scholarly journals An Analysis of Entropy-Based Eye Movement Events Detection

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 107 ◽  
Author(s):  
Katarzyna Harezlak ◽  
Dariusz Augustyn ◽  
Pawel Kasprowski
Keyword(s):  
Eye Movement ◽  
Sampling Rate ◽  
Approximate Entropy ◽  
Potential Method ◽  
Spatiotemporal Processing ◽  
Novel Approach ◽  
Movement Dynamics ◽  
Knn Classifier ◽  
Main Components ◽  
Events Detection

Analysis of eye movement has attracted a lot of attention recently in terms of exploring areas of people’s interest, cognitive ability, and skills. The basis for eye movement usage in these applications is the detection of its main components—namely, fixations and saccades, which facilitate understanding of the spatiotemporal processing of a visual scene. In the presented research, a novel approach for the detection of eye movement events is proposed, based on the concept of approximate entropy. By using the multiresolution time-domain scheme, a structure entitled the Multilevel Entropy Map was developed for this purpose. The dataset was collected during an experiment utilizing the “jumping point” paradigm. Eye positions were registered with a 1000 Hz sampling rate. For event detection, the knn classifier was applied. The best classification efficiency in recognizing the saccadic period ranged from 83% to 94%, depending on the sample size used. These promising outcomes suggest that the proposed solution may be used as a potential method for describing eye movement dynamics.

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 Two Stepped Majority Voting for Efficient EEG based Emotion Classification

2020 ◽  
Author(s):  
aras Masood Ismael ◽  
Ömer F Alçin ◽  
Karmand H Abdalla ◽  
Abdulkadir k sengur
Keyword(s):  
Emotion Recognition ◽  
Nearest Neighbor ◽  
Noise Removal ◽  
Majority Voting ◽  
Emotion Classification ◽  
K Nearest Neighbor ◽  
Discrimination Accuracy ◽  
Novel Approach ◽  
Knn Classifier ◽  
Low Pass

Abstract In this paper, a novel approach that is based on two-stepped majority voting is proposed for efficient EEG based emotion classification. Emotion recognition is important for human-machine interactions. Facial-features and body-gestures based approaches have been generally proposed for emotion recognition. Recently, EEG based approaches become more popular in emotion recognition. In the proposed approach, the raw EEG signals are initially low-pass filtered for noise removal and band-pass filters are used for rhythms extraction. For each rhythm, the best performed EEG channels are determined based on wavelet-based entropy features and fractal dimension based features. The k-nearest neighbor (KNN) classifier is used in classification. The best five EEG channels are used in majority voting for getting the final predictions for each EEG rhythm. In the second majority voting step, the predictions from all rhythms are used to get a final prediction. The DEAP dataset is used in experiments and classification accuracy, sensitivity and specificity are used for performance evaluation metrics. The experiments are carried out to classify the emotions into two binary classes such as high valence (HV) vs low valence (LV) and high arousal (HA) vs low arousal (LA). The experiments show that 86.3% HV vs LV discrimination accuracy and 85.0% HA vs LA discrimination accuracy is obtained. The obtained results are also compared with some of the existing methods. The comparisons show that the proposed method has potential in the use of EEG based emotion classification.

Eye Movements and Mirror Neurons

2020 ◽  
pp. 89-103
Author(s):  
Giuseppe Iurato
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Universal Algebra ◽  
Natural Science ◽  
Mirror Neurons ◽  
Mirror Neuron System ◽  
Mirror Neuron ◽  
Phenomenological Theory ◽  
Neuron System ◽  
Movement Dynamics

Denotational mathematics, in the context of universal algebra, may provide algebraic structures that are able to formalize human eye movement dynamics with respect to Husserlian phenomenological theory, from which it is then possible to make briefly reference to some further relations with mirror neuron system and related topics. In this way, the authors have provided a first instance of fruitful application of socio-humanities (to be precise, philosophy and sociology) in exact/natural science used in formalizing processes.

scholarly journals Eye Movement Dynamics of Good and Poor Readers: Then and Now

1979 ◽  
Vol 11 (4) ◽  
pp. 319-328 ◽  
Author(s):  
Lester A. Lefton ◽  
Richard J. Nagle ◽  
Gwendolyn Johnson ◽  
Dennis F. Fisher
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Fifth Graders ◽  
Poor Readers ◽  
Movement Behavior ◽  
Poor Reading ◽  
Movement Dynamics ◽  
Reading Text ◽  
One Year ◽  
Good And Poor Readers

While reading text, the eye movements of good and poor reading fifth graders, third graders and adults were assessed. Subjects were tested in two sessions one year apart. Dependent variables included the duration and frequency of forward going fixations and regressions; an analysis of individual differences was also made. Results showed that poor reading fifth graders have relatively unsystematic eye movement behavior with many more fixations of longer duration than other fifth graders and adults. The eye movements of poor readers are quantitatively and qualitatively different than those of normal readers.

scholarly journals Effects of Multisine Signal Bandwidth on Eye Movement Dynamics

2019 ◽  
Vol 52 (19) ◽  
pp. 282-287
Author(s):  
Jasmijn Büskens ◽  
Johan J.M. Pel ◽  
Daan M. Pool
Keyword(s):  
Eye Movement ◽  
Movement Dynamics

scholarly journals Detecting Mind-Wandering from Eye Movement and Oculomotor Data during Learning Video Lecture

