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A Review:Sources Extraction from Mixed Sound Signals


Affiliations
1 Department of Electronics & Telecommunication, Sinhgad College of Engineering, Pune (MH), India
     

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The sound observed by physician from chest cavity consists of mixed lung and heart sound. They observe the changes in sound for detection of abnormality. Now a day's digital stethoscope is used in hospitals for patients monitoring. Its waveform is mixed with ambient noise and overlapped by vibrations from movement of body. The Fast ICA (independent component analysis) is source division procedure known as blind source separation technique. It is iterative and capable of dividing heart and lung sound giving physically important sources whenever physical mixing of two or more independent sources takes place. Noise reduction will be the very important initial stage in this algorithm as raw captured data contains most of the surface contact noise between stethoscope and chest surface. This algorithm will function as sound extractor from mixed heart and lung sound for its advanced examination which can be utilized to perceive diseases.

Keywords

Blind Source Separation, Lung Sound, Heart Sound, Auscultation, Independent Component Analysis.
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  • A Review:Sources Extraction from Mixed Sound Signals

Abstract Views: 189  |  PDF Views: 2

Authors

Anurag A. Ballewar
Department of Electronics & Telecommunication, Sinhgad College of Engineering, Pune (MH), India
S. D. Lokhande
Department of Electronics & Telecommunication, Sinhgad College of Engineering, Pune (MH), India

Abstract


The sound observed by physician from chest cavity consists of mixed lung and heart sound. They observe the changes in sound for detection of abnormality. Now a day's digital stethoscope is used in hospitals for patients monitoring. Its waveform is mixed with ambient noise and overlapped by vibrations from movement of body. The Fast ICA (independent component analysis) is source division procedure known as blind source separation technique. It is iterative and capable of dividing heart and lung sound giving physically important sources whenever physical mixing of two or more independent sources takes place. Noise reduction will be the very important initial stage in this algorithm as raw captured data contains most of the surface contact noise between stethoscope and chest surface. This algorithm will function as sound extractor from mixed heart and lung sound for its advanced examination which can be utilized to perceive diseases.

Keywords


Blind Source Separation, Lung Sound, Heart Sound, Auscultation, Independent Component Analysis.