Using Nonlinear Tools to Evaluate Movement of Fragile Objects

2015 ◽  
Vol 31 (2) ◽  
pp. 95-101 ◽  
Author(s):  
Stefan Madansingh ◽  
Stacey L. Gorniak
Keyword(s):  
Approximate Entropy ◽  
Largest Lyapunov Exponent ◽  
Movement Variability ◽  
Discrete Trials ◽  
Movement Strategies ◽  
Direction Of Movement ◽  
Primary Direction ◽  
Kinematic Measures ◽  
Healthy Participants ◽  
Anterior Posterior

We investigated the movement strategies of young, healthy participants (7 men/7 women) during the movement of a fragile object using nonlinear analysis. The kinematic variables of position, velocity, and acceleration were quantified using largest Lyapunov exponent (LyE) and approximate entropy (ApEn) analysis to identify the structure of their movement variability and movement predictability, respectively. Subjects performed a total of 15 discrete trials of an upper extremity movement task without crushing the object at each fragility condition, using each hand (left/right). We tested four fragility conditions hypothesizing that an increase in fragility would result in higher movement predictability and decreased temporal variability. Comparisons between the structure of movement variability and movement predictability were based on fragility condition, handedness, and kinematic measures. In this specific population, object fragility and participant handedness did not significantly impact the structure of movement variability (LyE) in the primary direction of movement (Z direction), although some effects were observed in the anterior/posterior directions. ApEn values were minimized across conditions, showing increased movement predictability, and is suggested for the analysis of discrete kinematic movements. In healthy populations, the results of this study suggest minimal effects on task performance and movement predictability as a result of object fragility.

Gait kinematics in Low Back Pain: A non-linear approach

2021 ◽  
pp. 1-8
Author(s):  
Christos Tsigkanos ◽  
Theano Demestiha ◽  
Chara Spiliopoulou ◽  
Georgios Tsigkanos
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Healthy Subjects ◽  
Infrared Camera ◽  
Low Back ◽  
Movement Variability ◽  
Optoelectronic System ◽  
Mean Values ◽  
Non Linear ◽  
Healthy Participants

BACKGROUND: Kinematic analysis has been a dominant tool for addressing the neuromuscular and proprioceptive alterations that occur in Low Back Pain (LBP) patients. Movement variability is a crucial component of this analysis. During the past years a promising approach appears to be the application of non-linear indices. OBJECTIVE: The aim of the study was to compare movement variability, as expressed mainly by non-linear indices, at the pelvis and lumbar between LBP patients and healthy participants during gait. METHODS: Sixteen (16) LBP patients and thirteen (13) healthy control subjects (non-athletes) participated in the study. Participants walked on a treadmill at different walking conditions while recorded by a 6-infrared camera optoelectronic system. Kinematic variability of pelvic and lumbar movement was analyzed using linear (standard deviation) and non-linear indices (Maximal Lyapunov Exponent – LyE and Approximate Entropy – ApEn). RESULTS: Healthy subjects were found to have significantly greater mean values than LBP patients at seven pelvic and lumbar components in LyE, ApEn and SD. Specifically, the calculated LyE at the pelvis during normal gait was proven to have a sensitivity of 92.3% and a specificity of 90% in the discrimination of healthy subjects from LBP patients. Female subjects presented with higher variability in gait measures than males. CONCLUSION: Healthy participants presented with higher movement variability in their kinematic behavior in comparison to LBP patients. Lower variability values may be partly explained by the attempt of LBP patients to avoid painful end of range of motion positions. In this perspective non-linear indices seem to relate to qualitive characteristics of movement that need to be taken into consideration during rehabilitation.

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.

scholarly journals Reliability and Agreement of 3D Trunk and Lower Extremity Movement Analysis by Means of Inertial Sensor Technology for Unipodal and Bipodal Tasks

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 141 ◽  
Author(s):  
Rob Van der Straaten ◽  
Amber K. B. D. Bruijnes ◽  
Benedicte Vanwanseele ◽  
Ilse Jonkers ◽  
Liesbet De Baets ◽  
...  
Keyword(s):  
Lower Limb ◽  
Sagittal Plane ◽  
Inertial Sensor ◽  
Movement Analysis ◽  
Sensor Technology ◽  
Inertial Measurement ◽  
Sit To Stand ◽  
Movement Strategies ◽  
Measurement Units ◽  
Healthy Participants

This study evaluates the reliability and agreement of the 3D range of motion (ROM) of trunk and lower limb joints, measured by inertial measurement units (MVN BIOMECH Awinda, Xsens Technologies), during a single leg squat (SLS) and sit to stand (STS) task. Furthermore, distinction was made between movement phases, to discuss the reliability and agreement for different phases of both movement tasks. Twenty healthy participants were measured on two testing days. On day one, measurements were conducted by two operators to determine the within-session and between-operator reliability and agreement. On day two, measurements were conducted by the same operator, to determine the between-session reliability and agreement. The SLS task had lower within-session reliability and agreement compared with between-session and between-operator reliability and agreement. The reliability and agreement of the hip, knee, and ankle ROM in the sagittal plane were good for both phases of the SLS task. For both phases of STS task, within-session reliability and agreement were good, and between-session and between-operator reliability and agreement were lower in all planes. As both tasks are physically demanding, differences may be explained by inconsistent movement strategies. These results show that inertial sensor systems show promise for use in further research to investigate (mal)adaptive movement strategies.

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 In-Shoe Plantar Pressure Measurement—Influence of Insole Placement on Selected Parameters during Running

Proceedings ◽  
2020 ◽  
Vol 49 (1) ◽  
pp. 50 ◽  
Author(s):  
Franziska Mally ◽  
Otto Hofstätter ◽  
Markus Eckelt
Keyword(s):  
Pressure Measurement ◽  
Plantar Pressure ◽  
Center Of Pressure ◽  
Pressure Sensing ◽  
Pressure Decrease ◽  
Running Shoes ◽  
Mean Pressure ◽  
Plantar Pressure Measurement ◽  
Healthy Participants ◽  
Anterior Posterior

While it is assumed that pressure-sensing insoles are usually placed directly below the foot and on top of the shoes’ standard insoles, nearly no previously published study actually describes the procedure, which leaves a slight uncertainty. Therefore, the aim of this study was to evaluate whether the placement has an influence on selected parameters or not. Five healthy participants took part in the measurements and ran on a treadmill at a running velocity of 10 km/h with three different running shoes. Plantar pressure was measured using pressure-sensing insoles, which were once placed on top and once below the shoes’ standard insoles. Selected parameters were the maximum and mean pressure and the range of the center of pressure (COP) in anterior–posterior and medial–lateral directions. The results indicate that maximum and mean pressure decrease when the pressure-sensing insole lies below the shoe’s insole and the medial–lateral COP is the least effected parameter.

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.

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.

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.

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