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上肢物理康复使用严肃游戏和运动捕捉系统:系统评价。

Upper Limb Physical Rehabilitation Using Serious Videogames and Motion Capture Systems: A Systematic Review.

机构信息

Software Research Group, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia.

School of Computer Science, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia.

出版信息

Sensors (Basel). 2020 Oct 22;20(21):5989. doi: 10.3390/s20215989.

Abstract

The use of videogames and motion capture systems in rehabilitation contributes to the recovery of the patient. This systematic review aimed to explore the works related to these technologies. The PRISMA method (Preferred Reporting Items for Systematic reviews and Meta-Analyses) was used to search the databases Scopus, PubMed, IEEE Xplore, and Web of Science, taking into consideration four aspects: physical rehabilitation, the use of videogames, motion capture technologies, and upper limb rehabilitation. The literature selection was limited to open access works published between 2015 and 2020, obtaining 19 articles that met the inclusion criteria. The works reported the use of inertial measurement units (37%), a Kinect sensor (48%), and other technologies (15%). It was identified that 26% used commercial products, while 74% were developed independently. Another finding was that 47% of the works focus on post-stroke motor recovery. Finally, diverse studies sought to support physical rehabilitation using motion capture systems incorporating inertial units, which offer precision and accessibility at a low cost. There is a clear need to continue generating proposals that confront the challenges of rehabilitation with technologies which offer precision and healthcare coverage, and which, additionally, integrate elements that foster the patient's motivation and participation.

摘要

电子游戏和运动捕捉系统在康复中的应用有助于患者的康复。本系统评价旨在探索与这些技术相关的研究。使用 PRISMA 方法(系统评价和荟萃分析的首选报告项目)检索 Scopus、PubMed、IEEE Xplore 和 Web of Science 数据库,考虑到四个方面:物理康复、电子游戏的使用、运动捕捉技术和上肢康复。文献选择仅限于 2015 年至 2020 年期间发表的开放获取作品,获得了 19 篇符合纳入标准的文章。这些作品报告了惯性测量单元(37%)、Kinect 传感器(48%)和其他技术(15%)的使用情况。确定 26%的作品使用商业产品,而 74%是独立开发的。另一个发现是,47%的作品专注于中风后的运动恢复。最后,多样化的研究旨在使用结合惯性单元的运动捕捉系统支持物理康复,这些系统提供精度和可及性,成本低。显然需要继续提出利用提供精度和医疗保健覆盖的技术来应对康复挑战的建议,并且这些技术还需要整合促进患者动机和参与的元素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a299/7660052/e55b17de10ee/sensors-20-05989-g001.jpg

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