahtar kelimeler: Kalp ritmi; sınıflandırma; LSTM; RNN

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