• Title/Summary/Keyword: EEG curve

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A Study of the Relationship between Driver's Anxiety EEG & Driving Speed in Motorway Sections (주행속도와 기하구조에 따른 운전자 불안뇌파 분석 -고속주행시를 중심으로-)

  • Lim, Joon-Bum;Lee, Soo-Beom;Kim, Keun-Hyuk;Kim, Sang-Youp;Choi, Jai-Sung
    • Journal of the Korean Society of Safety
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    • v.27 no.3
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    • pp.167-175
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    • 2012
  • For establishing a standard of design element of the smart highway, this study investigated driver's anxiety EEG according to running speeds and geometric designs. Also, the experiment was implemented on 60 subjects. Based on running speed data and brainwave data, which were obtained from the experiment, this study analyzes anxiety EEG according to running speeds and geometric designs, and finally draws a forecasting model of anxiety EEG by selecting affecting factors of anxiety EEG. Forecasting model shows that left curve is the most influential on anxiety EEG figure. The reason is because when driver is driving on the first-lane, his or her visibility is impeded by a median strip. For this reason, anxiety EEG figure increases. And also steep downward slope and large radius of curve are heavily influential on driver's anxiety EEG figure. It is judged that anxiety EEG figure is increased by high speed on those section. Thus, the forecasting model of anxiety EEG suggested on this study will be utilized for design phase, and will decide the design speed on the superhighway. So, it will be used to make practical and safety road.

A Study for Distribution Methods Between Superelevation and Side Friction Factor Reflecting Ergonomic Characteristics by Increasing Design Speed (설계속도 상향에 따른 인간공학적 특성을 반영한 편경사와 횡방향마찰계수 분배방법에 관한 연구)

  • Jeong, Seungwon;Kim, Sangyoup;Choi, Jaisung;Kim, Hongjin;Jang, Taeyoun
    • International Journal of Highway Engineering
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    • v.15 no.3
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    • pp.103-115
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    • 2013
  • PURPOSES: The purpose of this study is to develop a method for distribution between superelevation and side friction factor by increasing design speed. METHODS: First of all, a method for distribution between superelevation and side friction factor and a theory for the functional formula of side friction factor in compliance with horizontal radius applied in South Korea and the United States are considered. Especially, design speed of 140km/h and numerical value of design elements are applied to the theory for the functional formula of side friction factor in AASHTO's methods. Also, the anxiety EEG upon running speed is measured to reflect ergonomic characteristics through field experiments at seven curve sections of the West Coast Freeway, and this data is applied to graph for the functional formula of side friction factor. RESULTS : Matching side friction factor against the anxiety EEG, the results that a critical points of driver's anxiety EEG sharply increase locate under existing parabola are figured out. CONCLUSIONS : Therefore, we could get a new type of the functional formula that driver's driving comfortability is guaranteed if the existing the functional formula of side friction factor goes down under boundary of the critical points of the anxiety EEG.

Adverse Effects on EEGs and Bio-Signals Coupling on Improving Machine Learning-Based Classification Performances

  • SuJin Bak
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.133-153
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    • 2023
  • In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

A GAUSSIAN SMOOTHING ALGORITHM TO GENERATE TREND CURVES

  • Moon, Byung-Soo
    • Journal of applied mathematics & informatics
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    • v.8 no.3
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    • pp.731-742
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    • 2001
  • A Gaussian smoothing algorithm obtained from a cascade of convolutions with a seven-point kernel is described. We prove that the change of local sums after applying our algorithm to sinusoidal signals is reduced to about two thirds of the change by the binomial coefficients. Hence, our seven point kernel is better than the binomial coefficients when trend curves are needed to be generated. We also prove that if our Gaussian convolution is applied to sinusoidal functions, the amplitude of higher frequencies reduces faster than the lower frequencies and hence that it is a low pass filter.

