Salinas Mandy M, Wilken Jason M, Dingwell Jonathan B
Department of Kinesiology & Health Education, University of Texas, Austin, TX 78712, USA.
Center for the Intrepid, Brooke Army Medical Center, JBSA Ft. Sam Houston, TX, USA.
Gait Posture. 2017 Sep;57:15-20. doi: 10.1016/j.gaitpost.2017.05.002. Epub 2017 May 8.
Humans use visual optic flow to regulate average walking speed. Among many possible strategies available, healthy humans walking on motorized treadmills allow fluctuations in stride length (L) and stride time (T) to persist across multiple consecutive strides, but rapidly correct deviations in stride speed (S=L/T) at each successive stride, n. Several experiments verified this stepping strategy when participants walked with no optic flow. This study determined how removing or systematically altering optic flow influenced peoples' stride-to-stride stepping control strategies. Participants walked on a treadmill with a virtual reality (VR) scene projected onto a 3m tall, 180° semi-cylindrical screen in front of the treadmill. Five conditions were tested: blank screen ("BLANK"), static scene ("STATIC"), or moving scene with optic flow speed slower than ("SLOW"), matched to ("MATCH"), or faster than ("FAST") walking speed. Participants took shorter and faster strides and demonstrated increased stepping variability during the BLANK condition compared to the other conditions. Thus, when visual information was removed, individuals appeared to walk more cautiously. Optic flow influenced both how quickly humans corrected stride speed deviations and how successful they were at enacting this strategy to try to maintain approximately constant speed at each stride. These results were consistent with Weber's law: healthy adults more-rapidly corrected stride speed deviations in a no optic flow condition (the lower intensity stimuli) compared to contexts with non-zero optic flow. These results demonstrate how the temporal characteristics of optic flow influence ability to correct speed fluctuations during walking.
人类利用视觉光流来调节平均步行速度。在众多可行策略中，健康人在电动跑步机上行走时，会让步幅长度（L）和步幅时间（T）在多个连续步幅中持续波动，但会在每一步幅n时迅速纠正步幅速度（S = L/T）的偏差。当参与者在没有视觉光流的情况下行走时，多项实验验证了这种行走策略。本研究确定了去除或系统性改变视觉光流如何影响人们逐步步幅的控制策略。参与者在跑步机上行走，虚拟现实（VR）场景投射到跑步机前方一个3米高、180°的半圆柱形屏幕上。测试了五种条件：空白屏幕（“BLANK”）、静态场景（“STATIC”），或光流速度慢于（“SLOW”）、与行走速度匹配（“MATCH”）或快于（“FAST”）行走速度的动态场景。与其他条件相比，在“BLANK”条件下，参与者的步幅更短、速度更快，且步幅变异性增加。因此，当视觉信息被去除时，个体似乎行走得更加谨慎。视觉光流既影响人类纠正步幅速度偏差的速度，也影响他们实施该策略以试图在每一步幅保持大致恒定速度的成功率。这些结果与韦伯定律一致：与非零视觉光流的情境相比，健康成年人在无视觉光流条件下（较低强度刺激）能更快地纠正步幅速度偏差。这些结果表明了视觉光流的时间特征如何影响行走过程中纠正速度波动的能力。
