• Journal of Biomedical Engineering Research
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• v.35 no.4
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• pp.99-104
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• 2014

Generally, human eye blinks are closely associated with the cognitive state or visual attention such as attentional requirements on visual stimuli. These previous studies have reported that eye blinks are related to explicit visual attention using blink rate, pattern and blink timing across subjects. However, these results have been obtained in a well-controlled experimental settings. So, it would prove difficult to investigate human's natural response in a continuous and realistic situation. In our study, we measured the eye blink intervals while participants viewed a movie clip. And we analyzed the blink interval data for relationship between visual attention and eye blink intervals. 24 participants took part in two experimental sessions, first session to measure the IEBI while viewing the movie clip and second session to conduct a memory performance test using a self-questionnaire, which were spaced 3 weeks apart. The results indicate significantly higher memory performance at long IEBI period than short IEBI period while watching a movie clip(t = 3.257, df = 17, p < 0.005, 2-tailed). In addition, memory performance score significantly correlated with the IEBI value(spearman's rho = 0.40, N = 36, p < 0.01, 2-tailed). Our results suggest that IEBI is used to measure or assess visual attention while wiewing the movie that it is capable of simulating aspects of real-life experiences by visual attention. Thus, we expect IEBI to be used to measure or assess our visual attention, cognition, further emotion about not only movies, advertisements and other cultural contents but also cognitive science.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.485-491
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• 1997

This paper describes the relationship between skin impedance signal, behavioral signal, and subjective evaluation depending on arousal level. Nz and reaction time had similar trend with mKSS level, but eyeblink rate was different from these two parameters. eye-blink rate increased slowly from mKSS level 1 to 5, and had high increasing rate at mKSS 7. But it showed steep descent at mKSS level 9. Each subject showed different eye-blink rates, but changing rates of EBR was similar at eachm KSS level. Therefore it suggests that rising rate of EBR can be used arousal level criterion. From the result of reaction time test. human performance was decreased rapidly above the mKSS level 5, and false positive and false negative data was observed above the mKSS level 3. It is desirable to give a subject some stimuli such as sound or aroma to rise arousal level between mKSS level 3 and mKSS level 5.

• Journal of IKEEE
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• v.22 no.4
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• pp.1109-1114
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• 2018

Electroencephalogram (EEG) is a tool used to study brain activity caused by external stimuli. In this process, artifacts are mixed and it is easy to distort the signal, so post-processing is necessary to remove it. Independent Component Analysis (ICA) is a widely used method for removing artifact. This method has a disadvantage in that it has excellent performance but some loss of brain wave information. In this paper, we propose a method to reduce EEG information loss by restricting the filter coverage using eye blink information obtained from Eyetracker. We then compared the results of the proposed method with the conventional method using quantization methods such as Signal to Noise Ratio (SNR) and Spectral Coherence (SC).

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.45-50
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• 2021

This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the drowsy driving study, 10 drivers drove approximately 37 km of a monotonous highway (about 22 min) twice. The results suggested that the appropriate duration of eyes continuously closed was 4 seconds. The results from real-world driving data were presented in the other paper - part 1.

• Journal of Korean Elementary Science Education
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• v.32 no.2
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• pp.185-197
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• 2013

The purpose of this study was to analyze the difference between eye movements according to science achievement of elementary school students in observation situation. Science achievement was based on the results of national achievement test conducted in 2012, a random sampling of classes. As an assessment tool to check observation test, two observation measure problems from TSPS (Test of Science Process Skill; developed in 1994) suitable for eye tracking system are adopted. The subjects of this study were twenty students of sixth grade who agreed to participate in the research. SMI (SensoMotoric Instruments)' iView $X^{TM}$ RED was used to collect eye movement data and Experiment 3.1 and BeGaze 3.1 program were used to plan and analyze experiment. As a result, eye movements in observation test varied greatly in fixation duration, frequency, saccade, saccade velocity and eye blink according to students' science achievement. Based on the result of eye movements analysis, heuristic search eye movement was discussed as an alternative to improve underachievers' science achievement.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.38-44
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• 2021

