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Research on Methods of Feature Extraction and Recognition of Two-Dimensional Phonocardiogram

Abstract: The one-dimensional heart sound signal is converted into a two-dimensional#br# phonocardiogram, then image feature of heart sounds based on image processing technology in a#br# two-dimensional phonocardiogram is extracted. Firstly the wavelet noise reduction and amplitude#br# normalization of one-dimensional heart sound by one-dimensional signal processing method are#br# realized, and then heart sounds after the treatment are converted into two-dimensional#br# phonocardiogram with uniformity and comparability, and pretreatment. And the image#br# characteristics of two-dimensional phonocardiogram are analyzed, which is characterization of#br# heart sounds’ physiological information combining with heart sounds’ physiological significance#br# and two-dimensional phonocardiogram’s image features, and the focus is on vertical and#br# horizontal ratio of coordinate and sequence code of inflection point. At last, the feasibility of#br# classification and identification is explored of 2D-PCG using Euclidean distance and Support#br# Vector Machine (SVM) based on vertical and horizontal ratio of coordinate, sequence code of#br# inflection point and wavelet coefficients. Experimental results show that the three features can#br# achieve the classification and recognition of the two-dimensional phonocardiogram, and inflection#br# point sequence code gets the highest recognition rate. The method of 2D-PCG classification and#br# identification based on a two- image processing has the feasibility and practical applicability, and#br# has broad application prospects.#br# Key words: two-dimensional phonocardiogram; image processing; feature extraction;#br# recognition   

  • Online:2015-04-30 Published:2015-03-30

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Abstract: The one-dimensional heart sound signal is converted into a two-dimensional
phonocardiogram, then image feature of heart sounds based on image processing technology in a
two-dimensional phonocardiogram is extracted. Firstly the wavelet noise reduction and amplitude
normalization of one-dimensional heart sound by one-dimensional signal processing method are
realized, and then heart sounds after the treatment are converted into two-dimensional
phonocardiogram with uniformity and comparability, and pretreatment. And the image
characteristics of two-dimensional phonocardiogram are analyzed, which is characterization of
heart sounds’ physiological information combining with heart sounds’ physiological significance
and two-dimensional phonocardiogram’s image features, and the focus is on vertical and
horizontal ratio of coordinate and sequence code of inflection point. At last, the feasibility of
classification and identification is explored of 2D-PCG using Euclidean distance and Support
Vector Machine (SVM) based on vertical and horizontal ratio of coordinate, sequence code of
inflection point and wavelet coefficients. Experimental results show that the three features can
achieve the classification and recognition of the two-dimensional phonocardiogram, and inflection
point sequence code gets the highest recognition rate. The method of 2D-PCG classification and
identification based on a two- image processing has the feasibility and practical applicability, and
has broad application prospects.

Key words: two-dimensional phonocardiogram, image processing, feature extraction;
recognition