• International conference on construction engineering and project management
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• 2022.06a
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• pp.760-767
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• 2022

This paper introduces alert fatigue and presents methods to measure alert fatigue by using physiological signals. Alert fatigue is a phenomenon that which an individual is constantly exposed to frequent alarms and becomes desensitized to them. Blind spots are one leading cause of struck-by accidents, which is one most common causes of fatal accidents on construction sites. To reduce such accidents, construction equipment is equipped with an alarm system. However, the frequent alarm is inevitable due to the dynamic nature of construction sites and the situation can lead to alert fatigue. This paper introduces alert fatigue and proposes methods to use physiological signals such as electroencephalography, electrodermal activity, and event-related potential for the measurement of alert fatigue. Specifically, this paper presents how raw data from the physiological sensors measuring such signals can be processed to measure alert fatigue. By comparing the processed physiological data to behavioral data, validity of the measurement is tested. Using preliminary experimental results, this paper validates that physiological signals can be useful to measure alert fatigue. The findings of this study can contribute to investigating alert fatigue, which will lead to lowering the struck-by accidents caused by blind spots.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.15 no.2
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• pp.127-140
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• 2011

Objectives: Acupuncture has been shown to relieve pain and modulate biological function by stimulating the organ-specific meridians and enhances parasympathetic activity and suppresses sympathetic activity. The aim of this review is to summarize and understand the effects of acupuncture on autonomic nervous system. Methods: We reviewed a total of 29 studies published from 2000 to 2010 searched by PueMed and various domestic oriental medicine journals to obtain acupuncture studies related with ANS. Each article was classified by ANS measurement index and reviewed for study objectives, outcomes, acupuncture points, experimental and control interventions. Results: In the study of acupuncture about EEG, HRV, SCR, the experiment results are not the same by acupoints. Although same acupoint the results differ by subject's condition. But the study showed some clear tendency. In brief, in normal states acupuncture enhanced either vagal or sympathetic tone depending on the stimulated acupuncture point sites. On the other hand, most of studies demonstrated that acupuncture restored the autonomic dysfunctions in various kinds of tired or stressful states. Conclusions: We reviewed studies that contributed to an understanding of the effects and mechanisms of acupuncture on autonomic nervous system. Although the relationship between acupuncture and ANS response is still uncertain, acupuncture could be a excellent treatment method for modulating autonomic dysfunction.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.27-34
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• 2010

This paper presents a methodology for classifying left and right motor imagery using a neural network with weighted fuzzy membership functions (NEWFM) and wavelet-based feature extraction. Wavelet coefficients are extracted from electroencephalogram(EEG) signal by wavelet transforms in the first step. In the second step, sixty numbers of initial features are extracted from wavelet coefficients by the frequency distribution and the amount of variability in frequency distribution. The distributed non-overlap area measurement method selects the minimized number of features by removing the worst input features one by one, and then minimized six numbers of features are selected with the highest performance result. The proposed methodology shows that accuracy rate is 86.43% with six numbers of features.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.671-677
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• 2012

A black-box program was implemented in order to monitor abnormal symptoms of human body irregularly occurring during sleep. The system consists of sensor probing body signals, auxiliary devices such as the alarm, lamp, network camera, and signal monitoring computer. Various types of sensors, PPG, ECG, EEG, temperature, respiration sensor, G-sensor, and microphone were used to more exactly identify the causes of abnormal symptoms. If a symptom occurs, the system records the patient's condition to provide information being utilized in the treatment. The sensors are attached on some locations of body being proper to check a specific type of abnormal reaction. Based on the normal range and type of measurement data, criteria of signal levels were set to distinguish abnormal reaction. An abnormal signal being probed, the program starts to operate the lamp, alarm, and network camera at the same time and stores the signal and video data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.459-465
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• 2017

This research aims to assess whether neurofeedback training can reduce theta waves in adolescents. The experiment was conducted on 35 early youths living in Gyeonggi-do at youth counseling centers during April-October. According to circumstances and opinions of participants in the pre-brain analysis, they were classified into a non-training group (A), 12-week training group (B), and 24-week training group (C), containing 10, 15, and 10 members, respectively. EEG measurement and neurofeedback training was performed using the prefrontal 2-channel NeuroharmonyS and Brain Optimization program. EEG data was processed utilizing Brain Analysis ver1.3. Deducted data was converted to SPSS 21.0 to enable statistical processing. As a strategy to reduce theta through the Beta increase training, we applied the appropriate Alpha, SMR, Beta low reward training to the individual. Study results confirmed that theta waves of adolescents decreased through the prefrontal neurofeedback training. Groups (B) and (C) exhibited a greater decrease in theta waves compared with the control group.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.381-391
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• 2017