Development of a Method of Cybersickness Evaluation with the Use of 128-Channel Electroencephalography (128 채널 뇌파를 이용한 사이버멀미 평가법 개발)

  • Han, Dong-Uk;Lee, Dong-Hyun;Ji, Kyoung-Ha;Ahn, Bong-Yeong;Lim, Hyun-Kyoon
    • Science of Emotion and Sensibility
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    • v.22 no.3
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    • pp.3-20
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    • 2019
  • With advancements in technology of virtual reality, it is used for various purposes in many fields such as medical care and healthcare, but as the same time there are also increasing reports of nausea, eye fatigue, dizziness, and headache from users. These symptoms of motion sickness are referred to as cybersickness, and various researches are under way to solve the cybersickness problem because it can cause inconvenience to the user and cause adverse effects such as discomfort or stress. However, there is no official standard for the causes and solutions of cybersickness at present. This is also related to the absence of tools to quantitatively measure the cybersickness. In order to overcome these limitations, this study proposed quantitative and objective cybersickness evaluation method. We measured 128-channel EEG waves from ten participants experiencing visually stimulated virtual reality. We calculated the relative power of delta and alpha in 11 regions (left, middle, right frontal, parietal, occipital and left, right temporal lobe). Multiple regression models were obtained in a stepwise manner with the motion sickness susceptibility questionnaire (MSSQ) scores indicating the susceptibility of the subject to the motion sickness. A multiple regression model with the highest under the area ROC curve (AUC) was derived. In the multiple regression model derived from this study, it was possible to distinguish cybersickness by accuracy of 95.1% with 11 explanatory variables (PD.MF, PD.LP, PD.MP, PD.RP, PD.MO, PA.LF, PA.MF, PA.RF, PA.LP, PA.RP, PA.MO). In summary, in this study, objective response to cybersickness was confirmed through 128 channels of EEG. The analysis results showed that there was a clearly distinguished reaction at a specific part of the brain. Using the results and analytical methods of this study, it is expected that it will be useful for the future studies related to the cybersickness.

Evaluation of Effectiveness on Delineation System Using Virtual Driving Simulator (가상주행 시뮬레이터를 활용한 시선유도시설 효과평가 연구)

  • Park, Jejin;Kim, Ducknyung;Park, Yongjin;Song, Wonchul
    • International Journal of Highway Engineering
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    • v.19 no.5
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    • pp.163-171
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    • 2017
  • PURPOSES : Traffic safety facilities are used to prevent traffic accidents before they occur by providing drivers with information on traffic situations and the geometric design of roads. However, some facilities not defined in guidelines do not meet installation criteria, yet are being installed and used in order to increase efficiency in traffic flow and prevent traffic accidents in a specific expressway zone. In this study, we have evaluated the effect of delineation system which are not defined in the guideline criteria. METHODS : Different virtual scenarios were created for roads using expressway median barrier chevron signs, with a driving simulator used to evaluate the installation and operational effect of such signs. Ten experiments were performed with left- and right-curved roads at curve radius intervals of 500 m, from 500 m to 2,500 m. RESULTS : For sections with a curve radius of more than 1,500 m, drivers had a clear tendency toward stable driving regardless of delineation system. When a chevron sign is installed on a protection fence in the road curving left, an expanded installation is recommended up to the section with a curve radius of 1,000 m. According to the analysis results for the RHB (Relative High Beta spectrum), driving concentration also improved up to a curve radius of 1,000 m. CONCLUSIONS :The experiment result indicates the extent of biasing within a lane and the manipulation amount of steering handle, were analyzed and found to be affected by curve radius and road alignment regardless of delineation system.

Machine Learning for Flood Prediction in Indonesia: Providing Online Access for Disaster Management Control

  • Reta L. Puspasari;Daeung Yoon;Hyun Kim;Kyoung-Woong Kim
    • Economic and Environmental Geology
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    • v.56 no.1
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    • pp.65-73
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    • 2023
  • As one of the most vulnerable countries to floods, there should be an increased necessity for accurate and reliable flood forecasting in Indonesia. Therefore, a new prediction model using a machine learning algorithm is proposed to provide daily flood prediction in Indonesia. Data crawling was conducted to obtain daily rainfall, streamflow, land cover, and flood data from 2008 to 2021. The model was built using a Random Forest (RF) algorithm for classification to predict future floods by inputting three days of rainfall rate, forest ratio, and stream flow. The accuracy, specificity, precision, recall, and F1-score on the test dataset using the RF algorithm are approximately 94.93%, 68.24%, 94.34%, 99.97%, and 97.08%, respectively. Moreover, the AUC (Area Under the Curve) of the ROC (Receiver Operating Characteristics) curve results in 71%. The objective of this research is providing a model that predicts flood events accurately in Indonesian regions 3 months prior the day of flood. As a trial, we used the month of June 2022 and the model predicted the flood events accurately. The result of prediction is then published to the website as a warning system as a form of flood mitigation.

