Experiments and Mathematical Modeling of Blindfolded Walking
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Date
2015-05
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The Ohio State University
Abstract
In an environment full of visual reference objects, it is easy for normal human to use vision to walk in a straight line for a fairly long time and distance. When the environment lacks reference sources (e.g. as in a desert, forest, meadow), or when external visual information is not available to the subjects, the subjects would tend to walk in non-straight-line paths (e.g., circles) even though they intend to go in straight lines. This research aimed to better understand the relation between vision and walking directional stability by using data collected from experiments to construct a mathematical model that can (at least approximately) predict people’s movements under blindfolded (or other no vision) situations. The experiments had two parts. In the first part, the subjects were asked to carry a GPS and walk on an open field while blindfolded. We found that the walking trajectories in these blind-folded outdoor experiments were far from straight-lines, with the subjects walking in curved paths with typical radius of curvature 8.8 m (mean over all subjects and trials). In the second part, the subjects were asked to walk as straight as possible from one end of the lab (indoors) to the other, again blindfolded. Several markers were put on the lower body of the subject. The lower body and pelvis movement were captured by the motion capture system. The data were processed by Matlab and used in the generation of mathematical model that relates body orientation to foot position. The mathematical model predicts the body position and heading angle, given the body position and heading angle of the previous step, including the noise and variability in the motion as measured in the indoor motion capture session. The simulated trajectories generated by the mathematical model were compared against the trajectories exhibited by the subjects on the field and we find that the simulated trajectories also have a substantial curvature. Thus, the simple model captures the experimental trajectories at least qualitatively, but there were quantitative differences between model predictions and data; a model that includes more state variables may be better. Understanding the role of vision in walking directional stability is an important part of a holistic understanding of human walking stability. A good model of human walking stability can be used as a tool for future researchers to develop medical devices to help those who have walking deficiencies or movement disorders.
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Keywords
Biomechanics, Blindfolded walking, Mathematical Model, gait