• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.306-312
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• 2022

During the unprecedented COVID-19 outbreak, the public's information needs created an environment where they overwhelmingly consume information on the chronic disease. Given that news media affect the public's emotional well-being, the pandemic situation highlights the importance of paying particular attention to how news stories frame their coverage. In this study, COVID-19 news speech emotion from mainstream broadcasters in South Korea and the United States (US) were analyzed using convolutional neural networks. Results showed that neutrality was detected across broadcasters. However, emotions such as sadness and anger were also detected. This was evident in Korean broadcasters, whereas those emotions were not detected in the US broadcasters. This is the first quantitative vocal emotion analysis of COVID-19 news speech. Overall, our findings provide new insight into news emotion analysis and have broad implications for better understanding of the COVID-19 pandemic.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.35-43
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• 2023

Emotion recognition while driving is an essential task to prevent accidents. Furthermore, in the era of autonomous driving, automobiles are the subject of mobility, requiring more emotional communication with drivers, and the emotion recognition market is gradually spreading. Accordingly, in this research plan, the driver's emotions are classified into seven categories using psychological and behavioral data, which are relatively easy to collect. The latent vectors extracted through the auto-encoder model were also used as features in this classification model, confirming that this affected performance improvement. Furthermore, it also confirmed that the performance was improved when using the framework presented in this paper compared to when the existing EEG data were included. Finally, 81% of the driver's emotion classification accuracy and 80% of F1-Score were achieved only through psychological, personal information, and behavioral data.

• Science of Emotion and Sensibility
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• v.23 no.3
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• pp.47-62
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• 2020

The snake detection theory posits that, due to competition with snakes, the primate visual system has been evolved to detect camouflaged snakes. Specifically, one of its hypotheses states that the subcortical visual pathway mainly consisting of koniocellular cells enables humans to automatically detect the threat of snakes without consuming mental resources. Here we tested the hypothesis by comparing human participants' responses to snakes with those to fearful faces and flowers. Participants viewed either original images or converted ones, which lacked the differences in color, luminance, contrast, and spatial frequency energies between categories. While participants in Experiment 1 produced valence and arousal ratings to each image, those in Experiment 2 detected target images in the breaking continuous flash suppression (bCFS) paradigm. As a result, visual factors influenced the responses to snakes most strongly. After minimizing visual differences, snakes were rated as being less negative and less arousing, and detected more slowly from suppression. In contrast, the images of the other categories were less affected by image conversion. In particular, fearful faces were rated as greater threats and detected more quickly than other categories. In addition, for snakes, changes in arousal ratings and those in bCFS response times were negatively correlated: Those snake images, the arousal ratings of which decreased, produced increased detection latency. These findings suggest that the influence of snakes on human responses to threat is limited relative to fearful faces, and that detection responses in bCFS share common processing mechanisms with conscious ratings. In conclusion, the current study calls into question the assumption that snake detection in humans is a product of unconscious subcortical visual processing.

• Korean Journal of Biological Psychiatry
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• v.20 no.4
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• pp.119-128
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• 2013

Objectives Memory impairment is a very important mental health issue for elderly and adults. Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Early detection of the prodromal stage of patients with AD is an important topic of interest for both mental health clinicians and policy makers. Methods Electroencephalograpgy (EEG) has been used as a possible biological marker for patients with MCI, and AD. In this review, we will summarize the clinical implications of EEG and ERP as a biological marker for AD and MCI. Results EEG power density, functional coupling, spectral coherence, synchronization, and connectivity were analyzed and proved their clinical efficacy in patients with the prodromal stage of AD. Serial studies on late event-related potentials (ERPs) were also conducted in MCI patients as well as healthy elders. Even though these EEG and ERP studies have some limitations for their design and method, their clinical implications are increasing rapidly. Conclusion EEG and ERP can be used as biological markers of AD and MCI. Also they can be used as useful tools for early detection of AD and MCI patients. They are useful and sensitive research tools for AD and MCI patients. However, some problems remain to be solved until they can be practical measures in clinical setting.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.202-205
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• 2009

체력이나 건강을 위한 트레이닝이나 심장 질환자의 생체신호 모니터링을 위해 다양하게 사용되는 심전도는 현재 여러가지 장비형태로 사용되고 있다. 최근에는 착용자가 인식하지 않고 손쉽고 편안한 방법으로 측정하거나 모니터링 할 수 있는 형태의 생체신호 모니터링 의복에 관한 연구가 많이 진행되고 있다. 본 연구에서는 20대 남성의 체표면 분석을 통해 심전도 검출이 가능한 일체형 의복을 설계하고 제작된 시제품의 착의평가를 진행하였다. 심전도 측정이 가장 효과적인 흉부 부분을 중심으로 심전도 데이터 추출 정확성을 위해 다층구조로 센서를 설계하고, 흉부의 움직임을 최소화하여 노이즈를 감소할 수 있는 디자인을 제안한 결과, 심전도 데이터 추출 정확성 및 편의성은 향상되고 노이즈는 감소하는 결과를 도출하였다.

