• Science of Emotion and Sensibility
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• v.26 no.2
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• pp.117-128
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• 2023

This study aimed to build on past findings about differences in personal walking experiences by demonstrating what elements were beneficial to participants with different walking habits. Accordingly, this study established the relationships between valued walking elements and people's motivation to walk, by dividing participants into three groups: Group W for people with a walking habit, Group HW for people who walk occasionally but not regularly, and Group NW for people who do not walk habitually. Participants walked a familiar and an unfamiliar route with a wearable device that recorded their heart-rate variability and electrodermal activity. Changes in the biometric data helped to identify the defining moments in each participant's walk. Participants discussed these moments in one-on-one interviews with a researcher to pinpoint their valued walking elements. As a result, this study classified walking elements into six themes: "Surroundings," "Social," "Exploration," "Route Plan," "Physical Exercise," and "Mental Thinking." A walking habit development model was made to show how "Route Plan" and "Exploration" were beneficial to Group NW, "Social" and "Surroundings" were beneficial to Group HW, and "Route Plan," "Mental Thinking," and "Physical Exercise" were beneficial to Group W.

• 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.

• ETRI Journal
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• v.45 no.1
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• pp.105-118
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• 2023

We tested the feasibility of automated discrimination of patients with panic disorder (PD) from healthy controls (HCs) based on multimodal physiological responses using machine learning. Electrocardiogram (ECG), electrodermal activity (EDA), respiration (RESP), and peripheral temperature (PT) of the participants were measured during three experimental phases: rest, stress, and recovery. Eleven physiological features were extracted from each phase and used as input data. Logistic regression (LoR), k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) algorithms were implemented with nested cross-validation. Linear regression analysis showed that ECG and PT features obtained in the stress and recovery phases were significant predictors of PD. We achieved the highest accuracy (75.61%) with MLP using all 33 features. With the exception of MLP, applying the significant predictors led to a higher accuracy than using 24 ECG features. These results suggest that combining multimodal physiological signals measured during various states of autonomic arousal has the potential to differentiate patients with PD from HCs.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.387-396
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• 2020

Wearable biosensors have the potential to non-invasively and continuously monitor seniors' stress in their daily interaction with the urban environment, thereby enabling to address the stress and ultimately advance their outdoor mobility. However, current wearable biosensor-based stress detection methods have several drawbacks in field application due to their dependence on batch-learning algorithms. First, these methods train a single classifier, which might not account for multiple subjects' different physiological reactivity to stress. Second, they require a great deal of computational power to store and reuse all previous data for updating the signle classifier. To address this issue, we tested the feasibility of online multi-task learning (OMTL) algorithms to identify multiple seniors' stress from electrodermal activity (EDA) collected by a wristband-type biosensor in a daily trip setting. As a result, OMTL algorithms showed the higher test accuracy (75.7%, 76.2%, and 71.2%) than a batch-learning algorithm (64.8%). This finding demonstrates that the OMTL algorithms can strengthen the field applicability of the wearable biosensor-based stress detection, thereby contributing to better understanding the seniors' stress in the urban environment and ultimately advancing their mobility.

• Anxiety and mood
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• v.3 no.2
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• pp.104-109
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• 2007

Objective : In the present study, we evaluated the differences between the skin electric conductance of patients with posttraumatic stress disorder (PTSD) and normal controls in order to determine the possibility of using skin electric conductance as a diagnostic measure. Method : The PTSD group included 14 subjects who were diagnosed with PTSD in St. Mary's Hospital after a motor vehicle accident, and the normal control group included 12 healthy subjects. The conductivity and capacitance of both groups were measured twice, and the data from each group was compared. Results : There was no significant difference in gender, but the patients in the PTSD group were significantly older than those in normal control group. The activity (conductivity) between the left head-left hand, right hand-right head, and right head-left head was significantly elevated in the PTSD group as compared with the normal control group. In addition, the reactivity (capacitance) between the right head-left head, left head-left hand, right hand-left hand, right hand-right foot, right foot-left foot, and left foot-left hand was significantly elevated in the PTSD group. Conclusion : In this study, the skin electric conductance of the patients with PTSD was significantly elevated in comparison with that of the healthy subjects. Although there were some limitations of this study, the results of this study suggested that skin electric conductance can be used to evaluate elevated psychophysiological responses in patients with PTSD. Future studies with more subjects and more structure are needed in order to confirm our results.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.11a
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• pp.225-229
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• 1998

The purpose of the current study was comparative analysis of autonomic and electrocortical responses to passive and active touch of the tektites with different subjective emotional preference. Perspective goal of the project is development of a template for classification of tactile stimuli according to subjective comfort and associated physiological manifestations. The study was carried out on 36 female college students. Physiological signals were acquired by Grass and B10PAC 100 systems with AcqKnowledge III software. Frontal, parietal and occipital EEG (relative power spectrum /percents/ of EEG bands - delta, theta, slow and fast alpha, low and fast beta), and autonomic variables, namely heart rate (HR), respiratory sinus arrhythmia (RSA), pulse transit time (PTT), respiration rate (RSP) and skin conductance parameters (SCL, amplitude, rise time and number of SCRs) were analyzed for rest baseline and stimulation conditions. Analysis of the overall pattern of reaction indicated that autonomic response to tactile stimulation was manifested in a form of moderate HR acceleration, RSP increase, RSA decrease (lowered vagal tone), decreased n and increased electrodermal activity (increased SCL, several SCRs) that reflects general sympathetic activation. Parietal EEG effects (on contra-lateral side to stimulated hand) were featured by short-term alpha-blocking, slightly reduced theta and significantly increased delta and enhanced fast beta activity with few variations across stimuli. The main finding of the study was that most and least preferred textures exhibited significant differences in autonomic (HR, RSP, PTT, SCR, and at less extent in RSA and SCL) and electrocortical responses (delta, slow and fast alpha, fast beta relative power). These differences were recorded both in passive and active stimulation modes, thus demonstrating reproducibility of distinction between most and least emotionally preferred tactile stimuli, suggesting influence of psychological factors, such as emotional property of stimulus, on physiological outcome. Nevertheless, development of sufficiently sensitive .and reliable template for classification of emotional responses to tactile stimulation based on physiological response pattern may require more extensive empirical database.

