earticle

영어

The purpose of this study was to identify the core research trends and topics within the field of body contouring devices by analyzing the frequency and interrelationships among keywords extracted from domestic academic journals and theses. A total of 53 documents were collected from reputable academic content platforms, such as DBpia and RISS, and text mining techniques were employed to extract 1,851 words, which were subsequently refined using preprocessing and duplicate removal, resulting in 40 core keywords. Semantic network analysis was then applied to compute centrality measures,including degree, betweenness, closeness, and eigenvector centrality, revealing that keywords such as ‘abdominal obesity’, ‘radiofrequency’, and ‘reduction effect’ play pivotal roles in this research domain. Moreover, CONCOR analysis grouped the keywords into four distinct clusters corresponding to body composition and obesity, anthropometric measurements, therapeutic interventions, and research outcomes, indicating that studies in this field address not only aesthetic improvement but also clinical efficacy. These findings provide valuable academic and practical insights, suggesting future research directions that integrate objective health indicators with innovative device applications to enhance the overall impact of body shape management solutions.

중국어

本研究旨在通过分析国内学术期刊和学位论文,揭示体型管理设备领域的研究趋势与 核心主题.为此,本研究从DBpia和RISS数据库中收集了53篇文献,运用文本挖掘技术提取 了1,851个词汇.经过预处理和去重处理后,最终提炼出40个核心关键词,并进行了语义网络 分析.通过连接中心性,中介中心性,邻近中心性,威势中心性等指标分析发现,腹部肥 胖,高频次,减重效果等指标显示出较高的中心性特征,被确定为主要研究主题.此外,通 过CONCOR聚类分析,研究将关键词划分为四个类别 : 体型与肥胖,人体测量指标,治疗与 手术干预,研究结果与临床因素,这表明体型管理设备研究已突破美容改善范畴,开始深入 探索临床效果.本研究通过整合未来健康指标与创新设备技术,将为强化体型管理的有效性 及科学依据提供基础性研究数据.