• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.11
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• pp.502-510
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• 2006

In this paper, we describe implementation of a computer access device for the severly motor-disability. Many people with severe motor disabilities need an augmentative communication technology. Those who are totally paralyzed, or 'locked-in' cannot use conventional augmentative technologies, all of which require some measure of muscle control. The forehead is often the last site to suffer degradation in cases of severe disability and degenerative disease. For example, In ALS(Amyotrophic Lateral Sclerosis) and MD(Muscular dystrophy) the ocular motorneurons and ocular muscles are usually spared permitting at least gross eye movements, but not precise eye pointing. We use brain and body forehead bio-potentials in a novel way to generate multiple signals for computer control inputs. A bio-amplifier within this device separates the forehead signal into three frequency channels. The lowest channel is responsive to bio-potentials resulting from an eye motion, and second channel is the band pass derived between 0.5 and 45Hz, falling within the accepted Electroencephalographic(EEG) range. A digital processing station subdivides this region into eleven components frequency bands using FFT algorithm. The third channel is defined as an Electromyographic(EMG) signal. It responds to contractions of facial muscles and is well suited to discrete on/off switch closures, keyboard commands. These signals are transmitted to a PC that analyzes in a time series and a frequency region and discriminates user's intentions. That software graphically displays user's bio-potential signals in the real time, therefore user can see their own bio-potentials and control their physiological signals little by little after some training sessions. As a result, we confirmed the performance and availability of the developed system with experimental user's bio-potentials.

• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.6
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• pp.271-280
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• 2017

In this paper, we propose a new safety system composed of wearable devices, driver's seat belt, and integrating controllers. The wearable device and driver's seat belt capture driver's biological information, while the integrating controller analyzes captured signal to alarm the driver or directly control the car appropriately according to the status of the driver. Previous studies regarding driver's safety from driver's seat, steering wheel, or facial camera to capture driver's physiological signal and facial information had difficulties in gathering accurate and continuous signals because the sensors required the upright posture of the driver. Utilizing wearable sensors, however, our proposed system can obtain continuous and highly accurate signals compared to the previous researches. Our advanced wearable apparatus features a sensor that measures the heart rate, skin conductivity, and skin temperature and applies filters to eliminate the noise generated by the automobile. Moreover, the acceleration sensor and the gyro sensor in our wearable device enable the reduction of the measurement errors. Based on the collected bio-signals, the criteria for identifying the driver's condition were presented. The accredited certification body has verified that the devices has the accuracy of the level of medical care. The laboratory test and the real automobile test demonstrate that our proposed system is good for the measurement of the driver's condition.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.821-827
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• 2018

Affective computing has gained increasing interest in the recent years with the development of potential applications in Human computer interaction (HCI) and healthcare. Although momentous research has been done on human emotion recognition, however, in comparison to speech and facial expression less attention has been paid to physiological signals. In this paper, Electroencephalogram (EEG) signals from different brain regions were investigated using modified wavelet energy features. For minimization of redundancy and maximization of relevancy among features, mRMR algorithm was deployed significantly. EEG recordings of a publically available "DEAP" database have been used to classify four classes of emotions with Multi class Support Vector Machine. The proposed approach shows significant performance compared to existing algorithms.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.161-170
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• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.37 no.2
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• pp.127-132
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• 2011

Juvenile ossifying fibroma is an expansive intraosseous lesion of the bones. In most patients, the tumors are located in the facial bones. The main characteristics of juvenile ossifying fibroma are the early age of onset, localization of the tumor, radiological pattern and a tendency for recurrence. This article describes a case of expanded juvenile ossifying fibroma in the right maxilla in a 12-year old boy. The lesion was removed totally by surgery under general anesthesia. The patient showed no radiological signals of recurrence approximately two years after surgery.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.72-78
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• 2022

The aim of this research is to improve the effectiveness of digital media advertising because current advertisements -in digital signage - indiscriminately appeals to the general public rather than to a specific target. In order to deliver efficient and customized advertisement information, an IoT human body detection sensor mounted on digital signage detected human faces and then classified them firstly by gender. The digital signage here is a smart digital signage that can analyze facial signals, discriminate them based on patterns, and apply the extracted data by displaying the corresponding information to the user. In addition, by identifying the customer's location approaching the smart digital signage and displaying the optimized content information for the customer's location through an algorithm, the digital signage can dramatize the advertisement Thus, this is a study meant forimproving information efficiency while reducing noise and driving power waste generated from unnecessary digital information reproduction.

• Korean Journal of Psychosomatic Medicine
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• v.32 no.1
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• pp.10-23
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• 2024

This study examines the changes in attractiveness and social perception of mask wearers during the COVID-19 pandemic. Before COVID-19, masks were seen as a sign of infection, decreasing the wearer's attractiveness. However, with the widespread normalization of mask-wearing during the pandemic, the perception mechanisms have become more complex. The attractiveness and social perception of mask wearers now vary based on factors such as the wearer's baseline attractiveness, race, and attitudes toward masks. Consequently, research findings on perception changes due to mask-wearing have been inconsistent. This inconsistency is due to the lack of standardized experimental methods and the failure to account for individual differences among participants, as well as insufficient theoretical background in the studies. From a psychiatric perspective, it is essential to formulate and test new hypotheses centered around the psychological mechanisms related to the human behavioral immune system when studying attractiveness perception during a pandemic. Notably, attention should be given to how differences in the activation of individuals' behavioral immune systems influence perceptions of mask wearers. Understanding these dynamics can provide crucial insights into how social perceptions and aversions impact mental health, thereby shedding light on various psychiatric issues that arise during infectious disease outbreaks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3319-3325
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• 2013

In this paper, hand acupuncture used as a way of life medicine in everyday life, the influence of human organ will be investigated by applying IT techniques. For this, hand acupuncture is based on priority of the most important organ in the human body to target the cardiac associated with cardiac reflex point A16 acupuncture point before and after for 5 min to stimulation of facial images were collected and applied to the Lab color system associated with the cardiac, color value of cheonjung and lips region were measured for comparison and analysis. Finally, by measuring the change in bio-image signals A16 acupuncture point stimulation effects on cardiac function were performed to investigate the effectiveness of acupuncture. Also, statistical significance tests from the experimental results were performed whether the experimental results is valid or not.

• Journal of Korean Neurosurgical Society
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• v.50 no.1
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• pp.51-53
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• 2011

We present a rare case of medulloblastoma which presented with unilateral sudden sensorineural hearing loss as an initial symptom. A 19-year-old man was admitted to our hospital with a chief complaint of dizziness and facial numbness on the right side. His illness had begun two years previously with sudden hearing loss on the right side, for which he had been treated as an idiopathic sudden hearing loss. Magnetic resonance imaging demonstrated abnormal signals located mainly in the right middle cerebellar peduncle. We performed partial resection of the tumor by suboccipital craniotomy. The histopathological diagnosis was medulloblastoma. Intrinsic brain tumor is an extremely rare cause of sudden sensorineural hearing loss and is therefore easily overlooked as was in the present case. The present case highlights not only the need to evaluate patients with sudden sensorineural hearing loss by magnetic resonance imaging but also the importance of paying attention to intrinsic lesions involving the brainstem. Although this condition like the presented case might be rare, intrinsic brain tumor should be considered as a potential cause of sudden sensorineural hearing loss, as it may be easily missed leading to a delay in appropriate treatment.