OpenPose and its current applications in sports and exercise science: a review

The aim of this scoping review is to investigate current applications of a markerless human pose estimation (HPE) algorithm in sports and exercise science. 17 studies are selected for this pur-pose. Results show that HPE is applied already in a variety of sports for different aims and pur-poses. Even though it provides many advantages over marker-based approaches, it still comes with challenges that need to be tackled in future research.Ziel dieser Übersichtsarbeit ist es, die aktuellen Anwendungen eines markerlosen Algorithmus zur Schätzung der menschlichen Körperhaltung (HPE) in der Sport- und Bewegungswissenschaft zu untersuchen. Zu diesem Zweck wurden 17 Studien ausgewählt. Die Ergebnisse zeigen, dass HPE bereits in einer Vielzahl von Sportarten mit unterschiedlichen Zielen und Zwecken eingesetzt wird. Obwohl sie viele Vorteile gegenüber markerbasierten Ansätzen bietet, gibt es immer noch Herausforderungen, die in der zukünftigen Forschung angegangen werden müssen

Evaluating the Effect of Shoes with Varying Mass on Vertical Ground Reaction Force Parameters in Short-Term Running

International Journal of Exercise Science 15(1): 191-205, 2022. Past investigations have revealed that running shoes affect ground reaction force parameters. However, these studies are unclear as to whether these changes, which occur while running in different shoe types of differing masses, are the result of the structural design or the mass of the shoe. The main aim of this study is to evaluate the effect of shoe mass on vertical ground reaction force parameters: active peak and impulse. Methods. 21 male runners (24.52 years old (± 3.09) and 77.13kg (± 7.9)) participated in the experiment. A baseline shoe (BS) = 283g and four weighted shoes (shoe 2 = 333g, shoe 3 = 433g, shoe 4 = 533g and shoe 5 = 598g) were compared for 8 minutes of running on the instrumented treadmill. Each shoe was compared in a repeated measurement with the BS. Results showed that active peaks and impulses differed significantly (p \u3c .05) between the BS and weighted shoes, except for shoe 2. From the threshold of 433g (shoe 3, which is 1.5 times heavier than the BS), we observed a significant increase in the vertical ground reaction force peak (1.86%) and impulse (1.84%). Other shoes such as shoe 4 and shoe 5, produced increasingly active peaks (N) of 2.08% N and 2.45% N compared to the BS. Increase of shoe masses in shoe 3, shoe 4, and shoe 5 resulted in an increase of impulse up to 1.84% Nm, 1.85% Nm and 2.49% Nm compared to the BS. Our determination of the shoe masses influencing these kinetic parameters may be a step towards reducing running-related injuries that result from accumulated microtrauma

COMPARATIVE STUDY OF SHOE-SURFACE INTERACTION IN TRAIL RUNNING - SUBJECTIVE AND OBJECTIVE EVALUATION

The purpose of this study is to compare and evaluate different running shoes in various surface conditions in two measurement phases. In the subjective test, fourteen trail runners performed the experiment with three running shoes in distinct surface conditions. Three features, comfort, cushioning and traction, were rated by means of questionnaire. In the objective measurement, a traction tester device was configured to simulate the movement and evaluate the rotational traction of the three shoes on different surfaces. The subjective test showed a significant difference with respect to comfort and cushioning. The objective measurement in dry conditions showed a significant decrease (P \u3c 0.05) in rotational traction on different surface types; rotational traction in wet conditions was significantly lower (P \u3c 0.05) than in dry conditions

Reinforcement learning estimates muscle activations

A digital twin of the human neuromuscular system can substantially improve the prediction of injury risks and the evaluation of the readiness to return to sport. Reinforcement learning (RL) algorithms already learn physical quantities unmeasurable in biomechanics, and hence can contribute to the development of the digital twin. Our preliminary results confirm the potential of RL algorithms to estimate the muscle activations of an athlete’s moves.Ein digitaler Zwilling des menschlichen neuromuskulären Systems kann die Vorhersage von Verletzungsrisiken und die Bewertung der Bereitschaft zur Rückkehr in den Sport erheblich verbessern. Algorithmen des bestärkenden Lernens (Reinforcement Learning, RL) lernen bereits physikalische Größen, die in der Biomechanik nicht messbar sind, und können daher zur Entwicklung des digitalen Zwillings beitragen. Unsere vorläufigen Ergebnisse bestätigen das Potenzial von RL-Algorithmen zur Schätzung der Muskelaktivierung bei den Bewegungen eines Sportlers

The ISEA Winterschool in Sports Engineering: 5 Years of Education and Team Building Experiences☆

Abstract Aim of the work is to present the ISEA Winterschool experience, spanning over the last 5 years. From 2011 to 2015, 150 students coming from several countries of the world joined the Winterschool in San Vito di Cadore, Italy, spending five days of intense teaching, testing and analysis activities under the guidance of 11 university professors experts in the field of winter sports. The support of about 25 tutors and the presence of a number of industry representative allowed the community to grow in the knowledge of Wintersports engineering and to build and reinforce friendly collaborations. This fostered the exchange of knowledges, stimulated joint projects and student exchanges over the years, that will last as positive results of the experience

A Fuzzy Controller Design for a Mechatronic Ski Binding

Mechatronic Ski Bindings are the most promising technical solution to reduce knee injuries in alpine skiing. The key to a successful system is the algorithm controlling the bindings adaption of the retention values. A fuzzy controller has advantages compared to classical controllers due to missing information about injury mechanisms and the complex dynamics of the skier. We present a controller structure and test it using the injury case reported in the literature.Mechatronische Skibindungen sind die vielversprechendste technische Lösung zur Reduzierung von Knieverletzungen im alpinen Skisport. Der Schlüssel zu einem erfolgreichen System ist der Algorithmus, der die Anpassung der Bindungen an die Haltewerte steuert. Ein Fuzzy-Regler hat Vorteile gegenüber klassischen Reglern, da Informationen über Verletzungsmechanismen und die komplexe Dynamik des Skifahrers fehlen. Wir stellen eine Reglerstruktur vor und testen sie anhand eines in der Literatur beschriebenen Verletzungsfalls

METHODOLOGICAL CHALLENGES FOR BIOMECHANICAL APPOACHES IN WINTER SPORTS

Many research questions related to performance or to injury prevention require biomechanical approaches and study plans that provide the best achievable compromise between internal and external validity. This is especially true for winter sport activities like skiing or snowboarding which cannot adequately be reproduced under laboratory conditions. The keynote presentation will illustrate how these methodological challenges have been addressed to answer three research questions related to injury prevention and the development of safety gear in winter sports: (1) the loading of the hip joint at different skiing manoeuvers (to answer the question if skiing is recommendable sport for people with hip replacement), (2) the effectiveness of wrist guards for the prevention of wrist or lower arm fractures in snowboarding (3) the development of algorithms for mechatronic ski bindings with the target to reduce the unchanged high rate of knee injuries