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Chaotic dynamics of respiratory sounds
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. Linköpings universitet, Institutionen för medicinsk teknik, Fysiologisk mätteknik.
Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för medicinsk teknik, Fysiologisk mätteknik.
2006 (engelsk)Inngår i: Chaos, Solitons & Fractals, ISSN 0960-0779, E-ISSN 1873-2887, Vol. 29, nr 5, s. 1054-1062Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

There is a growing interest in nonlinear analysis of respiratory sounds (RS), but little has been done to justify the use of nonlinear tools on such data. The aim of this paper is to investigate the stationarity, linearity and chaotic dynamics of recorded RS. Two independent data sets from 8 + 8 healthy subjects were recorded and investigated. The first set consisted of lung sounds (LS) recorded with an electronic stethoscope and the other of tracheal sounds (TS) recorded with a contact accelerometer. Recurrence plot analysis revealed that both LS and TS are quasistationary, with the parts corresponding to inspiratory and expiratory flow plateaus being stationary. Surrogate data tests could not provide statistically sufficient evidence regarding the nonlinearity of the data. The null hypothesis could not be rejected in 4 out of 32 LS cases and in 15 out of 32 TS cases. However, the Lyapunov spectra, the correlation dimension (D2) and the Kaplan-Yorke dimension (DKY) all indicate chaotic behavior. The Lyapunov analysis showed that the sum of the exponents was negative in all cases and that the largest exponent was found to be positive. The results are partly ambiguous, but provide some evidence of chaotic dynamics of RS, both concerning LS and TS. The results motivate continuous use of nonlinear tools for analysing RS data. © 2005 Elsevier Ltd. All rights reserved.

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2006. Vol. 29, nr 5, s. 1054-1062
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URN: urn:nbn:se:liu:diva-50139DOI: 10.1016/j.chaos.2005.08.197OAI: oai:DiVA.org:liu-50139DiVA, id: diva2:271035
Tilgjengelig fra: 2009-10-11 Laget: 2009-10-11 Sist oppdatert: 2017-12-12

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