System and method for classifying a heart sound
AssigneeDiacoustic Medical Devices (Pty) Ltd
InventorsEugene Pretorius, Otto Marsél Strydom, Matthys Louwrens Cronje
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Abstract
A method and system for electronically classifying a pre-processed heart sound signal of a patient as functional (normal) or pathological is provided. The pre-processed patient heart sound signal is segmentised and features are extracted therefrom (104) to build up a feature vector which is representative of the heart sound signal. The feature vector is then fed to a diagnostic decision support network (105) comprising a plurality of artificial neural networks, each relating to a known heart pathology, which is in turn used to conduct the classification.
Claims14
A computer-implemented method of classifying, a recorded, digitized acoustic heart sound signal of a patient, the heart sound signal having been pre-processed so as to be parsed into respective heart beat cycles with S1 and S2 heart sounds identified, the method being performed by a computing device and including the steps of:
- by a computing device, segmenting and extracting features from heart beat cycles making up the heart sound signal and compiling the extracted features into a feature vector, the extracted features including at least energy features extracted by utilizing a power spectrum calculation conducted on the heart beat cycles of the heart sound signal, and frequency domain features extracted by utilizing a frequency domain transformation of the heart beat cycles of the heart sound signal;
- feeding, by a computing device, the feature vector into a network of a plurality of artificial neural networks, each artificial neural network being associated with a specific pathology and being trained with at least features extracted from similarly pre-processed heart sound signals associated with the specific pathology;
- determining, by a computing device, whether the heart sound signal exemplifies features corresponding to the artificial neural network associated with any one or more of the pathologies;
- and
- classifying, by a computing device, the heart sound signal as normal or containing a murmur associated with one or more of the pathologies according to the determination.
A system for classifying a recorded. digitized acoustic heart sound signal of a patient, the heart sound signal having been pre-processed so as to be parsed into respective heart beat cycles with S1 and S2 heart sounds identified, the system including at least one processing circuit and a computer-readable non-transitory medium coupled to the processing circuit, the computer-readable medium comprising code executable by the processing, circuit for implementing a method comprising:
- receiving, by a computing device, the heart sound signal;
- by a computing device, segmenting and extracting, features from heart beat cycles making up the heart sound signal and compiling the extracted features into a feature vector, the extracted features including at least energy features extracted by utilizing a power spectrum calculation conducted on the heart beat cycles of the heart sound signal, and frequency domain features extracted by utilizing, a frequency domain transformation of the heart beat cycles of the heart sound signal;
- feeding, by a computing device, the feature vector into a network of a plurality of artificial neural networks, each artificial neural network being associated with a specific pathology and being trained with at least features extracted from similarly pre-processed heart sound signals associated with the specific pathology;
- determining, by a computing device, whether the heart sound signal exemplifies features corresponding to the artificial neural network associated with any one or more of the pathologies;
- and
- classifying, by a computing device, the heart sound signal as normal or containing a murmur associated with one or more of the pathologies according to the determination.
Dependencies are inferred from the claim text.