Biometric technology is a technology for authenticating a user using the physical or behavioral features of the inherent characteristics of the individual. With the necessity and efficiency of the technology in the fields of finance, security, access control, medical welfare, inspection, and entertainment, the service range has been expanding. Biometrics using biometric information such as fingerprints and faces have been exposed to counterfeit and disguised threats and become a social problem. Recent studies using a bio-signal from the inside of the body other than the bio-information of the external body are being developed. This paper analyzes the recent research and technology of biometric systems using bio-signals, ECG, heart sounds, EEG, and EMG to present the skills needed for the development direction. In the future, utilizing the deep learning to build and analyze database to manage bio-signal based big data for the complex condition of individuals, biometrics technologies suitable for real time environment are expected to be researched.

• Journal of Haehwa Medicine
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• v.26 no.1
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• pp.49-57
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• 2017

Objectives : The purpose of this study was to investigate the efficacy of inhalation therapy using Zizyphus jujuba var. spinosa blended oil and spa therapy on stress in adults. Methods : The study design was a double blind, randomized, single center clinical trial. A total of 30 volunteers who were highly stressed and were over 9 points on POMS(profile of mood states) participated in this study. Inhalation therapy using Zizyphus jujuba var. spinosa blended oil and spa therapy were applicate for the experimental group and Jojoba oil inhalation and spa therapy was given for the control group. During the 2 weeks, the participants were treated about inhalation and spa therapy twice a week. The treatment sequence is spa therapy after inhalation therapy. Result : The improvement of stress was evaluated by POMS, HRV(Heart Rate Variability), EEG(Electroencephalography), PSQI(Pittsburgh Sleep Quality Index), salivary cortisol. After treatment, POMS was significantly decreased between the experimental group and the control group. In other measurement(HRV, EEG, PSQI, salivary cortisol) except POMS, there were not significant. Overall, however, they showed a tendency to alleviate stress in the experimental group. Conclusions : We suggest that inhalation therapy using Zizyphus jujuba var. spinosa blended oil and spa therapy might be effective on stress.

• Journal of the Ergonomics Society of Korea
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• v.32 no.4
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• pp.345-353
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• 2013

Objective: This research measured physiological and psychological effects of Vibroacoustic stimulation(VA) to scapular and sacrum of supine position on the mattress. Background: When vibroacoustic stimulation applies to human body, it has a positive influence on physiological and psychological effects by stimulating the organs, tissues and cells of whole body. Method: This experiment was conducted to 10 normal males in two conditions: no stimulation and vibroacoustic stimulation. No stimulation experiment was executed as a supine position for 30 minutes without any vibrational stimulus, while vibroacoustic stimulation was transmitted by the vibrational speaker, which uses 40Hz frequency. Subjects had a laser Doppler flowmeter probe in scapular, sacrum, and also had 8 channel electroencephalogram(EEG) measurement sensor in the scalp. Blood pressure and skin temperature were measured in two conditions with an underlying posture for 30 minutes. Additionally, blood flow rate and EEG were measured before and after for two minutes on two conditions. Results: According to the vibroacoustic stimulation, blood flow rate and skin temperature were increased, while blood pressure was decreased. When using vibroacoustic stimulation compared to no stimulation, blood flow rate went approximately two times higher, and skin temperature also higher 3~4 times. Furthermore, the relative alpha power of brain wave was significantly increased when we applied to vibroacoustic stimulation. Conclusion: This experiment tested the VAT embedded in mattress in two conditions. According to this experiment, VAT decreases blood pressure, improves not only a physiological effect on blood flow rate as well as skin temperature, but also psychological functions by increasing relative alpha power. Application: The results of the publishing trend analysis might help physiological and psychological effects of vibroacoustic stimulation.

• Science of Emotion and Sensibility
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• v.12 no.2
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• pp.205-214
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• 2009

This paper addresses analyzing affective color data for emotional interior design. Both the physical and psychological patterns for spatial colors were tested on thirty subjects, of which fifteen were male. All subjects participated in both the physiological and psychological experiments. The data on the reflecting subjects' affective moods is gathered through EEG physical experiments and SD (Semantic Differential Scale) method surveys. This research has suggested the relation of both experiments through affective color response. The methods of SPSS 10.0 and TeleScan Version 2 are used for analyzing response data to coordinate the colour palette with changeable moods. From the analysis of statistical data, all of the visual stimuli related emotional keywords and physiological responses. Finally, the initial goal of this research is to construct an affective colour database that is tested through human color perception by physical and psychological experiments.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.