EFFECTS OF MOBILE PHONE RADIATION ON CARDIAC HEALTH

2011 ◽  
Vol 11 (05) ◽  
pp. 1241-1253 ◽  
Author(s):  
OLIVER FAUST ◽  
U. RAJENDRA ACHARYA ◽  
MYAGMARBAYAR NERGUI ◽  
DHANJOO N GHISTA ◽  
SUBHAGATA CHATTOPADHYAY ◽  
...  
Keyword(s):  
Health Risks ◽  
Radiation Effects ◽  
Approximate Entropy ◽  
Largest Lyapunov Exponent ◽  
Pathological Effect ◽  
Neurological Effects ◽  
The Masses ◽  
Result Analysis ◽  
Parameter Values ◽  
Mobile Phone Radiation

Mobile phones (MPs) progressed from a tool of the privileged few to a gadget for the masses. However, the physical effects, which enable wireless information transmission, did not change; MP technology still relies on pulsed high-frequency electromagnetic (EM) fields. Therefore, the health risks, associated with EM fields, remain. Studies that investigated these health risks have reported dizziness, numbness in the thigh, and heaviness in the chest. This study investigates neurological effects that are caused by EM fields radiated from MPs. The heart rate variability (HRV) can be used as a measure for these neurological effects, because the automated nervous system modulates the HRV. We measured the HRV of 14 healthy male volunteers. We used the following nonlinear parameters to quantify the MP radiation effects on HRV: approximate entropy (ApEn), capacity dimension (CaD), correlation dimension (CD), fractal dimension (FD), Hurst exponent (H), and the largest Lyapunov exponent (LLE). The results indicate that there is a measurable difference in the parameter values when the MP is kept close to the chest and when it is kept close to the head. However, these differences are very small and statistical analysis showed that they have no clinical significance. Furthermore, the result analysis does not show a consistent trend, which indicates that there is no underlying pathological effect.

A COMPUTATIONAL FRAMEWORK TO DISCRIMINATE DIFFERENT ANESTHESIA STATES FROM EEG SIGNAL

2018 ◽  
Vol 30 (03) ◽  
pp. 1850020 ◽  
Author(s):  
Seyyed Abed Hosseini
Keyword(s):  
General Anesthesia ◽  
Rbf Neural Network ◽  
Principal Component ◽  
Approximate Entropy ◽  
Largest Lyapunov Exponent ◽  
Eeg Signal ◽  
Wavelet Coefficients ◽  
Sparse Principal Component Analysis ◽  
Beta Band ◽  
Computational Framework

This paper develops a computational framework to classify different anesthesia states, including awake, moderate anesthesia, and general anesthesia, using electroencephalography (EEG) signal. The proposed framework presents data gathering; preprocessing; appropriate selection of window length by genetic algorithm (GA); feature extraction by approximate entropy (ApEn), Petrosian fractal dimension (PFD), Hurst exponent (HE), largest Lyapunov exponent (LLE), Lempel-Ziv complexity (LZC), correlation dimension (CD), and Daubechies wavelet coefficients; feature normalization; feature selection by non-negative sparse principal component analysis (NSPCA); and classification by radial basis function (RBF) neural network. Because of the small number of samples, a five-fold cross-validation approach is used to validate the results. A GA is used to select that by observing an interval of 2.7[Formula: see text]s for further assessment. This paper assessed superior features, such as LZC, ApEn, PFD, HE, the mean value of wavelet coefficients for the beta band, and LLE. The results indicate that the proposed framework can classify different anesthesia states, including awake, moderate anesthesia, and general anesthesia, with an accuracy of 92.07%, 96.18%, and 93.42%, respectively. Therefore, the proposed framework can discriminate different anesthesia states with an average accuracy of 93.89%. Finally, the proposed framework provided a facilitative representation of the brain’s behavior in different states of anesthesia.

Effect of a Planetary Gearbox on the Dynamics of a Rotor System

2018 ◽  
Author(s):  
Ali Tatar ◽  
Christoph W. Schwingshackl
Keyword(s):  
Degrees Of Freedom ◽  
Dynamic Behaviour ◽  
Rotor System ◽  
Mode Shapes ◽  
Rotating System ◽  
Planetary Gearbox ◽  
Finite Element Software ◽  
Gyroscopic Effects ◽  
The Masses ◽  
Parameter Values

