回顾与展望:Actigraph加速度计研究热点与发展趋势  

Review and Outlook:Actigraph Accelerometer Research Hotspots and Trends

作　　者：李中浩 邱芬 LI Zhong-hao;QIU Fen(Sports Department of Wuhan University of Technology,Wuhan 430079,China)

机构地区：[1]武汉理工大学体育部,湖北武汉430079

出　　处：《福建体育科技》2021年第4期30-35,共6页Fujian Sports Science and Technology

基　　金：2019年度教育部人文社会科学研究青年基金项目(19YJC890033);2020年湖北休闲体育发展研究中心开放基金课题重点项目(2020Z003);中央高校基本科研业务费专项资金资助(2019VI012)。

摘　　要：以CNKI数据库和Web of science核心合集中收录的近20年有关Actigraph加速度计的138篇中文文献和145篇外文文献为研究对象,利用Citespace对我国和国外Actigraph加速度计研究的文献数量、发文作者与机构、关键词、研究热点进行对比与综合分析,以揭示加速度计研究的热点和未来的发展趋势。结果显示:我国Actigraph加速度计的发展呈波动式递增,发文量整体上呈上升趋势且近几年增长较快;研究机构间和研究作者间并未形成协同合作的关系网,仅高产机构和高产作者间合作较多,高产作者大多属于高产机构;加速度计的研究主题突出涉及面广,主要是围绕体力活动、能量消耗展开。结合研究热点预测,未来我国加速度计的研究可以在久坐行为与人体健康风险的关系、体力活动时空特征以及建成环境、依托机器学习算法的神经网络模型等方面发力,进行多维度、系统化、深层次研究。Using the CNKI database and the Web of science core collection of 138 Chinese and 145 foreign literature on Actigraph accelerometer over the past 20 years,we investigated the number of Chinese and foreign Actigraph accelerometer literature,authors and institutions,keywords,and research using Citespace.The hot spots are compared and analyzed to reveal the hot spots and future development trend of accelerometer research.The results show that:The development of Actigraph accelerometers in China is increasing in a wave pattern,the number of publications on the whole showed an upward trend and fast growth in recent years;the relationship between research institutions and authors did not form a collaborative network,only the cooperation between high-yield institutions and high-yield authors is more,most of the high-yield authors belong to high-yield institutions;the research of accelerometer The theme highlights a wide range of issues,mainly around physical activity,energy consumption.Combined with the research hotspot prediction,the future of Chinese accelerometer research in the relationship between sedentary behavior and human health risks,physical activity spatio-temporal characteristics and built environment,relying on machine learning algorithms,such as neural network models,multi-dimensional,systematic,in-depth research.

关 键 词：加速度计 体力活动 研究热点 发展趋势 

分 类 号：G804.49[文化科学—运动人体科学]