• 대한통합의학회지
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• 제7권3호
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• pp.11-19
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• 2019

Purpose : The purpose of this study is to examine the effect of instrumental-activity of daily living program on a patient with subacute stroke in the view of self-efficiency, motivation for rehabilitation, social support. Methods : Eight stroke patients who attended instrumental-activity of daily living program at P hospital in Busan Metropolitan City from march 2018 to January 2019 were recruited. Instrumental-activity of daily living program was offered to 8 stroke patients 1 session (at least 1 hours) a day, 5 times a week, for 4~5 weeks. The instrumental-activity of daily living program was based on occupational therapy practice framework (OTPF) and international classification of functioning, disability and health (ICF). We evaluated self-efficacy, rehabilitation motivation, social support before and after intervention. Self-efficacy was evaluated using the general self-efficacy scale. The collected data was processed using SPSS 20.0 and were analyzed using descriptive statistics, Wilcoxon signed rank test, Pearson's correlation coefficient. Results : There were statistically significant differences in self-efficiency, rehabilitation motivation, social support between before and after instrumental-activity of daily living program (p<.05). Examining the correlation between the self-efficiency, rehabilitation motivation and social support of the stroke patient, there was a correlation between the self-efficiency and social support (p<.05). Conclusion : This study showed that the instrumental-activity of daily living program have positive effects on self-efficacy, rehabilitation motivation, social support. When considering the instrumental-activity of daily living program with improved self-efficacy, rehabilitation motivation, social support of the participants, we suggest that further studies will be needed to examine more extensive instrumental-activity of daily living and rehabilitation to the society with a larger sample size.

• 가정∙방문간호학회지
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• 제3권
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• pp.75-85
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• 1996

Nursing Intervention Classification(NIC) includes the 433 intervention lists to standardize the nursing language. Efforts to standardize and classify nursing care are important because they make explicit what has previously been implicit, assumed and unknown. NIC is a standardized language of both nurse-initiated and physician-initiated nursing treatments. Each of the 433 interventions has a label, definition and set of activities that a nurse does to carry it out. It defines the interventions performed by all nurses no matter what their setting or specialty. Principles of label, definition and activity construction were established so there is consistency across the classification. NIC was developed for following reasons; 1. Standandization of the nomen clature of nursing treatments. 2. Expansion of nursing knowledge about the links between diagnoses, treatments and outcomes. 3. Devlopment of nursing and health care information systems. 4. Teaching decision making to nursing students. 5. Determination of the costs of service provided by nurses. 6. Planning for resources needed in nursing practice settings. 7. Language to communicate the unigue function of nursing. 8. Articulation with the classification systems of other health care providers. The process of NIC development ; 1. Develop implement and evaluate an expert review process to evaluate feedback on specific interventions in NIC and to refine the interventions and classification as feedback indicates. 2. Define and validate indirect care interventions. 3. Refine, validate and publish the taxonomic grouping for the interventions. 4. Translate the classification into a coding system that can be used for computerization for articulation with other classifications and for reimbursement. 5. Construct an electronic version of NIC to help agencies in corporate the classifiaction into nursing information systems. 6. Implement and evaluate the use of the classification in a nursing information system in five different agencies. 7. Establish mechanisms to build nursing knowledge through the analysis of electronically retrievable clinical data. 8. Publish a second edition of the nursing interventions classification with taxonomic groupings and results of field testing. It is suggested that the following researches are needed to develp NIC in Korea. 1. To idenilfy the intervention lists in Korea. 2. Nursing resources to perform the nursing interventions. 3. Comparative study between Korea and U.S.A. on NIC. 4. Linkage among nursing diagnosis, nursing interventions and nursing outcomes. 5. Linkage between NIC and other health care information systems. 6. determine nursing costs on NIC.

• 대한감각통합치료학회지
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• 제10권1호
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• pp.11-20
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• 2012

