Knee joint forces (KJF) are biomechanical measures used to infer the load on knee joint structures. The purpose of this study is to develop an artificial neural network (ANN) that estimates KJF during sport movements, based on data obtained by wearable sensors. Thirteen participants were equipped with two inertial measurement units (IMUs) located on the right leg. Participants performed a variety of movements, including linear motions, changes of direction, and jumps. Biomechanical modelling was carried out to determine KJF. An ANN was trained to model the association between the IMU signals and the KJF time series. The ANN-predicted KJF yielded correlation coefficients that ranged from 0.60 to 0.94 (vertical KJF), 0.64 to 0.90 (anterior–posterior KJF) and 0.25 to 0.60 (medial–lateral KJF). The vertical KJF for moderate running showed the highest correlation (0.94 ± 0.33). The summed vertical KJF and peak vertical KJF differed between calculated and predicted KJF across all movements by an average of 5.7% ± 5.9% and 17.0% ± 13.6%, respectively. The vertical and anterior–posterior KJF values showed good agreement between ANN-predicted outcomes and reference KJF across most movements. This study supports the use of wearable sensors in combination with ANN for estimating joint reactions in sports applications.

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Introduction Speed is an important prerequisite in soccer. Therefore, a large number of tests have been developed aiming to investigate several speed skills relevant to soccer. This systematic review aimed to examine the validity and reliability of speed tests used in adult soccer players. Methods A systematic search was performed according to the PRISMA guidelines. Studies were included if they investigated speed tests in adult soccer players and reported validity (construct and criterion) or reliability (intraday and interday) data. The tests were categorized into linear-sprint, repeated-sprint, change-of-direction sprint, agility, and tests incorporating combinations of these skills. Results In total, 90 studies covering 167 tests were included. Linear-sprint (n = 67) and change-of-direction sprint (n = 60) were studied most often, followed by combinations of the aforementioned (n = 21) and repeated-sprint tests (n = 15). Agility tests were examined fewest (n = 4). Mainly based on construct validity studies, acceptable validity was reported for the majority of the tests in all categories, except for agility tests, where no validity study was identified. Regarding intraday and interday reliability, ICCs>0.75 and CVs<3.0% were evident for most of the tests in all categories. These results applied for total and average times. In contrast, measures representing fatigue such as percent decrement scores indicated inconsistent validity findings. Regarding reliability, ICCs were 0.11–0.49 and CVs were 16.8–51.0%. Conclusion Except for agility tests, several tests for all categories with acceptable levels of validity and high levels of reliability for adult soccer players are available. Caution should be given when interpreting fatigue measures, e.g., percent decrement scores. Given the lack of accepted gold-standard tests for each category, researchers and practitioners may base their test selection on the broad database provided in this systematic review. Future research should pay attention to the criterion validity examining the relationship between test results and match parameters as well as to the development and evaluation of soccer-specific agility tests.

Human posture is characterised by inherent body sway which forces the sensory and motor systems to counter the destabilising oscillations. Although the potential of biting to increase postural stability has recently been reported, the mechanisms by which the craniomandibular system (CMS) and the motor systems for human postural control are functionally coupled are not yet fully understood. The purpose of our study was, therefore, to investigate the effect of submaximum biting on postural stability and on the kinematics of the trunk and head. Twelve healthy young adults performed force-controlled biting (FB) and non-biting (NB) during bipedal narrow stance and single-leg stance. Postural stability was quantified on the basis of centre of pressure (COP) displacements, detected by use of a force platform. Trunk and head kinematics were investigated by biomechanical motion analysis, and bite forces were measured using a hydrostatic system. The results revealed that FB significantly improved postural control in terms of reduced COP displacements, providing additional evidence for the functional coupling of the CMS and human posture. Our study also showed, for the first time, that reductions in the sway of the COP were accompanied by reduced trunk and head oscillations, which might be attributable to enhanced trunk stiffness during FB. This physiological response to isometric activation of the masticatory muscles raises questions about the potential of oral motor activity as a strategy to reduce the risk of falls among the elderly or among patients with compromised postural control.

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This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Background: The robust identification of initial contact (IC) and toe-off (TO) events is a vital task in mobile sensor-based gait analysis. Shank attached gyroscopes in combination with suitable algorithms for data processing can robustly and accurately complete this task for gait event detection. However, little research has considered gait detection algorithms that are applicable to different locomotion tasks. Research question: Does a gait event detection algorithm for various locomotion tasks provide comparable estimation accuracies as existing task-specific algorithms? Methods: Thirteen males, equipped with a gyroscope attached to the right shank, volunteered to perform nine different locomotion tasks consisting of linear movements and movements with a change of direction. A rulebased algorithm for IC and TO events was developed based on the shank sagittal plane angular velocity. The algorithm was evaluated against events determined by vertical ground reaction force. Absolute mean error (AME), relative absolute mean error (RAME) and Bland-Altman analysis was used to assess its accuracy. Results: The average AME and RAME were 11 ± 3 ms and 3.07 ± 1.33 %, respectively, for IC and 29 ± 11 ms and 7.27 ± 2.92 %, respectively, for TO. Alterations of the walking movement, such as turns and types of running, slightly reduced the accuracy of IC and TO detection. In comparison to previous methods, increased or comparable accuracies for both IC and TO detection are shown.Significance: The study shows that the proposed algorithm is capable of detecting gait events for a variety of locomotion tasks by means of a single gyroscope located on the shank. In consequence, the algorithm can be applied to activities, which consist of various movements (e.g., soccer). Ultimately, this extends the use of mobile sensor-based gait analysis.