• Sleep Medicine and Psychophysiology
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• v.15 no.2
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• pp.71-76
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• 2008

Introduction: In this study, we compared sleep structure, EEG characteristic of pediatric obstructive sleep apnea (OSA) and normal controls which were matched in sex and age. Methods: Fifteen children (male：female=4：11) who complained snoring and were suspected to have sleep apnea and their age and sex matched normal controls (male：female=5：10) have been done nocturnal polysomnography (NPSG). Sleep parameters, sleep apnea variables and relative spectral components of EEG from NPSG have been compared between both groups. Results: Pediatric OSA group were distinguished from normal controls in terms of apnea index, respiratory disturbance index and nadir of oxyhemoglobulin desaturation. Pediatric OSA group showed increased percent of sleep stage 1, decreased rapid eye movement sleep percent and increased delta power in O1 EEG channel. However other sleep parameters and spectral powers were not different between two groups. Conclusion: In pediatric OSA group, sleep structure parameter disruption may be not prominent as the previous studies for adult OSA group because of including mild OSA data in diagnostic criteria. In addition, EEG changes might not be distinct due to low arousal index compared to adult OSA patients. We can observe general characteristics and particularity of pediatric OSA through this study.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.867-874
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• 2023

Recently, many problems are occurring in the bee ecosystem due to rapid climate change. The decline in the bee population and changes in the flowering period are having a huge impact on the harvest of bee-keepers. Since it is impossible to continuously observe the beehives in the hive with the naked eye, most people rely on knowledge based on experience about the state of the hive.Therefore, interest is focused on smart beekeeping incorporating IoT technology. In particular, with regard to swarming, which is one of the most important parts of beekeeping, we know empirically that the swarming time can be determined by the sound of the queen bee, but there is no way to systematically analyze this with data.You may think that it can be done by simply recording the sound of the queen bee and analyzing it, but it does not solve various problems such as various noise issues around the hive and the inability to continuously record.In this study, we developed a system that records queen bee sounds in a real-time cloud system and analyzes sound patterns.After receiving real-time analog sound from the hive through multiple channels and converting it to digital, a sound pattern that was continuously output in the queen bee sound frequency band was discovered. By accessing the cloud system, you can monitor sounds around the hive, temperature/humidity inside the hive, weight, and internal movement data.The system developed in this study made it possible to analyze the sound patterns of the queen bee and learn about the situation inside the hive. Through this, it will be possible to predict the swarming period of bees or provide information to control the swarming period.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.9-21
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• 2024

Objective : The purpose of this study was to confirm the characteristics and quality of a single-subject research that conducted interventions to improve activities of daily living (ADL) in stroke patients. Methods : 'Stroke,' 'activities of daily living,' and 'single-subject studies' were searched as keywords among papers published in the last 15 years between 2009 and 2023 among Research Information Sharing Service, DBpia, and e-articles. A total of nine papers were examined for the characteristics and quality before analysis. Results : The independent variables applied to improve ADL included constraint-induced therapy, mental practice for performing functional activities, virtual reality-based task training, subjective postural vertical training without visual feedback, bilateral upper limb movement, core stability training program, traditional occupational therapy and neurocognitive rehabilitation, smooth pursuit eye movement, neck muscle vibration, and occupation-based community rehabilitation. Assessment of Motor and Process Skills was the most common evaluation tool for measuring dependent variables, with four articles, and Modified Barthel Index and Canadian Occupational Performance Measure were two articles each. As a result of confirming the qualitative level of the analyzed papers, out of a total of nine studies, seven studies were at a high level, two at a moderate level, and none were at a low level. Conclusion : Various types of rehabilitation treatments have been actively applied as intervention methods to improve the daily life activities of stroke patients; the quality level of single-subject studies applying ADL interventions was reliable.

