A Quantitative Comparison of Slackline Balancing Capabilities of Experts and Beginners

Mechanical stability criteria are able to explain balance and robustness during simple motions, however, humans have learned many complex balancing tasks for which science lacks a thorough understanding. In this work, we analyzed slackline balancing to define general balance performance indicators. The goal is to not only measure slackline expertise, but to be able to quantify stability during any balance task. For this, we compared beginners that had never balanced on a slackline before to professional slackline athletes. Further, all participants performed a static balance test, based on which we divided beginners into a balance-experienced and a balance-inexperienced group. On average, the balance experienced group was able to balance twice as long on the slackline and therefore, we showed that this static balance experience is a predictor of slackline balance performance. Based on over 300 balancing trials on the slackline of 20 participants, we then defined and evaluated over 30 balance metrics. The parameters can be grouped into quantification of stability and recovery movements, balance specific skills and balance strategies. We found that normalized angular momentum and center of mass acceleration are measures for overall stability, with lower values representing better stability and fewer recovery movements. We showed that improved hand coordination and adjusted stance leg compliance are valuable skills for balance tasks. especially when controlling external forces. Looking at posture and movement strategies, we found that professional slackliners have adapted a different mean pose with larger inertia and an upright head position, when compared to beginners.

Abstract licence: CC BY

1. 13.

   Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs · 2013

24 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.