Identification of the Normal/Abnormal Heart Sounds Based on Energy Features and Xgboost
A normal/abnormal heart sound identification method was put forward in the paper. The wavelet packet energy features of the heart sounds were extracted in a large database of 1136 recordings and xgboost algorithm was used as the classifier. The feature importance is also evaluated and analyzed. Top 3, 6, 9 and 12 features were used to classify the heart sounds. Experimental results showed that the proposed algorithm can identify the normal and abnormal heart sounds effectively. And the result used top 9 features was as good as that of all features, which can reduce almost half of computation.
KeywordsHeart sounds Identification Wavelet packet energy Xgboost Feature importance
This work was supported in part by the National Natural Science Foundation of China under Grant Nos. 61601081, 61471081; Fundamental Research Funds for the Central Universities under Grant Nos. DC201501056, DCPY2016008, DUT15QY60, DUT16QY13; Dalian Youth Technology Star Project Supporting Plan under Grant No. 2015R091.
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