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Abstract: The paper reports the design, construction, and calibration of the prototype of a spirometer based on electronic speckle interferometry (ESPI). The conventional ESPI setup is modified by incorporating a DNM (Diaphragm-Nozzle-Mouthpiece) module comprising a metallic diaphragm, regulated airflow channel, and a mouthpiece. The exhaled air after a deep breathe is channelled to the DNM module where the diaphragm gets deformed. From the circular fringe pattern obtained by subtracting the speckled images before and after deformation of the metallic diaphragm, the radius of curvature (R) due to deformation is calculated using the principle of Newton’s rings. The value of R and peak expiratory flow rate (PEFR) from the standard spirometer reading are correlated. From the 640 observations spread over the range 100 - 500 L/min in the standard spirometer, an empirical relation is set in terms of R from the scatter plot. The ESPI spirometer (ESPIS) is validated by determining the value of R corresponding to a particular PEFR from the empirical relation and also from the standard spirometer. The PEFR calculated from ESPIS matches well with the standard spirometer reading, which suggests that the system designed and constructed can be used for biomedical applications for assessing lungs’ efficiency.
Found in: osebi
Keywords: Speckle, Spirometer, DNM module, ESPIS, Peak expiratory flow rate
Published: 28.06.2022; Views: 493; Downloads: 0
Fulltext (2,38 MB)

Abstract: The development of novel digital auscultation techniques has become highly significant in the context of the outburst of the pandemic COVID 19. The present work reports the spectral, nonlinear time series, fractal, and complexity analysis of vesicular (VB) and bronchial (BB) breath signals. The analysis is carried out with 37 breath sound signals. The spectral analysis brings out the signatures of VB and BB through the power spectral density plot and wavelet scalogram. The dynamics of airflow through the respiratory tract during VB and BB are investigated using the nonlinear time series and complexity analyses in terms of the phase portrait, fractal dimension, Hurst exponent, and sample entropy. The higher degree of chaoticity in BB relative to VB is unwrapped through the maximal Lyapunov exponent. The principal component analysis helps in classifying VB and BB sound signals through the feature extraction from the power spectral density data. The method proposed in the present work is simple, cost-effective, and sensitive, with a far-reaching potential of addressing and diagnosing the current issue of COVID 19 through lung auscultation.
Found in: osebi
Keywords: Breath sound analysis, Fractal dimension, Nonlinear time series analysis, Sample entropy, Hurst exponent, Principal component analysis
Published: 28.06.2022; Views: 534; Downloads: 0
Fulltext (2,73 MB)

Abstract: Chlorophyll fluorescence (Chl F) is widely used in sensing applications to understand terrestrial vegetation and environmental and climatic variations. The increasing rates of industrialization and carbon emission from internal combustion engines (ICEs) pose a threat to sustainable development. This study analyses the impact of carbon nanoparticles (CNPs) from ICEs on the optical absorption and fluorescence emission of leaf pigments. Leaf pigments without and with CNPs were subjected to UV-visible and photo-luminescence (PL) spectroscopy analyses. The field emission scanning electron microscopy and high-resolution transmission electron microscopy images of CNPs showed their morphology. The Jablonski diagram of the CNP-incorporated chlorophyll system helped in understanding the fluorescence emission,internal conversion, and the exchange of energy between them. The variations in (i) total chlorophyll, (ii) optical absorbance by total chlorophyll, (iii) PL emission peak (at 675 nm and 718 nm) intensities for different excitation wavelengths, and (iv) normalized absorbance at the PL emission peaks with different CNP concentrations were analysed by dividing into three regions. In Region I (0–0.625 mg ml−1 ), the radiative component dominated the nonradiative component as a result of energy transfer from CNPs to chlorophyll. In Region II (0.625–1.2 mg ml−1 ), the increase in CNP concentration initiated diffusion into chloroplasts, resulting in the increase in the nonradiative part of total energy and decrease in PL peak intensity. In Region III (1.2–2.5 mg ml−1 ), the energy absorbed by the CNPs dissipated more nonradiatively, leading to a slow rate of increase in the radiative part. The visual response of PL emission, color purity, and the distribution of the emitted energy over the spectrum studied with the help of CIE plots, power spectrum, and confocal fluorescence microscopy revealed the fluorescence emission in the red region. This study suggests the possibility of employing Chl F in agricultural, environmental, and biological fields for sensing applications.
Found in: osebi
Keywords: carbon nanoparticle, optical emission, fluorescence
Published: 05.07.2022; Views: 436; Downloads: 0
Fulltext (1,92 MB)

Abstract: The paper proposes a graph-theoretical approach to auscultation, bringing out the potential of graph features in classifying the bioacoustics signals. The complex network analysis of the bioacoustics signals - vesicular (VE) and bronchial (BR) breath sound - of 48 healthy persons are carried out for understanding the airflow dynamics during respiration. The VE and BR are classified by the machine learning techniques extracting the graph features – the number of edges (E), graph density (D), transitivity (T), degree centrality (Dcg) and eigenvector centrality (Ecg). The higher value of E, D, and T in BR indicates the temporally correlated airflow through the wider tracheobronchial tract resulting in sustained high-intense low-frequencies. The frequency spread and high-frequencies in VE, arising due to the less correlated airflow through the narrow segmental bronchi and lobar, appears as a lower value for E, D, and T. The lower values of Dcg and Ecg justify the inferences from the spectral and other graph parameters. The study proposes a methodology in remote auscultation that can be employed in the current scenario of COVID-19.
Found in: osebi
Keywords: Bioacoustic signal, Graph theory, Complex network, Lung auscultation
Published: 30.06.2022; Views: 480; Downloads: 0
Fulltext (2,63 MB)

Abstract: The work reported in this paper is the first attempt to delineate the molecular or particle dynamics from the thermal lens signal of carbon allotropic nanofluids (CANs), employing time series and fractal analyses. The nanofluids of multi-walled carbon nanotubes and graphene are prepared in base fluid, coconut oil, at low volume fraction and are subjected to thermal lens study. We have studied the thermal diffusivity and refractive index variations of the medium by analyzing the thermal lens (TL) signal. By segmenting the TL signal, the complex dynamics involved during its evolution is investigated through the phase portrait, fractal dimension, Hurst exponent, and sample entropy using time series and fractal analyses. The study also explains how the increase of the photothermal energy turns a system into stochastic and anti-persistent. The sample entropy (S) and refractive index analyses of the TL signal by segmenting into five regions reveal the evolution of S with the increase of enthalpy. The lowering of S in CAN along with its thermal diffusivity (50%–57% below) as a result of heat-trapping suggests the technique of downscaling sample entropy of the base fluid using carbon allotropes and thereby opening a novel method of improving the efficiency of thermal systems.
Found in: osebi
Keywords: carbon allotropic nanofluids, time series, entropy, MWCNT, thermal lens signal
Published: 30.06.2022; Views: 494; Downloads: 0
Fulltext (4,22 MB)