PURPOSE: To compare the responses in knee joint muscle activation patterns to different perturbations during gait in healthy subjects.SCOPE: Nine healthy participants were subjected to perturbed walking on a split-belt treadmill. Four perturbation types were applied, each at five intensities. The activations of seven muscles surrounding the knee were measured using surface EMG. The responses in muscle activation were expressed by calculating mean, peak, co-contraction (CCI) and perturbation responses (PR) values. PR captures the responses relative to unperturbed gait. Statistical parametric mapping analysis was used to compare the muscle activation patterns between conditions.RESULTS: Perturbations evoked only small responses in muscle activation, though higher perturbation intensities yielded a higher mean activation in five muscles, as well as higher PR. Different types of perturbation led to different responses in the rectus femoris, medial gastrocnemius and lateral gastrocnemius. The participants had lower CCI just before perturbation compared to the same phase of unperturbed gait.CONCLUSIONS: Healthy participants respond to different perturbations during gait with small adaptations in their knee joint muscle activation patterns. This study provides insights in how the muscles are activated to stabilize the knee when challenged. Furthermore it could guide future studies in determining aberrant muscle activation in patients with knee disorders.
Objective : The first aim of this study was to determine whether adolescents with asymptomatic Generalized Joint Hypermobility (GJH) have a lower level of physical functioning (physical activity level, muscle strength and performance) compared to non-hypermobile controls. Secondly, to evaluate whether the negative impact of perceived harmfulness on physical functioning was more pronounced in adolescents with asymptomatic GJH. Methods : Cross-sectional study. Sixty-two healthy adolescents (mean age 16.8, range 12-21) participated. Hypermobility (Beighton score), perceived harmfulness (PHODA-youth) and muscle strength (dynamometry), motor performance (Single-Leg-Hop-for-Distance) and physical activity level (PAL) (accelerometry) were measured. Hierarchical regression analyses were used to study differences in physical functioning and perceived harmfulness between asymptomatic GJH and non-hypermobile controls. Results : Asymptomatic GJH was associated with increased knee extensor muscle strength (peak torque/body weight; PT/BW), controlled for age and gender (dominant leg; ß = 0.29; p = .02). No other associations between asymptomatic GJH and muscle strength, motor performance and PAL were found. Perceived harmfulness was not more pronounced in adolescents with asymptomatic GJH. Conclusions : Adolescents with asymptomatic GJH had increased knee extensor muscle strength compared to non-hypermobile controls. No other differences in the level of physical functioning was found and the negative impact of perceived harmfulness was not more pronounced in adolescents with asymptomatic GJH.
In societies where physical activity levels are declining, stimulating sports participation in youth is vital. While sports offer numerous benefits, injuries in youth are at an all-time high with potential long-term consequences. Particularly, women football's popularity surge has led to a rise in knee injuries, notably anterior cruciate ligament (ACL) injuries, with severe long-term effects. Urgent societal attention is warranted, supported by media coverage and calls for action by professional players. This project aims to evaluate the potential of novel artificial intelligence-based technology to enhance player monitoring for injury risk, and to integrate these monitoring pathways into regular training practice. Its success may pave the way for broader applications across different sports and injuries. Implementation of results from lab-based research into practice is hindered by the lack of skills and technology needed to perform the required measurements. There is a critical need for non-invasive systems used during regular training practice and allowing longitudinal monitoring. Markerless motion capture technology has recently been developed and has created new potential for field-based data collection in sport settings. This technology eliminates the need for marker/sensor placement on the participant and can be employed on-site, capturing movement patterns during training. Since a common AI algorithm for data processing is used, minimal technical knowledge by the operator is required. The experienced PLAYSAFE consortium will exploit this technology to monitor 300 young female football players over the course of 1 season. The successful implementation of non-invasive monitoring of football players’ movement patterns during regular practice is the primary objective of this project. In addition, the study will generate key insights into risk factors associated with ACL injury. Through this approach, PLAYSAFE aims to reduce the burden of ACL injuries in female football players.
