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Characteristics of bi-directional unimanual and bimanual drawing movements: The application of the Delta-Lognormal models and Sigma-Lognormal model

机译:双向单向和双向绘图运动的特征:Delta-Lognormal模型和Sigma-Lognormal模型的应用

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The use of large digitizers, allowing users to interact using both hands simultaneously, are getting more and more popular in applications requiring human computer interaction. In most of these applications, gesture commands are used and these commands to activate specific actions can provide also information about the neuromuscular system of the user. As shown for single hand interactions, understanding of the neuromotor coordination processes using both hands could improve interface design. In the present paper, we address this topic with a first study aimed to characterize the bimanual and unimanual coordination. We compare the kinematic properties of movements performed unimanually and bimanually. Rapidly drawn lines are assessed using kinematic features in addition to the parameters estimated by two models, i.e., the Delta-Lognormal model and Sigma-Lognormal model. Sixteen right-handed participants were instructed to conduct 120 rapid drawing actions with the dominant hand, non-dominant hand, and both hands simultaneously. Kinematic variables (i.e. reaction time (RT) and movement time (MT)) together with parameters of the Delta-Lognormal model and Sigma-Lognormal model were extracted from the movements. The latter parameters estimate the agonist and antagonist synergies that contribute to the overall movement production of the rapid drawn lines. A 2 x 2 repeated measures ANOVA was applied to all dependent variables with manual condition (uni-vs bimanual) and hand used (dominant vs non-dominant) as independent factors. Parameters of the Delta-Lognormal model and Sigma-Lognormal model revealed that the prolonged preparation time of the bimanual task had both a central and peripheral origin, i.e., it originated at the CNS and neuromuscular levels. Furthermore, findings from the Sigma-lognormal model suggested that the dominant and non-dominant hand contribute differently to the manual conditions, which may lead to new heuristics for implementing command systems for computer interaction systems requiring bimanual manipulation as well as designing automatic systems for rehabilitative training. (c) 2018 Elsevier B.V. All rights reserved.
机译:大型数字转换器的使用(允许用户同时使用双手进行交互)在需要人机交互的应用中越来越受欢迎。在大多数这些应用中,使用手势命令,并且这些命令来激活特定动作也可以提供有关用户的神经肌肉系统的信息。如单手交互所示,使用两只手理解神经运动协调过程可以改善界面设计。在本文中,我们通过第一个研究来解决这个问题,该研究旨在表征两手和单手的协调。我们比较了单手和双手执行的运动的运动学特性。除了两个模型(即Delta对数正态模型和Sigma对数正态模型)估计的参数外,还使用运动学特征来评估快速绘制的线。指示16名惯用右手的参与者用优势手,非优势手和双手同时进行120次快速绘画动作。从运动中提取运动学变量(即反应时间(RT)和运动时间(MT))以及Delta对数正态模型和Sigma对数正态模型的参数。后面的参数估计了激动剂和拮抗剂的协同作用,这有助于快速绘制线条的整体运动产生。将2 x 2重复测量ANOVA应用于所有因变量,其中手动条件(uni-vs双手)和手动(显性与非显性)作为独立因素。 δ-对数正态模型和Sigma-对数正态模型的参数显示,双向任务准备时间的延长既有中心起源也有外围起源,即它起源于中枢神经系统和神经肌肉水平。此外,来自Sigma对数正态模型的结果表明,优势手和非优势手对手动条件的贡献不同,这可能会导致为需要双手操作的计算机交互系统实施命令系统以及为康复设计自动系统的新启发法训练。 (c)2018 Elsevier B.V.保留所有权利。

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