The Effect of Visual Stimulus on Voluntary Eye Movement Based on a VOR/OKR Model

Son, Le Anh; Inagami, Makoto; Hamada, Hiroto; Suzuki, Tatsuya; Aoki, Hirofumi

doi:10.20485/jsaeijae.8.2_37

Cited by 6 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This data can be used to simulate eye movement based on head movement such as [2] , [3] , Obinata group [4] , [5] , [6] , [7] , [8] , [9] , Anh Son et al [10] , [11] , [12] , [13] , [14] , [15] , and so on. In addition, this data can use to see the effect of a visual stimulus or mental workload on driver performance as well as eye movement.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

SmartEye and Polhemus data for vestibulo–ocular reflex and optokinetic reflex model

Son

Aoki

2018

Data in Brief

Self Cite

View full text Add to dashboard Cite

In this data article, this dataset included raw data of head and eye movement that collected by Polhemus (Polhemus Inc) and SmartEye (Smart Eye AB) equipment. Subjects who have driver license participated in this experiment. The experiment was conducted with a driving simulator that was controlled by CarSim (Mechanical simulation Co., Anna Arbor, MI) with the vehicle motion. This data set not only contained the eye and head movement but also had eye gaze, pupil diameter, saccades, and so on. It can be used for the parameter identification of the vestibulor-ocular reflex (VOR) model, simulation eye movement, as well as running other analysis related to eye movement.

show abstract

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

SmartEye and Polhemus data for vestibulo–ocular reflex and optokinetic reflex model

Son

Aoki

2018

Data in Brief

Self Cite

View full text Add to dashboard Cite

show abstract

“…For example, VOR has been analyzed by OpenGL visualization for camera movements to evaluate image stabilization [21]. Moreover, the visual stimulus has been analyzed during a car drive to develop a model based on VOR and OKR [22]. Discussion of researches on the topic that address used models, problems and solutions, designs of robots, control methods, and system behavior can be seen in comprehensive reviews, such as [2] and [23].…”

Section: Introductionmentioning

confidence: 99%

A Novel Algebraic Inverse Kinematics Based Approach to Gaze Control in Humanoid Robots

Alshakhs,

Mysorewala,

Saif

et al. 2023

IEEE Access

View full text Add to dashboard Cite

The vision system of humanoid robots is one of the essential components that allow them to do complex activities. This has led to numerous studies on artificial gaze stabilization, many of which are based on biological vision system reflexes. The gaze stabilization solution includes image capture and processing, inverse kinematics, and feedback control to achieve the desired gaze behavior. Generally, the multi-solution problem of finding the desired gaze direction and the inverse kinematics problem of finding the desired joints are solved by using cost functions and numerical solvers. This results in disadvantages that include long processing time, uncertain number of iterations, and risk of numerical instability. In this work, an alternative algebraic method is introduced by exploiting the cascading structure of the neck and eye. By using direct equations instead of numerical solving, the multi-solution and inverse kinematics problems are solved utilizing the geometrical structure and the proposed virtual configurations. Moreover, a sliding mode controller is designed to move the neck-eye joints to their desired positions. The developed scheme is simulated in the MATLAB/SIMULINK environment. Results for various scenarios show that the system can effectively gaze at different stationary and moving targets, showing human-like gaze behavior. In terms of timing, the desired gaze direction is quickly achieved and stabilized, whereas the neck-eye system dynamics stay longer. For one of the simulation cases presented, it took 0.3 seconds to achieve the desired gaze direction for the dynamics of more than 1 second.INDEX TERMS Degrees of freedom (DOF), face direction, gaze control, gaze stabilization, humanoid, iCub, inverse kinematics (IK), numerical solution, vestibulo-ocular reflex (VOR).

show abstract

“…Another potential method is to use the involuntary eye movements based on the vestibulo-ocular reflex model that are simulated by head movements or by vibrations from the moving vehicle. In this method, differences between predicted and actual eye simulation are assessed as a measure of mental workload (Obinata et al, 2008 , 2009 , 2010 ; Aoki et al, 2015 ; Anh Son et al, 2016 , 2017a , b , c , d , e , 2018 ; Le and Aoki, 2018 ; Son and Hirofumi, 2018 ; Son et al, 2018 ) However, the use of eye information to measure mental workload still has some limitations, such as oversensitivity to light, vibration, noise, and visual information.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Classifying Driver Mental Workload Under Naturalistic Conditions With Information From Near-Infrared Spectroscopy

Son

Aoki

Murase

et al. 2018

Front. Hum. Neurosci.

Self Cite

View full text Add to dashboard Cite

Driver cognitive distraction is a critical factor in road safety, and its evaluation, especially under real conditions, presents challenges to researchers and engineers. In this study, we considered mental workload from a secondary task as a potential source of cognitive distraction and aimed to estimate the increased cognitive load on the driver with a four-channel near-infrared spectroscopy (NIRS) device by introducing a machine-learning method for hemodynamic data. To produce added cognitive workload in a driver beyond just driving, two levels of an auditory presentation n-back task were used. A total of 60 experimental data sets from the NIRS device during two driving tasks were obtained and analyzed by machine-learning algorithms. We used two techniques to prevent overfitting of the classification models: (1) k-fold cross-validation and principal-component analysis, and (2) retaining 25% of the data (testing data) for testing of the model after classification. Six types of classifier were trained and tested: decision tree, discriminant analysis, logistic regression, the support vector machine, the nearest neighbor classifier, and the ensemble classifier. Cognitive workload levels were well classified from the NIRS data in the cases of subject-dependent classification (the accuracy of classification increased from 81.30 to 95.40%, and the accuracy of prediction of the testing data was 82.18 to 96.08%), subject 26 independent classification (the accuracy of classification increased from 84.90 to 89.50%, and the accuracy of prediction of the testing data increased from 84.08 to 89.91%), and channel-independent classification (classification 82.90%, prediction 82.74%). NIRS data in conjunction with an artificial intelligence method can therefore be used to classify mental workload as a source of potential cognitive distraction in real time under naturalistic conditions; this information may be utilized in driver assistance systems to prevent road accidents.

show abstract

The Effect of Visual Stimulus on Voluntary Eye Movement Based on a VOR/OKR Model

Cited by 6 publications

References 10 publications

SmartEye and Polhemus data for vestibulo–ocular reflex and optokinetic reflex model

SmartEye and Polhemus data for vestibulo–ocular reflex and optokinetic reflex model

A Novel Algebraic Inverse Kinematics Based Approach to Gaze Control in Humanoid Robots

A Novel Method for Classifying Driver Mental Workload Under Naturalistic Conditions With Information From Near-Infrared Spectroscopy

Contact Info

Product

Resources

About