목적 : 본 연구는 뇌성마비아동을 대상으로 일상생활활동수행 능력을 평가하기 위한 측정 도구인 수정바델지수(Modified Barthel Index: MBI)와 사물조작 기능 분류체계(Manual Ability Classification System: MACS)와 대동작 기능 분류체계(Gross Motor Function Classification System: GMFCS)와의 상관관계를 통하여 장애판정 지표인 MBI를 유용하게 활용할 수 있는 정보를 제공하고자 한다. 연구 방법 : 연구대상자는 전문재활병원에서 작업치료와 물리치료를 받고 있는 뇌성마비 아동 82명을 대상으로 MBI, MACS, GMFCS를 사용하여 평가하였으며, 일상생활활동 수행능력과 사물조작기능, 그리고 대동작기능과의 관계를 알아보기 위하여 상관분석을 사용하여 분석하였다. 결과 : 본 연구 결과는 MBI와 MACS간의 상관계수가 -.765(p<0.001)로 높은 음의 상관을 나타냈고, MBI와 GMFCS 는 상관계수가 -.851(p<0.001)로 높은 음의 상관관계가 있었다. MACS와 GMFCS의 상관계수 또한 .615(p<0.001)로 높은 상관관계를 보였다. 결론 : 뇌성마비 유형에 따른 MBI의 각 항목과 MACS, GMFCS와의 상관관계에 대한 결과는 모든 뇌성마비 유형과 관련하여 MBI의 항목과 MACS와 GMFCS은 유의미한 상관관계를 나타냈다. 뇌병변 장애등급 판정 기준으로 사용하는 MBI와 MACS, GMFCS와의 높은 상관관계는 장애판정 지표인 MBI를 뇌성마비 장애 아동들을 대상으로 유용하게 활용할 수 있을 것이다.

• 대한화학회지
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• 제59권4호
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• pp.320-335
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• 2015

이 연구의 목적은 생활에서 접할 수 있는 다양한 물질들을 분류하는 활동을 통하여 초등교사의 물질의 세 가지 상태에 대한 개념을 조사하고, 분류활동 결과에 대한 토론을 통해 개념변화가 이루어진 후 새롭게 분류한 결과가 합의에 도달하는지 알아보는데 있다. 이를 위하여 교육대학원에서 초등과학교육을 전공하는 초등 교사 25명과 I지역 소재의 초등 교사 10명을 선정하였다. 이들에게 분류 활동을 포함한 검사지의 투입과 분류 활동의 관찰, 그리고 면담을 통하여 자료를 수집하였으며, 수집된 자료는 양적 분석과 질적 분석을 병행하여 분석하였다. 연구 결과 초등교사는 주로 거시적 관점으로 물질의 세 가지 상태의 개념을 이해하고 있었고, 순물질이 아닌 혼합물일 경우 물질의 상태 분류에 어려움을 겪었다. 분류 결과에 대한 토론 후 교사들의 개념은 변화하였으며 새롭게 만들어진 개념으로 분류활동을 하였을 때 그 결과 역시 합의점에 도달하지 못하였다. 이러한 연구의 결과는 과학의 개념이 모든 사람에게 동일하게 합의되는 과정이 쉽지 않음을 보여준다. 따라서 분류라는 과학탐구과정이 갖는 본성의 이해를 도모하고 다양한 물질을 상태 분류할 수 있는 기능을 향상시킬 수 있도록 하는 교사교육이 요구된다. 더불어 혼합물의 분류에 대한 논의도 필요하다.

• ETRI Journal
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• 제42권1호
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• pp.78-89
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• 2020

Human activity recognition (HAR) has become effective as a computer vision tool for video surveillance systems. In this paper, a novel biometric system that can detect human activities in 3D space is proposed. In order to implement HAR, joint angles obtained using an RGB-depth sensor are used as features. Because HAR is operated in the time domain, angle information is stored using the sliding kernel method. Haar-wavelet transform (HWT) is applied to preserve the information of the features before reducing the data dimension. Dimension reduction using an averaging algorithm is also applied to decrease the computational cost, which provides faster performance while maintaining high accuracy. Before the classification, a proposed thresholding method with inverse HWT is conducted to extract the final feature set. Finally, the K-nearest neighbor (k-NN) algorithm is used to recognize the activity with respect to the given data. The method compares favorably with the results using other machine learning algorithms.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1857-1862
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• 2016

Human activity recognition using depth information is an emerging and challenging technology in computer vision due to its considerable attention by many practical applications such as smart home/office system, personal health care and 3D video games. This paper presents a novel framework of 3D human body detection, tracking and recognition from depth video sequences using spatiotemporal features and modified HMM. To detect human silhouette, raw depth data is examined to extract human silhouette by considering spatial continuity and constraints of human motion information. While, frame differentiation is used to track human movements. Features extraction mechanism consists of spatial depth shape features and temporal joints features are used to improve classification performance. Both of these features are fused together to recognize different activities using the modified hidden Markov model (M-HMM). The proposed approach is evaluated on two challenging depth video datasets. Moreover, our system has significant abilities to handle subject's body parts rotation and body parts missing which provide major contributions in human activity recognition.

