• 한국화재소방학회논문지
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• 제33권6호
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• pp.132-141
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• 2019

본 연구는 국립산림치유원에서 실시한 4박 5일형 산림치유프로그램이 소방공무원의 외상 후 스트레스 및 기분상태 변화에 미치는 효과를 알아보고자 수행되었다. 소방공무원 293명을 대상으로 설문조사를 실시하였으며, SPSS 24.0을 활용하여 빈도분석, 대응 t-검정 및 공분산분석을 실시하였다. 산림치유프로그램 참여 전과 후의 외상 후 스트레스, 기분상태의 차이 및 인구학적 특성에 따른 차이를 분석하였다. 외상 후 스트레스 결과, 참여 전 평균 11.38 ± 12.58점에서 참여 후 6.91 ± 10.50점으로 감소하여 통계적으로 유의한 영향을 미치는 것으로 나타났다. 기분상태검사 결과, 긍정적 요인은 증가하였고, 부정적 요인은 감소하였다. 전체 기분상태 또한 프로그램 참여 전 8.58 ± 18.47점에서 참여 후 -0.63 ± 15.83점으로 통계적으로 유의한 영향을 미치는 것으로 나타났다. 수면시간에 따른 스트레스 저감 효과 차이 분석 결과, 외상 후 스트레스는 수면시간이 6~8시간일 때 효과가 높게 나타났다. 본 연구결과는 소방공무원의 외상 후 스트레스 관리와 해소를 위한 방법이 될 수 있는 근거자료로 활용되기를 기대한다.

• 인지과학
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• 제12권1_2호
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• pp.77-89
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• 2001

얼굴 특징점의 지각적 위계구조를 반영한 표정인식 신경망 모형을 설계하였다. 입력자료는 MPEG-4 SNHC(Synthetic/Natural Hybrid Coding)의 얼굴 정의 파라미터(FDP) 중 39개 특징점 각각에 대해 150장의 표정연기 사진을 5개의 크기와 8개의 바위를 갖는 Gabor 필터로분석한 값이었다. 표정영상에 대한 감정상태 평정 값과 39개 특징점의 필터 반응 값을 중가 회귀분석한 결과, 감정상태의 쾌-불쾌 차원은 주로 입과 눈썹 주변의 특징점과 밀접한 과련이 있었고, 각성-수면차원은 주로 눈 주변의 특징점과 밀접한 관련이 있었다. 필터의 크기는 주로 저역 공간 주파수 필터와 감정상태가 관련이 있었고, 필터의 방위는 주로 비스듬한 사선방위와 감정상태가 관련이 있었다. 이를 기초로 표정인식 신경망을 최적화한 결과 원래 1560개(39x5x8) 입력요소를 400개(25x2x8)입력요소로 줄일 수 있었다. 표정인식 신경망의 최적화 결과를 사람의 감정상태 평정과 비교하여 볼 때, 쾌-불쾌 차원에서는 0.886의 상관관계가 있었고, 각성-수면 차원에서는 0.631의 상관관계가 있었다. 표정인식 신경망의 최적화 모형을 기쁨, 슬픔, 놀람, 공포, 분노, 혐오 등의 6가지 기본 정서 범주에 대응한 결과 74%의 인식률을 얻었다. 이러한 결과는 사람의 표정인식 원리를 이용하면 작은 양의 정보로도 최적화된 표정인식 시스템을 구현할수 있다는 점을 시시한다.

• 대한간호학회지
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• 제43권5호
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• pp.579-586
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• 2013

