由于练习虚拟游戏,中风患者的手轨迹有所改善(或没有改善!)

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
P. Passos, A. Diniz, Aline Braga Galvão Silveira Fernandes, Jacilda Oliveira dos Passos, Lorenna Raquel Dantas de Macedo Borges, T. Campos
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引用次数: 1

摘要

运动轨迹包含重要的时空信息,以表征需要位移的人类活动(例如抓住物体)。轨迹(dis)相似性度量在轨迹数据分析中具有高度相关性。本研究的主要目的是开发Procrustes方法的运行版本,以量化轨迹随时间的差异,作为一种可用于进一步研究的方法。经验数据用于量化中风患者在参与联合康复计划(虚拟现实加传统治疗)后,在日常生活任务(饮用水)中的运动变化。模拟研究的结果反映了运行程序方法的可靠性,该方法可以随着时间的推移连续量化轨迹之间的差异。对于经验数据,该方法确定了饮用水任务的关键部分,提供的信息可能表明联合计划对中风患者日常生活任务的有益影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improvements (or not!) in the hand trajectory of stroke patients due to practice of a virtual game
Movement trajectories contain important spatio-temporal information to characterise human activities that require displacements (eg grasp an object). A trajectory (dis)similarity measure is highly relevant in trajectory data analysis. The main purpose of this study was to develop a running version of the Procrustes Method to quantify dissimilarity between trajectories along time, as a method that can be used in further research. Empirical data was used to quantify changes in stroke patients’ movements in a daily life task (drinking water) after participating in a combined rehabilitation program (virtual reality plus conventional therapy). Results of the simulation study reflected the reliability of the Running Procrustes Method to quantify the dissimilarity between trajectories continuously over time. For the empirical data, this method identified critical parts of the drinking water task, providing information that might suggest beneficial effects of the combined program in stroke patients’ daily life tasks.
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来源期刊
Adaptive Behavior
Adaptive Behavior 工程技术-计算机:人工智能
CiteScore
4.30
自引率
18.80%
发文量
34
审稿时长
>12 weeks
期刊介绍: _Adaptive Behavior_ publishes articles on adaptive behaviour in living organisms and autonomous artificial systems. The official journal of the _International Society of Adaptive Behavior_, _Adaptive Behavior_, addresses topics such as perception and motor control, embodied cognition, learning and evolution, neural mechanisms, artificial intelligence, behavioral sequences, motivation and emotion, characterization of environments, decision making, collective and social behavior, navigation, foraging, communication and signalling. Print ISSN: 1059-7123
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