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Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction
Linköpings universitet, Institutionen för medicinsk teknik, Fysiologisk mätteknik. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för medicinsk teknik, Fysiologisk mätteknik. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för medicinsk teknik, Fysiologisk mätteknik. Linköpings universitet, Tekniska högskolan.
2005 (engelsk)Inngår i: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 12, nr 12, s. 812-815Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Heart sounds (HS) obscure the interpretation of lung sounds (LS). This letter presents a new method to detect and remove this undesired disturbance. The HS detection algorithm is based on a recurrence time statistic that is sensitive to changes in a reconstructed state space. Signal segments that are found to contain HS are removed, and the arising missing parts are replaced with predicted LS using a nonlinear prediction scheme. The prediction operates in the reconstructed state space and uses an iterated integrated nearest trajectory algorithm. The HS detection algorithm detects HS with an error rate of 4% false positives and 8% false negatives. The spectral difference between the reconstructed LS signal and an LS signal with removed HS was 0.34/spl plusmn/0.25, 0.50/spl plusmn/0.33, 0.46/spl plusmn/0.35, and 0.94/spl plusmn/0.64 dB/Hz in the frequency bands 20-40, 40-70, 70-150, and 150-300 Hz, respectively. The cross-correlation index was found to be 99.7%, indicating excellent similarity between actual LS and predicted LS. Listening tests performed by a skilled physician showed high-quality auditory results.

sted, utgiver, år, opplag, sider
Institutionen för medicinsk teknik , 2005. Vol. 12, nr 12, s. 812-815
Emneord [en]
Bioacoustics, heart sound (HS), lung sound (LS), nonlinear prediction, recurrence time statistics
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-11857DOI: 10.1109/LSP.2005.859528OAI: oai:DiVA.org:liu-11857DiVA, id: diva2:18261
Merknad
Original publication: Ahlstrom, C., Liljefeldt, O., Hult, P. and Ask, P., Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction, 2005, IEEE Signal Processing Letters, (12), 12, 812-815. http://dx.doi.org/10.1109/LSP.2005.859528. Copyright: IEEE, http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=97Tilgjengelig fra: 2008-05-20 Laget: 2008-05-20 Sist oppdatert: 2017-12-13
Inngår i avhandling
1. Nonlinear phonocardiographic Signal Processing
Åpne denne publikasjonen i ny fane eller vindu >>Nonlinear phonocardiographic Signal Processing
2008 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

The aim of this thesis work has been to develop signal analysis methods for a computerized cardiac auscultation system, the intelligent stethoscope. In particular, the work focuses on classification and interpretation of features derived from the phonocardiographic (PCG) signal by using advanced signal processing techniques.

The PCG signal is traditionally analyzed and characterized by morphological properties in the time domain, by spectral properties in the frequency domain or by nonstationary properties in a joint time-frequency domain. The main contribution of this thesis has been to introduce nonlinear analysis techniques based on dynamical systems theory to extract more information from the PCG signal. Especially, Takens' delay embedding theorem has been used to reconstruct the underlying system's state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction. In this thesis, the PCG signal's structure in state space has been exploited in several applications. Change detection based on recurrence time statistics was used in combination with nonlinear prediction to remove obscuring heart sounds from lung sound recordings in healthy test subjects. Sample entropy and mutual information were used to assess the severity of aortic stenosis (AS) as well as mitral insufficiency (MI) in dogs. A large number of, partly nonlinear, features was extracted and used for distinguishing innocent murmurs from murmurs caused by AS or MI in patients with probable valve disease. Finally, novel work related to very accurate localization of the first heart sound by means of ECG-gated ensemble averaging was conducted. In general, the presented nonlinear processing techniques have shown considerably improved results in comparison with other PCG based techniques.

In modern health care, auscultation has found its main role in primary or in home health care, when deciding if special care and more extensive examinations are required. Making a decision based on auscultation is however difficult, why a simple tool able to screen and assess murmurs would be both time- and cost-saving while relieving many patients from needless anxiety. In the emerging field of telemedicine and home care, an intelligent stethoscope with decision support abilities would be of great value.

sted, utgiver, år, opplag, sider
Institutionen för medicinsk teknik, 2008. s. 213
Serie
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1168
Emneord
Signal analysis methods, computerized cardiac auscultation system, phonocardiographic (PCG) signal, mitral insufficiency (MI), time- and cost-saving
HSV kategori
Identifikatorer
urn:nbn:se:liu:diva-11302 (URN)978-91-7393-947-8 (ISBN)
Disputas
2008-04-25, Elsa Brändströmsalen, Universitetssjukhuset, Linköping, 09:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2008-03-20 Laget: 2008-03-20 Sist oppdatert: 2009-04-21
2. Processing of the Phonocardiographic Signal: methods for the intelligent stethoscope
Åpne denne publikasjonen i ny fane eller vindu >>Processing of the Phonocardiographic Signal: methods for the intelligent stethoscope
2006 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Phonocardiographic signals contain bioacoustic information reflecting the operation of the heart. Normally there are two heart sounds, and additional sounds indicate disease. If a third heart sound is present it could be a sign of heart failure whereas a murmur indicates defective valves or an orifice in the septal wall. The primary aim of this thesis is to use signal processing tools to improve the diagnostic value of this information. More specifically, three different methods have been developed:

• A nonlinear change detection method has been applied to automatically detect heart sounds. The first and the second heart sounds can be found using recurrence times of the first kind while the third heart sound can be found using recurrence times of the second kind. Most third heart sound occurrences were detected (98 %), but the amount of false extra detections was rather high (7 % of the heart cycles).

• Heart sounds obscure the interpretation of lung sounds. A new method based on nonlinear prediction has been developed to remove this undesired disturbance. High similarity was obtained when comparing actual lung sounds with lung sounds after removal of heart sounds.

• Analysis methods such as Shannon energy, wavelets and recurrence quantification analysis were used to extract information from the phonocardiographic signal. The most prominent features, determined by a feature selection method, were used to create a new feature set for heart murmur classification. The classification result was 86 % when separating patients with aortic stenosis, mitral insufficiency and physiological murmurs.

The derived methods give reasonable results, and they all provide a step forward in the quest for an intelligent stethoscope, a universal phonocardiography tool able to enhance auscultation by improving sound quality, emphasizing abnormal events in the heart cycle and distinguishing different heart murmurs.

sted, utgiver, år, opplag, sider
Institutionen för medicinsk teknik, 2006. s. 75
Serie
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1253
Emneord
Bioacoustics, phonocardiographic, signal processing, heart sound, lung sound, nonlinear dynamics
HSV kategori
Identifikatorer
urn:nbn:se:liu:diva-7538 (URN)LiU-TEK-LIC-2006:34 (Lokal ID)91-85523-59-3 (ISBN)LiU-TEK-LIC-2006:34 (Arkivnummer)LiU-TEK-LIC-2006:34 (OAI)
Presentation
2006-05-31, IMT1, Campus US, Linköpings universitet, Linköping, 00:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2006-10-09 Laget: 2006-10-09 Sist oppdatert: 2010-01-14bibliografisk kontrollert

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