Identify the Type of Exercise to Prevent Falls for Healthy Elderly Life (고령자의 건강한 삶을 위한 낙상 예방 운동유형 확인)
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- Journal of Korea Entertainment Industry Association
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- v.13 no.7
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- pp.361-373
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- 2019
Falls are a threat to the physical health of the elderly as well as to their overall quality of life. The purpose of this study was to identify which type of exercise is effective for improving the balance of the elderly, and to obtain the basic data for developing the falls prevention exercise intervention program for the elderly. We compared to the differential effects between rhythmic step exercise and core muscle strengthening exercise in terms of functional balance test and self-reported balance test. Women older than 65 years and under 80 years of age were assigned to one of the step exercise group(21), core muscle exercise group(20), and control group(21), and for 8 weeks, twice per week, 20-30 minutes of exercise were treated. All participants performed one foot static balance test with open and closed eyes. And they responded to self-reported balance test, such as Fall Efficacy Scale(FES) and Activities-specific Balance Confidence(ABC) Scale. The results of statistical analysis are summarized as follows. First, rhythmic stepping exercise was more effective in improving functional balance than core muscle strengthening exercise. In particular, the effect of step exercise was obvious in the one-foot static balance test with open eyes. Second, the self-reported balance test showed better step exercise than core muscle exercise. Specifically, rhythmic step exercise was more effective in enhancing fall efficacy than core muscle exercise. In conclusion, the rhythmic step exercise was more effective in improving the balance ability of the elderly than the core muscle exercise. The rhythmic step exercise is more related to the lower extremity muscles, and especially since the rhythmic step exercise is performed in various ground changes, it seems to have a high similarity to the fall occurrence situation. For future research, we recommended the development of task-oriented ankle proprioceptive exercise intervention program and exercise equipment based on the specific motion situation in which the fall accident occurs in the elderly.
From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (