Assessing vibrotactile feedback strategies by controlling a cursor with unstable dynamics.
Assessing vibrotactile feedback strategies by controlling a cursor with unstable dynamics.
复制标题
通过控制动态不稳定的光标来评估振动触觉反馈策略。
DOI：
10.1109/embc.2014.6944152
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Batista,AaronP
中科院分区：
文献类型：
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作者：
Quick,KristinM;Card,NicholasS;Whaite,StephenM;Mischel,Jessica;Loughlin,Patrick;Batista,AaronP
脑机接口（BCI）控制主要使用视觉反馈。然而，真实的手臂运动是在多种反馈机制下控制的。缺乏额外的BCI反馈模式迫使用户在执行任务时保持视觉接触。这种严格的要求导致在固有地缺乏视觉反馈的任务（例如抓握）期间或当视觉注意力被转移时的差的BCI控制。使用我们称为临界稳定性任务（CST）的临界跟踪任务的修改版本[1]，我们测试了9名人类受试者使用自由手臂运动或捏力控制不稳定系统的能力。受试者提供视觉反馈，“比例”振动触觉反馈，或“开-关”振动触觉反馈的不稳定系统的状态。我们通过使虚拟系统更不稳定来增加控制任务的难度。我们判断一种特定形式的反馈的有效性，是指系统在失去控制之前所能达到的最大不稳定性。首先，受试者可以单独使用振动触觉反馈来控制一个不稳定的系统，虽然控制更好地使用视觉反馈。第二，“比例”振动触觉反馈提供了比“开关”振动触觉反馈稍好的控制。第三，在最有效的输入和反馈方法方面，受试者内部存在很大的差异。这突出了需要量身定制的输入和反馈方法的主题时，需要高度的控制。我们的新任务可以为传统的中心向外范式提供补充，以帮助提高实验室BCI研究的现实意义。
Brain computer interface (BCI) control predominately uses visual feedback. Real arm movements, however, are controlled under a diversity of feedback mechanisms. The lack of additional BCI feedback modalities forces users to maintain visual contact while performing tasks. Such stringent requirements result in poor BCI control during tasks that inherently lack visual feedback, such as grasping, or when visual attention is diverted. Using a modified version of the Critical Tracking Task [1] which we call the Critical Stability Task (CST), we tested the ability of 9 human subjects to control an unstable system using either free arm movements or pinch force. The subjects were provided either visual feedback, `proportional' vibrotactile feedback, or `on-off' vibrotactile feedback about the state of the unstable system. We increased the difficulty of the control task by making the virtual system more unstable. We judged the effectiveness of a particular form of feedback as the maximal instability the system could reach before the subject lost control of it. We found three main results. First, subjects can use solely vibrotactile feedback to control an unstable system, although control was better using visual feedback. Second, `proportional' vibrotactile feedback provided slightly better control than `on-off' vibrotactile feedback. Third, there was large intra-subject variability in terms of the most effective input and feedback methods. This highlights the need to tailor the input and feedback methods to the subject when a high degree of control is desired. Our new task can provide a complement to traditional center-out paradigms to help boost the real-world relevance of BCI research in the lab.