The dynamic analysis of rotors with bladed disks has been investigated in detail over many decades and is reasonably well understood today. In contrast, the dynamic behaviour of two rotors that are coupled via a planetary gearbox is much less well understood. The planetary gearbox adds inertia, mass, stiffness, damping and gyroscopic moments to the system and can strongly affect the modal properties and the dynamic behaviour of the global rotating system. The main objective of this paper is to create a six degrees of freedom numerical model of a rotor system with a planetary gearbox and to investigate its effect on the coupled rotor system. The analysis is based on the newly developed finite element software “GEAROT” which provides axial, torsional and lateral deflections of the two shafts at different speeds via Timoshenko beam elements and also takes gyroscopic effects into account. The disks are currently considered as rigid and the bearings are modelled with isotropic stiffness elements in the translational and rotational directions. A novel planetary gearbox model has been developed, which takes the translational and rotational stiffness and the damping of the gearbox, as well as the masses and inertias of the sun gear, ring gear, planet gears and carrier into account. A rotating system with a planetary gearbox has been investigated with GEAROT. The gearbox mass and stiffness parameters are identified as having a significant effect on the modal behaviour of the rotor system, affecting its natural frequencies and mode shapes. The higher frequency modes are found to be more sensitive to the parameter changes as well as the modes which have a higher deflection at the location of the gearbox on the rotor system. Compared with a single shaft system, the presence of a gearbox introduces new global modes to the rotor system and decouples the mode shapes of the two shafts. The introduction of a planetary gearbox may also lead to an increase or a reduction of the frequency response of the rotor system based on gear parameter values.

Research of Extracting Information about Reservoir Logging Signals Based on Chaos Characteristics

2013 ◽  
Vol 380-384 ◽  
pp. 3742-3745
Author(s):  
Chun Yan Nie ◽  
Rui Li ◽  
Wan Li Zhang
Keyword(s):  
Lyapunov Exponent ◽  
Correlation Dimension ◽  
Approximate Entropy ◽  
Water Layer ◽  
Time Correlation ◽  
Largest Lyapunov Exponent ◽  
Characteristic Parameters ◽  
Chaotic Characteristic ◽  
Oil Water

The mechanism of logging signals generating was researched. In the same time, correlation dimension, largest Lyapunov exponent and approximate entropy of chaotic characteristics were extracted. On this basis, chaotic characteristic parameters were applied in processing, analysis and interpretation, try to find chaotic characteristics of different of reservoirs for example oil, water layer and the dry layer. The results showed that chaos characteristics in different reservoir is different, therefore, we can distinguish the different natures of reservoirs by extracting chaos characteristics.

scholarly journals Application of Time-Scale Decomposition of Entropy for Eye Movement Analysis

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 168 ◽  
Author(s):  
Katarzyna Harezlak ◽  
Pawel Kasprowski
Keyword(s):  
Eye Movement ◽  
Time Scale ◽  
Movement Analysis ◽  
Approximate Entropy ◽  
Largest Lyapunov Exponent ◽  
Eye Movement Analysis ◽  
Movement Dynamics ◽  
Signal Characteristics ◽  
Time Scale Decomposition ◽  
Events Detection

The methods for nonlinear time series analysis were used in the presented research to reveal eye movement signal characteristics. Three measures were used: approximate entropy, fuzzy entropy, and the Largest Lyapunov Exponent, for which the multilevel maps (MMs), being their time-scale decomposition, were defined. To check whether the estimated characteristics might be useful in eye movement events detection, these structures were applied in the classification process conducted with the usage of the kNN method. The elements of three MMs were used to define feature vectors for this process. They consisted of differently combined MM segments, belonging either to one or several selected levels, as well as included values either of one or all the analysed measures. Such a classification produced an improvement in the accuracy for saccadic latency and saccade, when compared with the previously conducted studies using eye movement dynamics.

scholarly journals Dynamical Analysis of a New Chaotic Fractional Discrete-Time System and Its Control

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1344
Author(s):  
A. Othman Almatroud ◽  
Amina-Aicha Khennaoui ◽  
Adel Ouannas ◽  
Giuseppe Grassi ◽  
M. Mossa Al-sawalha ◽  
...  
Keyword(s):  
Discrete Time ◽  
Software Package ◽  
Control Method ◽  
Approximate Entropy ◽  
Dynamical Analysis ◽  
Largest Lyapunov Exponent ◽  
Bifurcation Diagrams ◽  
Discrete Time System ◽  
Time System ◽  
Quadratic Nonlinearities

This article proposes a new fractional-order discrete-time chaotic system, without equilibria, included two quadratic nonlinearities terms. The dynamics of this system were experimentally investigated via bifurcation diagrams and largest Lyapunov exponent. Besides, some chaotic tests such as the 0–1 test and approximate entropy (ApEn) were included to detect the performance of our numerical results. Furthermore, a valid control method of stabilization is introduced to regulate the proposed system in such a way as to force all its states to adaptively tend toward the equilibrium point at zero. All theoretical findings in this work have been verified numerically using MATLAB software package.