2020 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
DongMin Jang ◽  
IlHo Yang ◽  
SeoungUn Kim
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Fixation Duration ◽  
Peak Velocity ◽  
Eye Gaze ◽  
Sampling Rate ◽  
Maximum Amplitude ◽  
Mind Wandering ◽  
Video Lecture ◽  
Video Lectures

The purpose of this study was to detect mind-wandering experienced by pre-service teachers during a video learning lecture on physics. The lecture was videotaped and consisted of a live lecture in a classroom. The lecture was about Gauss's law on physics. We investigated whether oculomotor data and eye movements could be used as a marker to indicate the learner’s mind-wandering. Each data was collected in a study in which 24 pre-service teachers (16 females and 8 males) reported mind-wandering experience through self-caught method while learning physics video lecture during 30 minutes. A Tobii Pro Spectrum (sampling rate: 300 Hz) was used to capture their eye-gaze during learning Gauss's law through a course video. After watching the video lecture, we interviewed pre-service teachers about their mind-wandering experience. We first used the self-caught method to capture the mind-wandering timing of pre-service teachers while learning from video lectures. We detected more accurate mind-wandering segments by comparing fixation duration and saccade count. We investigated two types of oculomotor data (blink count, pupil size) and nine eye movements (average peak velocity of saccades; maximum peak velocity of saccades; standard deviation of peak velocity of saccades; average amplitude of saccades; maximum amplitude of saccades; total amplitude of saccades; saccade count/s; fixation duration; fixation dispersion). The result was that the blink count could not be used as a marker for mind-wandering during learning video lectures among them (oculomotor data and eye movements), unlike previous literatures. Based on the results of this study, we identified elements that can be used as mind-wandering markers while learning from video lectures that are similar to real classes, among the oculomotor data and eye movement mentioned in previous literatures. Additionally, we found that most participants focused on past thoughts and felt unpleasant after experiencing mind-wandering through interview analysis.

scholarly journals On Optimal Sizing of a Solar Thermal Building: A Novel Approach

2018 ◽  
Vol 57 ◽  
pp. 04004
Author(s):  
Shahrzad Parsania
Keyword(s):  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Solar Thermal ◽  
Optimal Size ◽  
Thermal System ◽  
Auxiliary Power Unit ◽  
Auxiliary Power ◽  
Novel Approach ◽  
Main Components ◽  
Solar Thermal System

Within the last decade, domestic energy management has gained a lot of attention. As the complexity of the solar thermal system in terms of the number of system components and energy sources increases, understanding how to manage the cooperation of all the components in order to improve the global efficiency measurements is of crucial importance. Here, the question is how to define an optimal size of the main components in a solar thermal system in order to minimize system cost. Unlike the existing approaches, we propose the use of a novel algorithm called Gravitational Search Algorithm (GSA) to analyze the accurate sizing of energy components, i.e. collector size, tank volume and Auxiliary Power Unit (APU). The objective is to maximize solar fraction, minimize the energy consumption and installation costs subject to constraints. Our proposed GSA model is evaluated and compared with one of the most well-known algorithms, Particle Swarm optimization (PSO) taking into account the fundamental system characteristics. Numerical results show that our proposed methodology significantly improves energy efficiency and reduces operational cost of the solar thermal system in contemporary built environment.

scholarly journals Beat Hamiltonians and generalized ponderomotive forces in hot magnetized plasma

1978 ◽  
Vol 20 (3) ◽  
pp. 365-390 ◽  
Author(s):  
Shayne Johnston ◽  
Allan N. Kaufman ◽  
George L. Johnston
Keyword(s):  
Canonical Transformation ◽  
Mode Coupling ◽  
Scalar Potential ◽  
Potential Method ◽  
Magnetized Plasma ◽  
First Order ◽  
Interaction Terms ◽  
Novel Approach ◽  
Ponderomotive Forces ◽  
Nonlinear Mode Coupling

A novel approach to the theory of nonlinear mode coupling in hot magnetized plasma is presented. The formulation retains the conceptual simplicity of the familiar ponderomotive-scalar-potential method, but removes the approximations. The essence of the approach is a canonical transformation of the single-particle Hamiltonian, designed to eliminate those interaction terms which are linear in the fields. The new entity (the ‘oscillation centre’) then has no first-order uttering motion, and generalized ponderomotive forces appear as nonlinear terms in the transformed Hamiltonian. This viewpoint is applied to derive a compact symmetric formula for the general three-wave coupling coefficient in hot uniform magnetized plasma, and to extend the conventional ponderomotive-scalar-potential method to the domain of strongly magnetized plasma.

Design Automation of Modular Industrial Robots

2009 ◽  
Author(s):  
Mehdi Tarkian ◽  
Johan O¨lvander ◽  
Xiaolong Feng ◽  
Marcus Petterson
Keyword(s):  
Design Automation ◽  
Parametric Design ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Modular Robots ◽  
Integrated Analysis ◽  
Analysis Tool ◽  
Modeling Methodology ◽  
Novel Approach ◽  
Main Components

This paper presents a novel approach for designing modular robots. There are two main components in this approach namely the modeling methodology of the robot and a framework for simulation of the models and execution of an optimization process. To illustrate the presented methodology an integrated analysis tool for an industrial robot is developed combining dynamic and geometric models in a parametric design approach. An optimization case is conducted to visualize the automation capabilities of the proposed framework, and enhance the design for modular industrial robots.

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