So far only a few studies are available on slackline balancing: Training effects of slackline balancing on posture, neuromuscular performance and other balance tasks have been well-studied ( Donath et al., 2013, 2015). The subject's Center of Mass (CoM) is well above the anchor points, thus the Virtual Pivot Point ( Maus et al., 2010), which is the point where all forces acting on the subject coincide, is below the CoM and does not provide stabilization, but makes the system intrinsically unstable. The restoring forces always point toward the straight line defined by the two anchor points ( Paoletti and Mahadevan, 2012 Athanasiadis, 2017).
Unlike balancing on flat surface, the contact point with the slackline can swing both sideways and vertically, which increases the difficulty of maintaining an upright position.
Slackline balancing is a sport where the athlete tries to maintain balance on an elastic ribbon band that is mounted between two anchor points as shown in Figure 1. Therefore, a lot can be learned for balance training, quantification of stability and even humanoid robotics by analyzing those tasks. In challenging balance exercises signs of stable or impaired balance are much more obvious than in every day situations.
LEARN TO SLACKLINE PROFESSIONAL
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. especially when controlling external forces. We showed that improved hand coordination and adjusted stance leg compliance are valuable skills for balance tasks. 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. The parameters can be grouped into quantification of stability and recovery movements, balance specific skills and balance strategies. Based on over 300 balancing trials on the slackline of 20 participants, we then defined and evaluated over 30 balance metrics. 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. Further, all participants performed a static balance test, based on which we divided beginners into a balance-experienced and a balance-inexperienced group. For this, we compared beginners that had never balanced on a slackline before to professional slackline athletes. The goal is to not only measure slackline expertise, but to be able to quantify stability during any balance task. In this work, we analyzed slackline balancing to define general balance performance indicators. 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. 2Canada Excellence Research Chair in Human-Centred Robotics and Machine Intelligence, Departments of Systems Design Engineering & Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada.1Optimization, Robotics and Biomechanics, Institute of Computer Engineering at Heidelberg University (ZITI), Heidelberg University, Heidelberg, Germany.
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