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MODELING AND FILTERING ATHETOID MOVEMENT FOR ASSISTIVE COMPUTER INTERFACES

机译：辅助计算机接口的建模和滤波等速线运动

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This paper presents a novel approach to modeling and filtering of athetoid motion for use in assistive computer interfaces during targeting tasks such as clicking on icons. Data were recorded from a subject with athetosis during unassisted icon-clicking trials with an isometric joystick. In order to facilitate development and preliminary testing of filter designs without the cost and difficulty of repeated testing with subjects with athetosis, a quantitative model of the recorded subject data was developed using pseudoinverse methods. Using this model within the visuomotor control loop for the icon-clicking task, a prediction filter was then developed to reduce the target acquisition time for the user. The filter consists of an "autoregressive stretching window" system which selects five data points evenly distributed across the input and output histories to predict the intended target, together with a second-order system that smoothes the movement of the cursor. The filter has demonstrated a reduction of up to 49% in target acquisition time in preliminary experiments with the athetoid model.
机译：本文提出了一种新颖的方法，用于在目标任务（例如单击图标）期间在辅助计算机界面中使用的动脉粥样硬化运动的建模和过滤。使用等距摇杆在无辅助图标点击试验期间记录了一个患有无神力症患者的数据。为了简化过滤器设计的开发和初步测试，而又没有成本和困难，对带有无动脉粥样硬化的受试者进行重复测试，使用伪逆方法开发了记录的受试者数据的定量模型。通过在视觉控制回路中使用该模型来执行图标单击任务，然后开发了预测过滤器以减少用户的目标获取时间。该过滤器由一个“自回归拉伸窗口”系统和一个平滑光标移动的二阶系统组成，该系统选择在输入和输出历史上均匀分布的五个数据点以预测目标。该过滤器已经证明，在使用动脉粥样化模型的初步实验中，目标获取时间最多可减少49％。

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