This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the real-world driving study, 52 drivers drove approximately 11.0 km of rural road (about 20 min), 7.9 km of urban road (about 25 min), and 20.8 km of highway (about 20 min). The results suggested that the appropriate number of blinks during the last 60 seconds was 4 times, and the head movement interval was 35 seconds. The results from drowsy driving data will be presented in another paper - part 2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.2
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• pp.122-129
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• 2014

In this study, emotion-classification gathered from users was performed, classification-experiments were then conducted using SVM(Support Vector Machine) and K-means algorithm. Total 15 numbers of channels; CP6, Cz, FC2, T7. PO4, AF3, CP1, CP2, C3, F3, FC6, C4, Oz, T8 and F8 among 32 members of the channels measured were adapted in Brain signals which indicated obvious the classification of emotions in previous researches. To extract emotion, watching DVD and IAPS(International Affective Picture System) which is a way to stimulate with photos were applied and SAM(Self-Assessment Manikin) was used in emotion-classification to users' emotional conditions. The collected users' Brain-wave signals gathered had been pre-processing using FIR filter and artifacts(eye-blink) were then deleted by ICA(independence component Analysis) using. The data pre-processing were conveyed into frequency analysis for feature extraction through FFT. At last, the experiment was conducted suing classification algorithm; Although, K-means extracted 70% of results, SVM showed better accuracy which extracted 71.85% of results. Then, the results of previous researches adapted SVM were comparatively analyzed.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.274-284
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• 2021

Customized services to a sleep induction for better sleepcare are more effective because of different satisfaction levels to users. The EOG data measured at the frontal lobe when a person blinks his eyes can be used as biometric data because it has different values for each person. The accuracy of measurement is degraded by a noise source, such as toss and turn. Therefore, it is necessary to analyze the noisy data and remove them from normal EOG by filtering. There are low-pass filtering and high-pass filtering as filtering using a frequency band. However, since filtering within a frequency band range is also required for more effective performance, we propose a machine learning model for the filtering of EOG data in this paper as the second filtering method. In addition, optimal values of parameters such as the depth of the hidden layer, the number of nodes of the hidden layer, the activation function, and the dropout were found through experiments, to improve the performance of the machine learning filtering model, and the filtering performance of 95.7% was obtained. Eventually, it is expected that it can be used for effective user identification services by using filtering model for EOG data.

• Korean Institute of Interior Design Journal
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• v.20 no.3
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• pp.135-142
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• 2011

There occurs subtle shaking in our eyes while in looking at objects and this study sets up the standard of reconciliation from the property of observation and organizes the property of data reconciliation by the observation range to secure the feasibility of reconciliation range and method of the original data obtained from observation experiment and its analysis process. The results from above study can be concluded as in the followings: First, it made clear the process to exclude eye blink and data out of image range from the original data so to set up the range of available data. Second, on the basis of existing theory, it was possible to define the minimum attention time as 0.1 second (3 times of observation) and the visual understanding time of space as 0.3 second (9 times of observation) in the study on the property of observation, and this definition of observation time of sight fixation becomes an important indicator in the analysis of observation data. Third, based on the observation theory of continuity securing and attention, it was able to arrange the standard of reconciliation by carrying out reconciliation works only when fixed data with more than three times of observation showed consecutively before and behind the data with intermittent movements. Fourth, In the sector whether visual understanding occurred (more than 9 times), it increased by 12% for the frequency of observation and by 7.8% for the times of observation compared with the ones before the reconciliation. These results showed to have a constant change by subjects so that it was able to arrange a foundation to secure objective data in the analysis of the observation range and its extent.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.813-815
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• 2016

This paper implements a device control system based on the brain wave data. Brain-Computer Interface (BCI) technology can pass directly to the system without going through the operation of the language or body. By controlling the device to detect brain waves in real time according to the change of status it helps to ease life for a variety of services, such as disabled people with limited mobility or students, people who need multi-tasking. In addition, it is possible to develop an application service such as the home device control system. A device control system implemented in the paper based on the data collected from the EEG Headset associated to control the power of the smart phone and audio. Control the power ON / OFF operation by the Attention, and support service functions to control the audio by the Meditation and Eye blink. It was confirmed that the device control using the brain wave data to be operated through a laboratory test successfully.