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

Attitudes towards shared decision making in mental health: A qualitative synthesis

Purpose: Shared decision making (SDM) prioritises joint deliberation between practitioner and service user, and a respect for service-users’ experiential knowledge, values and preferences. The purpose of this paper is to review the existing literature pertaining to key stakeholders’ attitudes towards SDM in mental health. It examines whether perceived barriers and facilitators differ by group (e.g. service user, psychiatrist, nurse and social worker) and includes views of what facilitates and hinders the process for service users and practitioners. Design/methodology/approach: This review adopts the principles of a qualitative research synthesis. A key word search of research published between 1990 and 2016 was undertaken. Qualitative, quantitative and mixed methods studies were included. Findings: In total, 43 papers were included and several themes identified for service user and practitioner perspectives. Both practitioners and service users see SDM as an ethical imperative, and both groups highlight the need to be flexible in implementing SDM, suggesting it is context dependent. A range of challenges and barriers are presented by both practitioners and service users reflecting complex contextual and cultural features within which interactions in mental health take place. There were qualitative differences in what service users and practitioners describe as preventing or enabling SDM. The differences highlighted point towards different challenges and priorities in SDM for service users and practitioners. Originality/value: The presentation of nuanced views and attitudes that practitioners and service users hold represent an important and under reported area and offer insight into the reasons for the gap between idealised policy and actual practice of SDM in mental health settings

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