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使用速度变化和深度信息的视觉反馈噪声分析圆形跟踪运动的额状面和矢状面的运动控制策略。

Analysis of motor control strategy for frontal and sagittal planes of circular tracking movements using visual feedback noise from velocity change and depth information.

机构信息

Department of Mechanical and Control Engineering, Handong Global University, Pohang, Republic of Korea.

Department of Information and Computer Engineering, National Institute of Technology, Gunma College, Maebashi, Japan.

出版信息

PLoS One. 2020 Nov 11;15(11):e0241138. doi: 10.1371/journal.pone.0241138. eCollection 2020.

Abstract

We aim to investigate a control strategy for the circular tracking movement in a three-dimensional (3D) space based on the accuracy of the visual information. After setting the circular orbits for the frontal and sagittal planes in the 3D virtual space, the subjects track a target moving at a constant velocity. The analysis is applied to two parameters of the polar coordinates, namely, ΔR (the difference in the distance from the center of a circular orbit) and Δω (the difference in the angular velocity). The movement in the sagittal plane provides different depth information depending on the position of the target in orbit, unlike the task of the frontal plane. Therefore, the circular orbit is divided into four quadrants for a statistical analysis of ΔR. In the sagittal plane, the error was two to three times larger in quadrants 1 and 4 than in quadrants 2 and 3 close to the subject. Here, Δω is estimated using a frequency analysis; the lower the accuracy of the visual information, the greater the periodicity. When comparing two different planes, the periodicity in the sagittal plane was approximately 1.7 to 2 times larger than that of the frontal plane. In addition, the average angular velocity of the target and tracer was within 0.6% during a single cycle. We found that if the amount of visual information is reduced, an optimal feedback control strategy can be used to reduce the positional error within a specific area.

摘要

我们旨在研究一种基于视觉信息精度的三维(3D)空间中圆形跟踪运动的控制策略。在 3D 虚拟空间中设置了额状面和矢状面的圆形轨道后,受试者以恒定速度跟踪移动的目标。该分析应用于极坐标的两个参数,即 ΔR(圆形轨道中心距离的差异)和 Δω(角速度的差异)。与额状面的任务不同,矢状面的运动根据轨道上目标的位置提供不同的深度信息。因此,圆形轨道被分为四个象限,用于对 ΔR 进行统计分析。在矢状面中,象限 1 和 4 的误差比靠近受试者的象限 2 和 3 大两到三倍。在这里,使用频率分析来估计 Δω;视觉信息的精度越低,周期性越大。在比较两个不同的平面时,矢状面的周期性大约是额状面的 1.7 到 2 倍。此外,在单个周期内,目标和示踪剂的平均角速度在 0.6%以内。我们发现,如果视觉信息量减少,可以使用最佳反馈控制策略来减少特定区域内的位置误差。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32f0/7657550/f472e2ed7065/pone.0241138.g001.jpg

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