• Science of Emotion and Sensibility
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• v.1 no.2
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• pp.13-22
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• 1998

The sense of touch has both objective and subjective characteristics. During hand evaluation of the fabrics. psycho physiological processes such as emotion and stimulation. On other site, the mode of touch (passive vs. active) is also capable to modulate somatosensory responses. I.e., suppress somatocensory perception during active electrocortical responses to passive and active touch of the textiles with different subjective emotional preference. The study was carried out on 36 female college students. Physiological signals were acquired by Grass and BIOPAC 100 systems with AcqKnowledge variables, namely heart rate (HR), respiratory sinus arrhythmia (RSA), pulse transit time (PTT), respiration rate (RSP) and skin conductance parameters (SCL, amplitude, risetime and number of SCRs) were analyzed for baseline and stimulation conditions. Analysis was manifested in a form of moderate HR acceleration. RSP increase, RSA decrease (lowered vagal tone), decreased PTT and increased electrodermal activity (increased SCL, several SCRs) that reflects general sympathetic activation. Parietal EEG effects (on contra-lateral side to stimulated hand)were featured by short-term alpha-blocking, slightly reduced theta, significantly increased delta and enhanced fast beta activity with few variations across stimuli. The main finding of the study was that most and least preferred textures exhibited significant differences in autonomic (HR, RSP, PTT, SCR, and at less extent in RSA and SCL) and electrocortical responses (delta, slow and fast alpha, fast beta relative power). These differences were recorded both in passive and active stimulation modes, thus demonstrating reproducibility of distinction between most and least emotionally preferred tactile stimuli, suggesting influence of psychological factors, such as emotional property of stimulus, on physiological outcome.

• Journal of Biomedical Engineering Research
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• v.42 no.5
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• pp.211-224
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• 2021

Purpose: The purpose of this study is to present a way to alleviate motion sickness(MS) by stimulating acupoint through PEMFs, and to assess the effectiveness of PEMFs against stimulation previously used to stimulate acupoint using biosignal evaluations and surveys. Materials and Methods: Thirteen healthy men participated in the experiment. MS was induced in the participants, and MS relief stimulation was applied for 30 minutes. There were 4 types of MS relief stimulation, and Sham, Reliefband, Transcutaneous electrical nerve stimulation(TENS), and Pulsed electromagnetic fields stimulation(PEMFs) were used. The biosignals were measured during 30 minutes of applying MS relief stimulation, and the symptoms of MS were evaluated through a questionnaire survey. The measured biosignals are Electrocardiogram(ECG), Electrodermal activity(EDA), Respiration, Skin temperature(SKT), and Electrogastrogram(EGG). A one-way ANOVA test was performed for the rate of change by stimulation for MS relief over time. Results: Participants who were stimulated had a sharp decrease in MS symptoms. Biosignals were analyzed to evaluate autonomic nervous system activity, and the parasympathetic nervous system could be activated through stimulation. Conclusion: TENS and PEMFs were more effective in relieving MS symptoms than Reliefband. It is believed that PEMFs will be effective in consideration of the comfort of participants to be applied to actual vehicles, and studies to further verify the effects of PEMFs on MS should be conducted.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.15-25
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• 2000

Cardiac, respiratory, electrodermal and frontal (F3, F4) EEG responses were analyzed and compared during to slides of International Affective Picture System (IAPS) in the study on 42 students. Physiological responses during 20s of exposure to slides intended to elicit happiness (nurturant and erotic), sadness, disgust, surprise, fear or anger emotions were quite similar and were expressed in heart rate (HR) deceleration, decreased HR variability (HRV), specific SCR, increased non-specific SCR frequency (N-SCR), and EEG changes exhibited in theta increase, alpha-blocking and increased beta activity, and frontal asymmetry. However, some emotions demonstrated variations of the response magnitudes, enabling to differentiate some paris of emotions by several physiological parameters. The profiles showed higher magnitudes of HRV and EEG responses in exciting (i.e., erotic) and higher cardiac and respiratory responses in surprise. The most different pairs were exciting-surprise (by HR, HRV, theta, and alpha asymmetry), exciting-sadness (by theta, alpha, and alpha asymmetry), and exciting-fear (by HRV, theta, F3 alpha, and alpha asymmetry). Nurturant happiness yielded the least differentiation. Differences were found as well within negative emotions, e.g., anger-sadness were differentiated by HRV and theta asymmetry, while disgust-fear by N-SCR and beta asymmetry. Obtained results suggest that magnitudes of profiles of physiological variables differentiate emotions evoked by affective pictures, despite that the patterns of most responses were featured by qualitative similarity in given passive viewing context.