Review on the Relative Sea-level Changes in the Yellow Sea during the Late Holocene (한반도 서해안의 후기 홀로세 해수면 변동 곡선에 대한 검토)

  • Choi, Sung-Ja
    • Economic and Environmental Geology
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    • v.51 no.5
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    • pp.463-471
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    • 2018
  • In this paper, we review previous studies on the relative sea-level changes in the Yellow Sea during the Holocene to comprehensive understand the various research results. Currently, it is reported two theories : 1) the Holocene sea-level has never been higher than the present-day level; and 2) sea-level have reached highstand during mid-Holocene, followed by slow lowering to that of the present. The first theory yields a curve that is similar to a climate-change-related eustatic sea-level curve. However, in reality, most of the relative sea-level fluctuation resulted from land uplift or subsidence. The second theory yields a curve that is fairly coincident with a relative sea-level curve indicative of continental margins being located away from the ice sheets(i.e., far-field), and is considered as an effect of GIA(Glacio Isostatic Adjustment) and gravitational attraction. Based on detailed review of previous researches, we realized that they sourced the same papers, but obtained different results because they selectively chose and added the data. The data used to derive the second theory pertain to the northern Gunsan region, which is located within the western area of the Chugaryeong fault. Thus, we believe that the sea-level curve for the second theory is only representative of the area north of Gunsan, which is subject to GIA and tectonic deformation. Although the relative sea-level curve for the west coastal area is comparable to that for the far-field continental margin region, it is necessary to evaluate local tectonic activities as suggested by active seismicity in the west coastal area and the more than 400 faults currently existing in on the Korean Peninsula.

1-D Shear Wave Velocity Structure of Northwestern Part of Korean Peninsula (한반도 북서부의 1차원 전단파 속도구조)

  • Kim, Tae Sung
    • Economic and Environmental Geology
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    • v.52 no.6
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    • pp.555-560
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    • 2019
  • One-dimensional shear wave velocity structure of North Korea is constrained using short (2-sec) to long period (30-sec) Rayleigh waves generated from four seismic events in China. Rayleigh waves are well recorded at the five broadband seismic stations (BRD, SNU, CHNB, YKB, KSA) which are located near to the border between North and South Korea. Group velocities of fundamental-mode Rayleigh waves are estimated with the Multiple Filter Analysis and refined by using the Phase Matched Filter. Average group velocity dispersion curve ranging from 2.9 to 3.2 km/s, is inverted to constrain the shear wave velocity structures. Relatively low group velocity dispersion curves along the path between the events to BRD at period from 4 to 6 seconds may correspond to the sedimentary sequence of the West Korea Bay Basin (WKBB) in the Yellow Sea. The low velocity zone in deep layers (14-20 km) may be related to the deep sedimentary structure in Pyongnam basin. The fast shear wave velocity structure from the surface to the depth of 14 km is consistent with the existence of metamorphic rocks and igneous bodies in Nangrim massif and Pyongnam basin.

Application of RTI to Improve Image Clarity of a Trace Fossil Cochlichnus Found from the Jinju and Haman Formations

  • Sangho Won;Dal-Yong Kong
    • Economic and Environmental Geology
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    • v.56 no.4
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    • pp.397-408
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    • 2023
  • A total of 64 specimens of trace fossils were collected from the Jinju Formation of the construction site of Jinju Aviation Industrial Complex, and from the Haman Formation of Namhae Gain-ri fossil site. The fossils are continuously and regularly meandering sine-curve in shape. The fossil varies in morphology: width between 0.2 and 5.6 mm, wavelength between 1.5 and 28 mm, and amplitude between 0.9 and 7.9 mm; the Jinju specimens are commonly wider than the Haman ones. The ratio of wavelength to amplitude is more or less regular regardless of width of the specimen, and the linear correlation of the ratios shows that the Jinju specimens fit better than the Haman specimens. Taking all morphometric parameters, specimens in all size ranges are temporarily identified as ichnospecies Cochlichnus anguineus. In order to obtain more distinct and clearer images of Cochlichnus, we selected two specimens and applied a new imaging technology RTI. For photography of the trace fossils, 50 to 80 images were taken per set with photometric lighting close to the surface and horizontally. RTI technology clearly showed that the images of tiny fossils were improved: the surface contrast become sharper and messy and unnecessary information disappeared. Currently, RTI technology is used in many fields including preservation of cultural properties and archaeology. As a consequence, we hope to apply this technique to the field of paleontology, especially to the study of trace fossils of very small size.