Separation of Heart Sounds & Lung Sounds using Independent Component Analysis
Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.
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Universiti Malaysia Perlis
2010
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my.unimap-75352010-01-21T01:31:51Z Separation of Heart Sounds & Lung Sounds using Independent Component Analysis B.HemaKumar R.Anandanatarajan mail2hemakumar@graffiti.net Human heart and lung sounds Electronic stethoscope Fuzzy expert system Independent component analysis Acoustical analysis Auscultation Heart -- Diseases -- Diagnosis Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. Auscultation is the most common way of physical examination of a patient by a physician. Recently, in order to develop automated home care system and to assist physician getting better auscultation results; electronic stethoscope and computer analysis have become an inevitable trend. On this account a fuzzy expert system based body sounds analysis kit designed by HemaKumar [1]. In this existing kit, the interface part design is the most important aspect. The problem with the existing design is that it needs separate channels for heart and lung sounds to be analyzed by the fuzzy model. Such separation of heart and lung sounds becomes very much important for an acute care physician in an ICCU (Intensive Coronary Care Unit). In this study, to separate the two signals, a novel Heart sound (HS) separation method based on Independent Component Analysis (ICA) is developed. This method applies an ICA algorithm to the spectrograms of two simultaneous lung sound recordings obtained at two different locations on the chest and yields the independent spectrograms of the separated signals. Then, by implementing the Inverse Short Time Fourier Transform, the separated signals are reconstructed in the time domain. The method was applied to data of 25 healthy subjects. Analysis of the results indicates the efficiency of the proposed method in terms of HS separation from lung sounds. 2010-01-21T01:30:58Z 2010-01-21T01:30:58Z 2009-10-11 Working Paper p.1C4 1 - 1C4 5 http://hdl.handle.net/123456789/7535 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009) Universiti Malaysia Perlis |
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Malaysia |
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Universiti Malaysia Perlis |
| content_source |
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| language |
English |
| topic |
Human heart and lung sounds Electronic stethoscope Fuzzy expert system Independent component analysis Acoustical analysis Auscultation Heart -- Diseases -- Diagnosis |
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Human heart and lung sounds Electronic stethoscope Fuzzy expert system Independent component analysis Acoustical analysis Auscultation Heart -- Diseases -- Diagnosis B.HemaKumar R.Anandanatarajan Separation of Heart Sounds & Lung Sounds using Independent Component Analysis |
| description |
Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. |
| author2 |
mail2hemakumar@graffiti.net |
| author_facet |
mail2hemakumar@graffiti.net B.HemaKumar R.Anandanatarajan |
| format |
Working Paper |
| author |
B.HemaKumar R.Anandanatarajan |
| author_sort |
B.HemaKumar |
| title |
Separation of Heart Sounds & Lung Sounds using Independent Component Analysis |
| title_short |
Separation of Heart Sounds & Lung Sounds using Independent Component Analysis |
| title_full |
Separation of Heart Sounds & Lung Sounds using Independent Component Analysis |
| title_fullStr |
Separation of Heart Sounds & Lung Sounds using Independent Component Analysis |
| title_full_unstemmed |
Separation of Heart Sounds & Lung Sounds using Independent Component Analysis |
| title_sort |
separation of heart sounds & lung sounds using independent component analysis |
| publisher |
Universiti Malaysia Perlis |
| publishDate |
2010 |
| url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/7535 |
| _version_ |
1643788864961118208 |
| score |
13.214268 |