• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2329-2337
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• 2013

This study was done objected to the chronic stroke patients in order to evaluate change in brain wave activity and cognitive performance when Neurofeedback training. The subjects were over 6 months ago in chronic stroke patients screened-test through the 20 patients, 10 persons in each group were randomly placed. This was carried out in 4 weeks in total, with control group(n=10) on general physical therapy and experimental group(n=10) on general physical therapy along with Neurofeedback training. The general physical therapy was applied 5 times a week, 30 minutes at once, Neurofeedback training was applied as equally as the general physical therapy, which makes 20 times in total. To learn about the effect before the training, after training, and 2 weeks after the training in electric physiological measurement method of the brain, electroencephalogram(EEG) to examine challenges by calculating the absolute spectrum power for standard EEG change(%), followed by evaluation with clinical assessment tool MMSE-K, Stroop Test, Digit Span Test. As a result of comparing the change in brain wave through EEG, after training and 2 weeks after training showed that absolute ${\alpha}$-power and absolute ${\beta}$-SMR power of experimental group have increased and absolute ${\theta}$-power decreased significantly compared to experimental group I. Moreover, the MMSE-K score in trial appraisal has increased significantly, and the error in Stroop Test and Digit Span Test has decreased significantly. such results, with the chronic stroke patient's brain wave control, Neurofeedback training was determined to improve the cognitive performance. this study suggests a new training possibility of stroke patients by identifying the training effects of Neurofeedback training that trains the brain directly with brain wave control.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.101-116
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• 2011

Current researches on emotion detection classify emotions by using the information from facial, vocal, and bodily expressions, or physiological responses. This study was to review three representative emotion recognition methods, which were based on psychological theory of emotion. Firstly, literature review on the emotion recognition methods based on facial expressions was done. These studies were supported by Darwin's theory. Secondly, review on the emotion recognition methods based on changes in physiology was conducted. These researches were relied on James' theory. Lastly, a review on the emotion recognition was conducted on the basis of multimodality(i.e., combination of signals from face, dialogue, posture, or peripheral nervous system). These studies were supported by both Darwin's and James' theories. In each part, research findings was examined as well as theoretical backgrounds which each method was relied on. This review proposed a need for an integrated model of emotion recognition methods to evolve the way of emotion recognition. The integrated model suggests that emotion recognition methods are needed to include other physiological signals such as brain responses or face temperature. Also, the integrated model proposed that emotion recognition methods are needed to be based on multidimensional model and take consideration of cognitive appraisal factors during emotional experience.

• Knowledge Management Research
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• v.22 no.1
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• pp.39-56
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• 2021

In the current knowledge society, mobile devices have become a useful tool for performing work. In the context of COVID-19 which has made digital transformation inevitable, the importance of mobile work behaviors - performing work tasks through mobile devices - is further highlighted. Drawing from the behavioral immune system theory and cognitive appraisal theory of emotions, this study proposes that individual workers' concern about getting infected by COVID-19 will be negatively related to job satisfaction but positively related to mobile work behaviors. We further propose that leaders' communality and agency trait will be positively related to both job satisfaction and the increase of mobile work behaviors. Analyses of a matched dataset comprising survey data and mobile application usage data from 407 workers showed that their leaders' agency and communality were significantly related to the workers' job satisfaction. However, their mobile productivity was significantly related only to the communality of their leaders. The results of this study will provide useful theoretical and practical implications for researchers and managers who aim to understand and promote the technology adoption and knowledge productivity of workers in a pandemic situation.