Predicting aperture crossing behavior from within-trial metrics of motor control reliability

被引:5
|
作者
Lucaites, Kathryn M. [1 ]
Venkatakrishnan, Roshan [2 ]
Bhargava, Ayush [2 ]
Venkatakrishnan, Rohith [2 ]
Pagano, Christopher C. [1 ]
机构
[1] Clemson Univ, Dept Psychol, 418 Brackett Hall, Clemson, SC 29634 USA
[2] Clemson Univ, Sch Comp, 100 McAdams Hall, Clemson, SC 29634 USA
关键词
Affordances; Lateral sway; Motor control reliability; Apertures; BODY-SCALED INFORMATION; TIME-SERIES ANALYSIS; PERCEIVING AFFORDANCES; APPROXIMATE ENTROPY; PERCEPTION; VARIABILITY; WALKING; LOCOMOTION; DYNAMICS; DEPENDS;
D O I
10.1016/j.humov.2020.102713
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Actors utilize intrinsically scaled information about their geometric and dynamic properties when perceiving their ability to pass through openings. Research about dynamic factors of affordance perception have shown that the reliability of a given movement, or the precision of one's motor control for that movement, increase the buffer space used when interacting with the environment. While previous work has assessed motor control reliability as a person-level variable (i.e., behavior is aggregated across many trials), the current study assessed how characteristics of motor control and movement reliability within a single trial impact real-time action strategies for passing through apertures. Participants walked 5 m and then passed through apertures of various widths while their motions were tracked. For each trial, we collected walking time-series data, then calculated the magnitude and complexity of the lateral sway. Assessing two behavioral measures of the buffer, we found that trial-level metrics of motor control reliability, in addition to the person-level metrics previously studied, significantly predicted the buffer on each trial. This study supports previous claims that actors pick up real-time information about their dynamic capabilities in order to perceive and act within their environment. Further, the study recommends that future affordance research consider trial-level movement data, including nonlinear analyses that inform the pattern and structure of motor control reliability.
引用
收藏
页数:11
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