Purpose: This article provides an update and overview of a nursing research program focused on understanding the pathophysiology and management of irritable bowel syndrome (IBS). Methods: This review includes English language papers from the United States, Europe, and Asia (e.g., South Korea) from 1999 to 2013. We addressed IBS as a health problem, emerging etiologies, diagnostic and treatment approaches and the importance of a biopsychosocial model. Results: IBS is a chronic, functional gastrointestinal disorder characterized by recurrent episodes of abdominal pain and alterations in bowel habit (diarrhea, constipation, mixed). It is a condition for which adults, particularly women ages 20-45, seek health care services in both the United States and South Korea. Clinically, nurses play key roles in symptom prevention and management including designing and implementing approaches to enhance the patients' self-management strategies. Multiple mechanisms are believed to participate in the development and maintenance of IBS symptoms including autonomic nervous system dysregulation, intestinal inflammation, intestinal dysbiosis, dietary intolerances, alterations in emotion regulation, heightened visceral pain sensitivity, hypothalamic-pituitary-adrenal dysregulation, and dysmotility. Because IBS tends to occur in families, genetic factors may also contribute to the pathophysiology. Patients with IBS often report a number of co-morbid disorders and/or symptoms including poor sleep. Conclusion: The key to planning effective management strategies is to understand the heterogeneity of this disorder. Interventions for IBS include non-pharmacological strategies such as cognitive behavior therapy, relaxation strategies, and exclusion diets.

• ETRI Journal
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• 제44권3호
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• pp.426-437
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• 2022

To understand the multilateral characteristics of human behavior and physiological markers related to physical, emotional, and environmental states, extensive lifelog data collection in a real-world environment is essential. Here, we propose a data collection method using multimodal mobile sensing and present a long-term dataset from 22 subjects and 616 days of experimental sessions. The dataset contains over 10 000 hours of data, including physiological, data such as photoplethysmography, electrodermal activity, and skin temperature in addition to the multivariate behavioral data. Furthermore, it consists of 10 372 user labels with emotional states and 590 days of sleep quality data. To demonstrate feasibility, human activity recognition was applied on the sensor data using a convolutional neural network-based deep learning model with 92.78% recognition accuracy. From the activity recognition result, we extracted the daily behavior pattern and discovered five representative models by applying spectral clustering. This demonstrates that the dataset contributed toward understanding human behavior using multimodal data accumulated throughout daily lives under natural conditions.

• 한국산학기술학회논문지
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• 제10권4호
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• pp.722-727
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• 2009

인체동작상태를 구분하는 기술은 인체활동에 따라 변하는 생체신호의 측정 분석분야, 수면장애의 진단 치료 효과의 스크리닝 검사분야, 만성질환 환자의 운동 상태 진단 운동처방분야에 필요한 기술이다. Armband에 내장된 아날로그 디바이스사의 ADXL202AE을 이용하여 수직방향신호의 평균치(LAA), 수평방향신호의 평균치(TAA), 수직방향 신호의 가속도 변화량의 절대치의 평균치(L-MAD), 수평방향신호의 가속도 변화량의 절대치의 평균치(T-MAD)의 획득과 데이터 처리하여, 인체동작상태(눕기, 앉기, 걷기, 뛰기)를 구분하는 퍼지규칙 기반의 퍼지추론시스템을 구현하였다. 입력데이터(LAA, TAA, L-MAD, T-MAD)와 출력데이터(Lying, Sitting, Walking, Running)의 각 구역에서의 소속정도(menbership degree)와 퍼지규칙은 실험을 통해 얻은 수치 데이터를 사용하여 결정하였다. 눕기$\rightarrow$걷기$\rightarrow$뛰기$\rightarrow$눕기 순으로 생성한 모의실험용 데이터를 분석한 결과, 눕기, 앉기, 걷기, 뛰기의 동작상태 구분율은 각각 100%이었다.

• 산업기술연구
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• 제25권B호
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• pp.211-220
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• 2005

The wireless sensor network consists of a number of sensor nodes which have physical constraints. Each sensor node senses surrounding environments and sends the sensed information to Sink. The inherent vulnerability in security of the sensor nodes has promoted the needs for the lightweight security protocol. In this paper, we propose a non-hierarchical sensor network and a security protocol that is suitable for monitoring the man-made objects such as bridges. Furthermore, we present the efficient way of setting the routing path by storing IDs, MAC(message authentication code) and the location information of the nodes, and taking advantage of the two node states, Sleep and Awake. This also will result in the reduced energy consuming rate.

