Abstract
Successful locomotion over complex terrain such as a rocky trail requires walkers to place each step on a safe foothold with high spatiotemporal precision while also taking the future terrain into account. We have previously shown that humans guide foot placement using a visual control strategy that exploits the physical dynamics of the bipedal gait cycle (e.g. Matthis, Barton & Fajen, 2014). However, this work was limited to locomotion over virtual terrain projected onto flat surfaces within the laboratory. In the current project, we develop a research protocol to allow accurate and integrated tracking of the eye, head, and feet during locomotion over real-world complex and rocky terrain, a protocol that has been previously limited by numerous technical challenges. This protocol allows us to test predictions derived from the results of previous lab-based studies on the visual control of foot placement in real-world terrains, and opens new opportunities to study the visual control of locomotion outside a laboratory setting. Our protocol utilizes a Positive Science mobile eye tracker with a GoPro scene camera and inertial measurement units (IMUs) attached to the head, trunk, and feet. Each IMU integrates the output of temperature-calibrated, tri-axial accelerometers, gyroscopes, and magnetometers to determine the sensor's orientation within a world-centered reference frame. The orientation quaternions produced by the head and trunk-mounted IMUs were used to rotate the gaze vectors recorded by the eye tracker in order to specify gaze fixations within a body-centered reference frame and relate gaze location to foot placement. In a pilot study, subjects walked across different types of real-world terrain while performing different distraction tasks. Preliminary results reveal that foot placement in complex terrain is highly demanding of attentional resources, and that the control strategies used to guide foot placement vary dramatically according to the difficulty of the terrain being traversed. Meeting abstract presented at VSS 2015. Language: en
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