Determination of Respiratory Parameters by means of Hurst Exponents of the Respiratory Sounds and Stochastic Processing Methods

2021 ◽  
pp. 1-1
Author(s):  
Esra Saatci ◽  
Ertugrul Saatci
Keyword(s):  
Respiratory Sounds ◽  
Processing Methods ◽  
Respiratory Parameters ◽  
Stochastic Processing ◽  
Hurst Exponents

Analysis of Stall Precursors and Determination of Optimum Signal Processing Methods for an LM-2500 Gas Turbine

2008 ◽  
Author(s):  
Knox T. Millsaps ◽  
Gustave C. Dahl ◽  
Daniel E. Caguiat ◽  
Jeffrey S. Patterson
Keyword(s):  
Time Series ◽  
Signal Processing ◽  
Gas Turbine ◽  
Rotor Speed ◽  
Processing Methods ◽  
Turbine Engine ◽  
Pressure Signal ◽  
Time Series Analyses ◽  
Signal Processing Methods

This paper presents an analysis of data taken from several stall initiation events on a GE LM-2500 gas turbine engine. Specifically, the time series of three separate pressure signals located at compressor stages 3, 6, and 15 were analyzed utilizing various signal processing methods to determine the most reliable indicator of incipient stall for this engine. The spectral analyses performed showed that rotating precursor waves traveling around the annulus at approximately half of the rotor speed were the best indicators. Non-linear chaotic time series analyses were also used to predict stall, but it was not as reliable an indicator. Several algorithms were used and it was determined that stall wave perturbations can be reliably identified about 900 revolutions prior to the stall. This work indicates that a single pressure signal located at stage 3 on an LM-2500 gas turbine is sufficient to provide advance warning of more than 2 seconds prior to the fully developed stall event.

Disposal of blood [1-13C]lactate in humans during rest and exercise

1986 ◽  
Vol 60 (1) ◽  
pp. 232-241 ◽  
Author(s):  
R. S. Mazzeo ◽  
G. A. Brooks ◽  
D. A. Schoeller ◽  
T. F. Budinger
Keyword(s):  
Blood Lactate ◽  
Lactate Concentration ◽  
Blood Lactate Concentration ◽  
Curvilinear Relationship ◽  
O2 Consumption ◽  
Lactate Oxidation ◽  
Respiratory Parameters ◽  
Steady Rate ◽  
Lactate Levels

Lactate irreversible disposal (RiLa) and oxidation (RoxLa) rates were studied in six male subjects during rest (Re), easy exercise [EE, 140 min of cycling at 50% of maximum O2 consumption (VO2max)] and hard exercise (HE, 65 min at 75% VO2max). Twenty minutes into each condition, subjects received a Na+-L(+)-[1–13C]lactate intravenous bolus injection. Blood was sampled intermittently from the contralateral arm for metabolite levels, acid-base status, and enrichment of 13C in lactate. Expired air was monitored continuously for determination of respiratory parameters, and aliquots were collected for determination of 13C enrichment in CO2. Steady-rate values for O2 consumption (VO2) were 0.33 +/- 0.01, 2.11 +/- 0.03, and 3.10 +/- 0.03 l/min for Re, EE, and HE, respectively. Corresponding values of blood lactate levels were 0.84 +/- 0.01, 1.33 +/- 0.05, and 4.75 +/- 0.28 mM in the three conditions. Blood lactate disposal rates were significantly correlated to VO2 (r = 0.78), averaging 123.4 +/- 20.7, 245.5 +/- 40.3, and 316.2 +/- 53.7 mg X kg-1 X h-1 during Re, EE, and HE, respectively. Lactate oxidation rate was also linearly related to VO2 (r = 0.81), and the percentage of RiLa oxidized increased from 49.3% at rest to 87.0% during exercise. A curvilinear relationship was found between RiLa and blood lactate concentration. It was concluded that, in humans, 1) lactate disposal (turnover) rate is directly related to the metabolic rate, 2) oxidation is the major fate of lactate removal during exercise, and 3) blood lactate concentration is not an accurate indicator of lactate disposal and oxidation.

Design and Implementation of Digital Asthma Diagnosis System

2019 ◽  
Vol 14 (3) ◽  
pp. 1-15
Author(s):  
Qinghua Yao ◽  
Xiantao Yang
Keyword(s):  
Mathematical Model ◽  
Mutation Rate ◽  
Forced Expiratory Volume ◽  
Digital Signals ◽  
Respiratory Parameters ◽  
The Mathematical Model ◽  
The Relationship ◽  
Objective Indicators ◽  
Signal Conditioning Circuit

In this article, the MSP430F149 is the microcontroller (MCU), and a pressure sensor, MPX5100AP, is used to measure body measurement of maximal forced expiratory volume (FEV) and peak expiratory flow rate (PEFR). The two analog signals are processed by the signal conditioning circuit, and then the corresponding digital signals are acquired by the MCU. With the related operations of multiple respiratory parameters, a built-up time of respiration signal mutation rate values and the determination of the mutation rate, a mathematical model is built among FEV, PEFR and the rate of variation. The mathematical model of the system is analyzed, and the relationship between the detection results and the degree of airway obstruction is established. Finally, the patient's condition analysis results are given directly on the LCD, which provided the objective indicators for the medical treatment of the disease.

scholarly journals Determination of Relationship Between Respiratory Parameters and Aerobic Capacity of Referees

2014 ◽  
Vol 152 ◽  
pp. 1267-1273 ◽  
Author(s):  
Mürşit Ceyhun Birinci ◽  
Ali Kerim Yılmaz ◽  
Alperen Erkin ◽  
Sezgin Şahbaz ◽  
İlkay Aydın
Keyword(s):  
Aerobic Capacity ◽  
Respiratory Parameters

scholarly journals Investigation of NIR spectra pre-processing methods combined with multivariate regression for determination of moisture in powdered industrial egg

2018 ◽  
Vol 40 (1) ◽  
pp. 30133
Author(s):  
Lycio Shinji Watanabe ◽  
Yuri Renan Bovolenta ◽  
Vinicius Ricardo Acquaro Junior ◽  
Douglas Fernandes Barbin ◽  
Tiago Bervelieri Madeira ◽  
...  
Keyword(s):  
Multivariate Regression ◽  
Processing Methods
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