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用于上肢康复的严肃游戏的交互模式:系统评价。

Interaction Modalities Used on Serious Games for Upper Limb Rehabilitation: A Systematic Review.

机构信息

Research Center for Artificial Intelligence, Universidad Veracruzana, Xalapa, Mexico.

School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom.

出版信息

Games Health J. 2019 Oct;8(5):313-325. doi: 10.1089/g4h.2018.0129. Epub 2019 Jul 9.

Abstract

This systematic review aims to analyze the state-of-the-art regarding interaction modalities used on serious games for upper limb rehabilitation. A systematic search was performed in IEEE Xplore and Web of Science databases. PRISMA and QualSyst protocols were used to filter and assess the articles. Articles must meet the following inclusion criteria: they must be written in English; be at least four pages in length; use or develop serious games; focus on upper limb rehabilitation; and be published between 2007 and 2017. Of 121 articles initially retrieved, 33 articles met the inclusion criteria. Three interaction modalities were found: vision systems (42.4%), complementary vision systems (30.3%), and no-vision systems (27.2%). Vision systems and no-vision systems obtained a similar mean QualSyst (86%) followed by complementary vision systems (85.7%). Almost half of the studies used vision systems as the interaction modality (42.4%) and used the Kinect sensor to collect the body movements (48.48%). The shoulder was the most treated body part in the studies (19%). A key limitation of vision systems and complementary vision systems is that their device performances might be affected by lighting conditions. A main limitation of the no-vision systems is that the range-of-motion in angles of the body movement might not be measured accurately. Due to a limited number of studies, fruitful areas for further research could be the following: serious games focused on finger rehabilitation and trauma injuries, game difficulty adaptation based on user's muscle strength and posture, and multisensor data fusion on interaction modalities.

摘要

本系统评价旨在分析用于上肢康复的严肃游戏中使用的交互模式的最新技术。在 IEEE Xplore 和 Web of Science 数据库中进行了系统搜索。使用 PRISMA 和 QualSyst 协议来筛选和评估文章。文章必须符合以下纳入标准:必须用英文书写;至少有四页长;使用或开发严肃游戏;专注于上肢康复;并在 2007 年至 2017 年之间发表。最初检索到的 121 篇文章中,有 33 篇符合纳入标准。发现了三种交互模式:视觉系统(42.4%),互补视觉系统(30.3%)和无视觉系统(27.2%)。视觉系统和无视觉系统获得了相似的平均 QualSyst(86%),其次是互补视觉系统(85.7%)。几乎一半的研究将视觉系统作为交互模式(42.4%),并使用 Kinect 传感器来收集身体运动(48.48%)。研究中最常治疗的身体部位是肩部(19%)。视觉系统和互补视觉系统的一个主要限制是其设备性能可能会受到照明条件的影响。无视觉系统的主要限制是身体运动角度的运动范围可能无法准确测量。由于研究数量有限,进一步研究的有前景领域可能是:专注于手指康复和创伤损伤的严肃游戏,基于用户肌肉力量和姿势的游戏难度适应以及交互模式上的多传感器数据融合。

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