scholarly journals Dynamics Analysis and Fractional-Order Approximate Entropy of Nonlinear Inventory Management Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Tengfei Lei ◽  
Rita Yi Man Li ◽  
Haiyan Fu
Keyword(s):  
Lyapunov Exponent ◽  
Inventory Management ◽  
Approximate Entropy ◽  
Human Action ◽  
Management Model ◽  
Management Systems ◽  
Largest Lyapunov Exponent ◽  
Complex Nonlinear Systems ◽  
Definition Of ◽  
Special Circumstances

Inventory management is complex nonlinear systems that are affected by various external factors, including course human action and policy. We study the inventory management model under special circumstances and analyse the equilibrium point of the system. The dynamics of the system is analysed by means of the eigenvalue trajectory, bifurcations, chaotic attractor, and largest Lyapunov exponent diagram. At the same time, according to the definition of fractional calculus, the fractional approximate entropy is used to analyse the system, and the results are consistent with those of the largest Lyapunov exponent diagram, which shows the effectiveness of this method.

Public Perceptions of Radiation Effects on Health Risks and Well-Being

2020 ◽  
Author(s):  
Yusniza Kamarulzaman ◽  
Farrah Dina Yusop ◽  
Noorhidawati Abdullah ◽  
Azian Madun ◽  
Kwan-Hoong Ng
Keyword(s):  
Health Risks ◽  
Radiation Effects ◽  
Well Being ◽  
Public Perceptions

scholarly journals Chaotic Analysis of the Electroretinographic Signal for Diagnosis

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Surya S. Nair ◽  
K. Paul Joseph
Keyword(s):  
Approximate Entropy ◽  
Physiological Signals ◽  
Largest Lyapunov Exponent ◽  
Time Varying ◽  
Congenital Stationary Night Blindness ◽  
Recurrence Plots ◽  
Control Groups ◽  
Nonlinear Parameters ◽  
Naked Eye ◽  
Signal Features

Electroretinogram (ERG) is a time-varying potential which arises from different layers of retina. To be specific, all the physiological signals may contain some useful information which is not visible to our naked eye. However this subtle information is difficult to monitor directly. Therefore the ERG signal features which are extracted and analyzed using computers are highly useful for diagnosis. This work discusses the chaotic aspect of the ERG signal for the controls, congenital stationary night blindness (CSNB), and cone-rod dystrophy (CRD) classes. In this work, nonlinear parameters like Hurst exponent (HE), the largest Lyapunov exponent (LLE), Higuchi’s fractal dimension (HFD), and approximate entropy (ApEn) are analyzed for the three different classes. It is found that the measures like HE dimension and ApEn are higher for controls as compared to the other two classes. But LLE shows no distinguishable variation for the three cases. We have also analyzed the recurrence plots and phase-space plots which shows a drastic variation among the three groups. The results obtained show that the ERG signal is highly complex for the control groups and less complex for the abnormal classes withPvalue less than 0.05.

scholarly journals Mobile phone radiation effects into ERK1, ERK2 and PKCα signaling pathway of Wistar rats pituitary

2012 ◽  
Vol 26 (S1) ◽  
Author(s):  
Luiz Carlos Caires ◽  
Ernesto Silveira Goulart Guimarães ◽  
Camila Manso Musso ◽  
Rebecca Vasconcellos ◽  
Diego Assis ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Signaling Pathway ◽  
Radiation Effects ◽  
Wistar Rats ◽  
Mobile Phone Radiation

Sexual dimorphism in the complexity of cardiac pacemaker activity

2002 ◽  
Vol 283 (4) ◽  
pp. H1695-H1702 ◽  
Author(s):  
Terry B. J. Kuo ◽  
Cheryl C. H. Yang
Keyword(s):  
Cardiac Pacemaker ◽  
Approximate Entropy ◽  
Surrogate Data ◽  
Pacemaker Activity ◽  
Largest Lyapunov Exponent ◽  
Nonlinear Structure ◽  
Electrocardiogram Signals ◽  
Neural Modulation ◽  
Frequency Components ◽  
Normal Women

This study explored the effects of gender and aging on the complexity of cardiac pacemaker activity. Electrocardiogram signals were studied in normal women ( n = 240) and men ( n = 240) ranging in age from 40 to 79 yr. Nonlinear analysis of short-term resting R-R intervals was performed using the correlation dimension (CD), approximate entropy (ApEn), and largest Lyapunov exponent (LLE). Evidence of nonlinear structure was obtained by the surrogate data test. CD, ApEn, and LLE were negatively correlated with age. Despite similar means and SDs of the R-R intervals, women had a significantly higher CD, ApEn, and LLE compared with men in the age strata of 40–44 and 45–49 yr. CD and ApEn were strongly ( r > 0.71) correlated with low- and high-frequency components. We conclude that the resting cardiac pacemaker activity of women is more complex than that of men in middle age, and the gender-related difference diminishes after the age of 50 yr. The higher complexity implies a more comprehensive neural modulation.

Sign in / Sign up

Export Citation Format

Share Document