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Football players have a high risk of leg muscle injuries, especially when exposed to mental stress. Injuries to muscles of the thigh are common in amateur and professional football, representing almost a third of all injuries. These injuries occur primarily in non-contact situations and from overuse. They can lead to a range of costs, including financial costs associated with treatment as well as those associated with long-term recovery, and absence from training and/or competition. Further, there is a high risk of injury recurrence and subsequent injury.
Evaluation of muscle recruitment and muscle models in musculoskeletal simulation of dynamic motion
(2021)
Musculoskeletal simulation plays an increasingly important role in sports biomechanics. In the last years, the field of application widened from orthopaedics and ergonomics to sports [1]. A muscle recruitment algorithm with a quadratic objective function is usually used to calculate muscle activity in dynamic movements. The agreement of calculated and measured thigh muscle activity has already been investigated [2]. They found a strong agreement for sprinting and running, while the correlation decreased for side-cutting manoeuvres. Nevertheless, the influence of different muscle recruitment criteria on muscle activity in dynamic musculoskeletal simulations is currently unknown. Hence, this study aimed to analyse the effect of different muscle recruitment criteria and muscle models on the correlation of numerical and measured muscle activity in highly dynamic movements.
Osteoporosis is a common disease of old age. However, in many cases, it can be very well prevented and counteracted with physical activity, especially high-impact exercises. Wearables have the potential to provide data that can help with continuous monitoring of patients during therapy phases or preventive exercise programs in everyday life. This study aimed to determine the accuracy and reliability of measured acceleration data at different body positions compared to accelerations at the pelvis during different jumping exercises. Accelerations at the hips have been investigated in previous studies with regard to osteoporosis prevention. Data were collected using an IMU-based motion capture system (Xsens) consisting of 17 sensors. Forty-nine subjects were included in this study. The analysis shows the correlation between impacts and the corresponding drop height, which are dependent on the respective exercise. Very high correlations (0.83–0.94) were found between accelerations at the pelvis and the other measured segments at the upper body. The foot sensors provided very weak correlations (0.20–0.27). Accelerations measured at the pelvis during jumping exercises can be tracked very well on the upper body and upper extremities, including locations where smart devices are typically worn, which gives possibilities for remote and continuous monitoring of programs.