• Science of Emotion and Sensibility
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• v.4 no.1
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• pp.61-67
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• 2001

This paper described the effect of subjective approach in case of the human sensibility experiments. The procedure is proceeded subjectively. Human faces are selected as the image presentation media. Pleasant and unpleasant images are selected directly by examiner, And also the image presentation system, which is executed with a computer and has the square-type black box monitor equipment, is manufactured. Images are presented with the step-variation time interval technique. questionnaire test and EEG signal detection data are analyzed. The analysis parameters are a “frequency band integral value” and a “band differential variation ratio”. he results show the high sensibility and fast response. The fact that image presenting repetition alleviates is verified.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.169-172
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• 2009

본 연구에서는 P300에 기초한 유죄지식검사에서 목표자극과 관련자극, 무관련자극을 제시하는 횟수가 검사의 정확도에 미치는 영향을 평가하였다. 이를 위하여, 한 집단의 실험참여자들에게는 모의범죄를 수행한 후 P300에 기초한 유죄지식검사를 실시하였으며, 다른 집단의 실험참여자들에게는 모의범죄를 수행하지 않은 상태에서 P300에 기초한 유죄지식 검사를 실시하였다. 모든 실험참여자들에게 목표자극 1개와 관련자극 1개, 무관련자극 4개를 각각 120회씩 총 720회 제시하였다. 실험결과, 유죄조건에서 관련자극은 시행수가 증가함에 따라서 P300의 크기가 감소하는 습관화 현상을 보이는 경향이 있었으며, 시행수가 증가함에 따라서 유죄판단을 위한 통계적 지수가 달라지는 경향이 있었다. 시행수가 40회에서 80회 사이일 때, 가장 높은 정확도가 나타나는 것으로 보였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.321-324
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• 2002

본 논문에서는 다양한 환경하에서 인간의 식별과 감정을 인식할 수 있는 감정 인식 알고리즘을 제안한다. 제안된 알고리즘을 구현하기 위해, 먼저, CCD 칼라 카메라에 의해 획득한 원 영상으로부터 피부색을 이용해 얼굴영상을 얻는 과정을 거친다. 그 다음, 주요 요소분석을 기본으로 하는 얼굴인식기술인 Eigenface를 사용하여 이미지들을 고차원의 픽셀공간으로부터 저차원공간으로의 변환하는 파정을 거친다. 제안된 개인에 대한 식별과 감성인식은 사용한 특징벡터들의 추출로 인한 Eigenface의 가중치와 상관관계를 통해 이루어진다 즉, 영상의 가중치로부터 개인에 대한 식별과 감성정보를 찾는 방법을 제안한다. 마지막으로, 실험을 통해 제안된 방법의 응용가능성을 보인다.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.21-28
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• 2022

People differ greatly in their capacity to persist in the face of challenges. Despite significant research, relatively little is known about cognitive factors that might be involved in perseverance. Building upon human threat-management mechanism, we predicted that perseverant people would be characterized by reduced sensitivity (i.e., longer detection latency) to threat cues. Our data from 5,898 job applicants showed that highly perseverant individuals required more time to correctly identify anger in faces, regardless of stimulus type (dynamic or static computer-morphed faces). Such individual differences were not observed in response to other facial expressions (happiness, sadness), and the effect was independent of gender, dispositional anxiety, or conscientiousness. Discussions were centered on the potential role of threat sensitivity in effortful pursuit of goals.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.112-118
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• 2009

This paper proposes a rapid detection algorithm of a salient region for music video browsing system, which can be applied to mobile device and digital video recorder (DVR). The input music video is decomposed into the music and video tracks. For the music track, the music highlight including musical chorus is detected based on structure analysis using energy-based peak position detection. Using the emotional models generated by SVM-AdaBoost learning algorithm, the music signal of the music videos is classified into one of the predefined emotional classes of the music automatically. For the video track, the face scene including the singer or actor/actress is detected based on a boosted cascade of simple features. Finally, the salient region is generated based on the alignment of boundaries of the music highlight and the visual face scene. First, the users select their favorite music videos from various music videos in the mobile devices or DVR with the information of a music video's emotion and thereafter they can browse the salient region with a length of 30-seconds using the proposed algorithm quickly. A mean opinion score (MOS) test with a database of 200 music videos is conducted to compare the detected salient region with the predefined manual part. The MOS test results show that the detected salient region using the proposed method performed much better than the predefined manual part without audiovisual processing.