This study investigated how environmental design shapes perceptual-motor exploration, when meta-stable regions of performance are created. Here, we examined how creating meta-stable regions of performance could destabilize pre-existing skills, favoring greater exploration of performance environments, exemplified in this study by climbing surfaces. In this investigation we manipulated hold orientations on an indoor climbing wall to examine how nine climbers explored, learned, and transferred various trunk-rolling motion patterns and hand grasping movements. The learning protocol consisted of four sessions, in which climbers randomly ascended three different routes, as fluently as possible. All three routes were 10.3 m in height and composed of 20 hand-holds at the same locations on an artificial climbing wall; only hold orientations were altered: (i) a horizontal-edge route was designed to afford horizontal hold grasping, (ii) a vertical-edge route afforded vertical hold grasping, and (iii), a double-edge route was designed to afford both horizontal and vertical hold grasping. As a meta-stable condition of performance invite an individual to both exploit his pre-existing behavioral repertoire (i.e., horizontal hold grasping pattern and trunk face to the wall) and explore new behaviors (i.e., vertical hold grasping and trunk side to the wall), it was hypothesized that the double-edge route characterized a meta-stable region of performance. Data were collected from inertial measurement units located on the neck and hip of each climber, allowing us to compute rolling motion referenced to the artificial climbing wall. Information on ascent duration, the number of exploratory and performatory movements for locating hand-holds, and hip path was also observed in video footage from a frontal camera worn by participants. Climbing fluency was assessed by calculating geometric index of entropy. Results showed that the meta-stable condition of performance may have afforded utilization of more adaptive climbing behaviors (expressed in higher values for range and variability of trunk rolling motion and greater number of exploratory movements). Findings indicated how climbers learn to explore and, subsequently, use effective exploratory search strategies that can facilitate transfer of learning to performance in novel climbing environments.
This study investigated a new performance indicator to assess climbing fluency (smoothness of the hip trajectory and orientation of a climber using normalized jerk coefficients) to explore effects of practice and hold design on performance. Eight experienced climbers completed four repetitions of two, 10-m high routes with similar difficulty levels, but varying in hold graspability (holds with one edge vs holds with two edges). An inertial measurement unit was attached to the hips of each climber to collect 3D acceleration and 3D orientation data to compute jerk coefficients. Results showed high correlations (r = .99, P < .05) between the normalized jerk coefficient of hip trajectory and orientation. Results showed higher normalized jerk coefficients for the route with two graspable edges, perhaps due to more complex route finding and action regulation behaviors. This effect decreased with practice. Jerk coefficient of hip trajectory and orientation could be a useful indicator of climbing fluency for coaches as its computation takes into account both spatial and temporal parameters (ie, changes in both climbing trajectory and time to travel this trajectory).
Abstract-This paper presents a novel application of a machine learning method to automatically detect and classify climbing activities using inertial measurement units (IMUs) attached to the wrists, feet, and pelvis of the climber. This detection/classification can be useful for research in sport science to replace manual annotation where IMUs are becoming common. Detection requires a learning phase with manual annotation to construct statistical models. Full-body activity is then classified based on the detection of each IMU.
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