• 생물정신의학
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• 제4권2호
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• pp.155-161
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• 1997

Serotonin has been implicated in the etiology of many disease states and may be particularly important mental illness, such as depression, anxiety, schizophrenia, sleep disorders, suicide, eating disorders, obsessive compulsive disorders, migraine and others. Many currently used treatments of these disorders are thought to act by modulating serotonergic function. The identification of many serotonin subtypes, most of which have been shown to have functional activity and differential distribution, has stimulated considerable effort into synthesizing selective ligands(drugs) to help understand their significance. This should understand the role of serotonin in mental disorders and these new drugs can be studied alone and in combination with other treatments in order to clarify the parameters of drug use for the clinical effect.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 춘계 학술대회 및 국제 감성공학 심포지움 논문집 Proceeding of the 2000 Spring Conference of KOSES and International Sensibility Ergonomics Symposium
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• pp.126-132
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• 2000

This paper presents a facial expression recognition based on Gabor wavelets that uses a fuzzy C-means(FCM) clustering algorithm and neural network. Features of facial expressions are extracted to two steps. In the first step, Gabor wavelet representation can provide edges extraction of major face components using the average value of the image's 2-D Gabor wavelet coefficient histogram. In the next step, we extract sparse features of facial expressions from the extracted edge information using FCM clustering algorithm. The result of facial expression recognition is compared with dimensional values of internal stated derived from semantic ratings of words related to emotion. The dimensional model can recognize not only six facial expressions related to Ekman's basic emotions, but also expressions of various internal states.

• 수면정신생리
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• 제6권2호
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• pp.133-142
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• 1999

Recently, with increasing the number of patients with head injury and cerebrovascular accident, there has been an increasing need for the useful assessment tools of brain dysfunction and it's localization. With the advances in the neuroscience since the mid-1970s, particularly in the areas of neuroanatomical tracing, neuroimaging, and improved behavioraltest design, it has been possible to develop a more precise understanding and localization of brain dysfunction. However, these equipments are not readily available in the private clinics and too expensive to use as a screening tool to all suspected patients with brain dysfunction. Although several screening tests such as Mini-Mental States Examination(MMSE) or Brief Cognitive Rating Scale(BCRS) are simple in use and useful for the brief assessment of brain dysfunction, these are also limited in using for localization of brain dysfunction because of their simplicity. With increasing need of the assessment tool which is able to localize the dysfunction more precisely in the clinical practice, we planned to develop the new assessment tool, the Bedside Neurocognitive Function Localization Test(BNLT) which is suitable for this purpose. The BNLT was designed to be utilized for localizing brain dysfunction effectively and readily in the clinical practice. We introduced the whole process of designing the BNLT in this manuscript.

• 여성건강간호학회지
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• 제20권1호
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• pp.14-28
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• 2014

Purpose: This study was to identify relationships of maternal psychosocial factors including mother's mood state, childcare stress, social support and sleep satisfaction with breastfeeding adaptation and immune substances in breast milk, especially secretory immunoglobulin A (sIgA) and transforming growth factor-beta 2 (TGF-${\beta}2$). Methods: Data were collected from 84 mothers who delivered full-term infants by natural childbirth. Structured questionnaires and breast milk were collected at 2~4 days and 6 weeks postpartum. Data were analyzed using descriptive statistics, Pearson's correlation, multiple linear regression, and generalized estimating equation (GEE). Results: Scores for the breastfeeding adaptation scale were significantly related with child care stress, mood state and social support. Mother's anger was positively correlated with the level of sIgA in colostrum (p<.01). Immune substances of breastmilk was significantly influenced by time for milk collection (p<.001) and the type of breastfeeding (sIgA, p<.001, TGF-${\beta}2$, p=.003). Regression analysis showed that breastfeeding adaptation could be explained 59.1% by the type of breastfeeding, childcare stress, the Profile of Mood States, emotional support and sleep quality (F=16.67, p<.001). Conclusion: The findings from this study provide important concepts of breastfeeding adaptation program and explanation of psychosocial factors by immune substances in breast milk. Future research, specially, bio-maker research on breast milk should focus on the ways to improve breastfeeding adaptation.