• Korean Journal of Clinical Laboratory Science
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• v.44 no.2
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• pp.52-58
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• 2012

Patients with obstructive sleep apnea (OSA) often have more aggravated symptoms in the supine position. We tried to investigate the clinical characteristics and the predictive factors for positional OSA. Polysomnographic data were reviewed for OSA patients (apnea hypopnea index, $AHI{\geq}5$) from April, 2008 to April, 2011 at the Asan Medical Center. Clinical data, comorbid medical condition data and questionnaires (SF-36, MFI-20, ESS, BDI, STAI) were assessed. All patients were classified into two groups: positional patients (PP) group and non-positional patients (NPP) group. PP was defined as a patient who had the AHI in the supine position was at least twice as high as that in the lateral position. The body position of patients was confirmed by sleep position sensor and video monitor. All patients had at least 30 minutes of positional and 30 minutes of non-positional sleep. We compared clinical, medical, polysomnographic data, and questionnaire results between two (PP and NPP) groups and investigated predictive factors for the PP group using binary logistic regression analysis. In total, 371 patients were investigated. 265 (71.4%) was categorized as PP group and 106 (28.5%) as NPP group. The mean age ($mean{\pm}SD$) was higher in the PP group ($52.4{\pm}9.8$) than in the NPP group ($49.5{\pm}11.9$) (p<0.05). Comparison of sleep parameters between the PP and the NPP group showed that the PP group had significantly lower BMI (PP: $26.1{\pm}3.2kg/m^2$; NPP: $27.8{\pm}4.3kg/m^2$, p<0.001), neck circumference (PP: $39.7{\pm}2.8cm$; NPP: $41.5{\pm}3.7cm$, p<0.001) and hypertension rate (PP: n=89/265 (33.5%); NPP: n=48/106 (45.2%), p=0.0240). In the PP group, the percentage of deep sleep (PP: $8.7{\pm}8.1%$; NPP: $5.6{\pm}7.0%$, P=0.001) and rapid eye movement (REM) (PP: $17.5{\pm}6.1%$; NPP: $14.0{\pm}6.9%$, p<0.001) were significantly higher whereas the percentage of light sleep (stage N1) was significantly lower than the NPP group (PP: $30.4{\pm}12.3$; NPP: $44.5{\pm}20.8%$, p<0.001). During the sleep, the AHI in the supine position (PP: $48.6{\pm}19.5$; NPP: $60.5{\pm}22.6$, p<0.001) and in the non-supine position (PP: $9.4{\pm}8.9$; NPP: $48.4{\pm}24.8$, p=<0.001) were significantly lower and the minimal arterial oxygen saturation in non-REM sleep was significantly higher in the PP group (PP: $80.3{\pm}7.6$; NPP: $75.1{\pm}9.9$, p=<0.001). There were no significant differences in all questionnaires including quality of life. The results of the binary logistic regression analysis showed that age, the amount of REM sleep(%) and AHI were significant predictive factors for positional OSA. The significant predictive factors for positional OSA were older age, higher percentage of REM and lower AHI. The questionnaire results were not significantly different between the two groups.

• Trans-
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• v.15
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• pp.25-56
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• 2023

VR is a dynamic image simulation technology with very high information density. Among them, spatial depth, temporality, and realism bring an unprecedented sense of immersion to the experience. However, due to its high information density, the information contained in it is very easy to be manipulated, creating an illusion of objectivity. Users need guidance to help them interpret the high density of dynamic image information. Just like setting up navigation interfaces and interactivity in games, interactivity in virtual reality is a way to interpret virtual content. At present, domestic research on VR content is mainly focused on technology exploration and visual aesthetic experience. However, there is still a lack of research on interactive storytelling design, which is an important part of VR content creation. In order to explore a better interactive storytelling model in virtual reality content, this paper analyzes the interactive storytelling features of the VR animated version of <Wolves in the walls> through the methods of literature review and case study. We find that the following rules can be followed when creating VR content: 1. the VR environment should fully utilize the advantages of free movement for users, and users should not be viewed as mere observers. The user's sense of presence should be fully considered when designing interaction modules. Break down the "fourth wall" to encourage audience interaction in the virtual reality environment, and make the hot media of VR "cool". 2.Provide developer-driven narrative in the early stages of the work so that users are not confused about the ambiguous world situation when they first enter a virtual environment with a high degree of freedom. 1.Unlike some games that guide users through text, you can guide them through a more natural interactive approach that adds natural dialog between the user and story characters (NPC). Also, since gaze guidance is an important part of story progression, you should set up spatial scene user gaze guidance elements within it. For example, you can provide eye-following cues, motion cues, language cues, and more. By analyzing the interactive storytelling features and innovations of the VR animation <Wolves in the walls>, I hope to summarize the main elements of interactive storytelling from its content. Based on this, I hope to explore how to better showcase interactive storytelling in virtual reality content and provide thoughts on future VR content creation.