Browsing by Author "Ionescu, C."

Now showing 1 - 2 of 2

Citation - WoS: 1
Citation - Scopus: 1
Extraction of Reliable Information From Hme-Domain Pressure and Flow Signals Measured by Means of Forced Oscillation Techniques
(Syscom 18 SRL, 2014) Nigmatulun, R.R.; Baleanu, Dumitru; Osokin, S.I.; Ionescu, C.; Baleanu, D.; Matematik
This paper aims to give a proof-of-concept for the possible application of the forced oscillation lung function test to assess the viscoelastic properties of the airways and tissue. In particular, a novel signal processing algorithm is employed on non-stationary, noisy, (relatively) short time series of respiratory pressure and flow signals. This novel technique is employed to filter the useful information from the signals acquired under two measurement conditions: pseudo-functional residual capacity (PFRC) and pseudo-total lung capacity (PTLC). The PFRC is the measurement performed at lowest lung volume with maximum deflation, and the PTLC is measurement performed at the maximum lung volume under maximum inflation. The results suggest that the proposed technique is able to extract information on the viscoelastic properties of the lung tissue at a macroscopic level. The conclusion of this preliminary study is that the proposed combination of signal processing method and lung function test is suited to be employed on a large database in order to deliver reference values and perform further statistical analysis.
Citation - WoS: 11
Citation - Scopus: 15
Nimrad: Novel Technique for Respiratory Data Treatment
(Springer London Ltd, 2014) Nigmatullin, R. R.; Ionescu, C.; Baleanu, D.
This paper illustrates the efficiency and simplicity of a new technique which is determined in this paper as NIMRAD (the non-invasive methods of the reduced analysis of data) for describing information extracted from biological signals. As a specific example, we consider the respiratory data. The NIMRAD can be applied for quantitative description of data recorded for complex systems in cases where the adequate model is absent and the treatment procedure should not contain any uncontrollable error. The theoretical developments are applied to signals measured from the respiratory system by means of the forced oscillation technique based on non-invasive lung function test. In order to verify the feasibility of the proposed algorithm for developing new diagnosis tools, we apply NIMRAD on two different respiratory data sets, namely from a healthy subject and from a patient diagnosed with asthma. The results are promising and suggest that NIMRAD could be further tailored and used for specific clinical applications.