• The Journal of Korean Physical Therapy
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• 제24권6호
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• pp.398-404
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• 2012

Purpose: This is designed to study the effect of weight-support walking training through motor learning on motor functions of children with cerebral palsy, in particular their activity of daily living and balance. Methods: Thirteen children with spastic cerebral palsy, at gross motor function classification system (GMFCS) levels III~IV, underwent treadmill walking training. It used principles of weight support, 4 times a week for 7 weeks, 10 minutes at a time, before and after neurodevelopmental physical therapy. Everyday functions were measured using Functional Independence Measure for Children (Wee-FIM). The ability to keep their balance was measured using electronic measuring equipment from good balance system and the assessment was made before and after the experiment. Results: There were significant differences (p<0.05) between pre and post experiment levels of functional independence in everyday life, in self-care activities, mobility, locomotion and social cognition. With regard to changes in standing balance, there were significant differences before and after the experiment (p<0.05) in GMFCS level III. There was a reduction in the agitation velocity in the x- and y-axes which measures the left-to-right shaking; in GMFCS level IV, velocity moment was reduced. Conclusion: Walking training using a treadmill can help improve the everyday activity and balance in children with spastic cerebral palsy. It can also be served as a useful purpose as a method of intervention in pediatric care.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5530-5546
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• 2016

Automatic analysis and understanding of human activities is a challenging task in computer vision, especially for the surveillance scenarios which typically contains crowds, complex motions and occlusions. To address these issues, a Bag-of-words representation of videos is developed by leveraging information including crowd positions, motion directions and velocities. We infer the crowd activity in a motion field using Category Constrained Correlated Topic Model (CC-CTM) with latent topics. We represent each video by a mixture of learned motion patterns, and predict the associated activity by training a SVM classifier. The experiment dataset we constructed are from Crowd_PETS09 bench dataset and UCF_Crowds dataset, including 2000 documents. Experimental results demonstrate that accuracy reaches 90%, and the proposed approach outperforms the state-of-the-arts by a large margin.

• PNF and Movement
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• 제16권3호
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• pp.495-503
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• 2018

Purpose: This study analyzes the predictive power of upper extremity activity and the activities of daily living in patients with stroke using an easy-to-use evaluation tool. Methods: The Fugl-Meyer assessment (FMA) of the upper extremity and action research arm test (ARAT) are performed, and the Korean modified Barthel index (K-MBI) is measured. The predictive power of the upper extremity activity level and the daily activity level are analyzed using regression analysis. The statistical significance level is 0.05. Results: The coefficient of determination, R2, for predicting the ARAT using FMA was high at 0.88, but the regression equation for predicting the K-MBI using the FMA and ARAT did not show a statistically significant difference. Conclusion: The assessment of the upper extremity should be performed at the activity level, as well as the impairment level. The assessment for predicting the activities of daily living should be carried out for each level of the international classification of functioning (ICF), disability, and health, which can be linked to daily life, in addition to the assessment of the upper arm. Future research should conduct more diverse analyses using the ICF assessment tools at various levels.

• Journal of Nutrition and Health
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• 제36권7호
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• pp.769-776
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• 2003

This study has analyzed the association of physical activity and television watching time with obesity in 30-50 aged women from middle income town in Busan city area. Data were obtained using a questionnaire, including information about physical activity, TV watching time and health habit; social data regarding educational level and monthly income; family history of chronic condition. Height and weight were measured. Outcome variable was obesity, defined as a body mass index 25 kg/m$^2$ or greater. Odds ratios (OR) for obesity were estimated by multivariate logistic regression, and interpreted as a relative risk of obesity. The prevalence of obesity was 11.8%. The mean BMI of obese women was 26.9 kg/m$^2$. The OR of obesity was higher in subject of 40s than 30s. Subjects who had higher educational level presented lower OR than those of elementary or middle school education. Family income was not associated with obesity. Women having a family history of chronic condition had higher risk of obesity than those who did not have it. The OR was lower in active people at work (OR = 0.51; 95% CI = 0.26 - 0.98) than in inactive ones, and the ORs associated with regular exercise or activity at leisure time were not statistically different. However, subjects watching TV $\geq$ 3.5 hr/day showed higher OR (OR = 2.34; 95% CI = 1.16 - 4.74), compared with those watching TV $\geq$ 1.5 hr/day. Association of the joint classification of physical activity variables with obesity was estimated. The highest relative risk of 5.99 was in women in physically inactive at work and high category of TV watching ($\geq$ 3.5 hr/day). Even in women in active at work, the watching TV $\geq$ 3.5 hr/day made them have the high OR (OR = 2.44; 95% CI = 1.03 - 5.77). And at each time level of TV watching, the increasing activity level at work was associated with lower OR for obesity. These findings suggest that both TV watching time and physical activity at work were related to obesity in adult female, each with independent effects on obesity. TV watching time seems to be a significant factor that could partly evaluate the energy expenditure.