Background The gait modification strategies Trunk Lean and Medial Thrust have been shown to reduce the external knee adduction moment (EKAM) in patients with knee osteoarthritis which could contribute to reduced progression of the disease. Which strategy is most optimal differs between individuals, but the underlying mechanism that causes this remains unknown. Research question Which gait parameters determine the optimal gait modification strategy for individual patients with knee osteoarthritis? Methods Forty-seven participants with symptomatic medial knee osteoarthritis underwent 3-dimensional motion analysis during comfortable gait and with two gait modification strategies: Medial Thrust and Trunk Lean. Kinematic and kinetic variables were calculated. Participants were then categorized into one of the two subgroups, based on the modification strategy that reduced the EKAM the most for them. Multiple logistic regression analysis with backward elimination was used to investigate the predictive nature of dynamic parameters obtained during comfortable walking on the optimal modification gait strategy. Results For 68.1 % of the participants, Trunk Lean was the optimal strategy in reducing the EKAM. Baseline characteristics, kinematics and kinetics did not differ significantly between subgroups during comfortable walking. Changes to frontal trunk and tibia angles correlated significantly with EKAM reduction during the Trunk Lean and Medial Thrust strategies, respectively. Regression analysis showed that MT is likely optimal when the frontal tibia angle range of motion and peak knee flexion angle in early stance during comfortable walking are high (R2Nagelkerke = 0.12). Significance Our regression model based solely on kinematic parameters from comfortable walking contained characteristics of the frontal tibia angle and knee flexion angle. As the model explains only 12.3 % of variance, clinical application does not seem feasible. Direct assessment of kinetics seems to be the most optimal strategy for selecting the most optimal gait modification strategy for individual patients with knee osteoarthritis.
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.
BACKGROUND: Patients with knee osteoarthritis can adapt their gait to unload the most painful knee joint in order to try to reduce pain and improve physical function. However, these gait adaptations can cause higher loads on the contralateral joints. The aim of the study was to investigate the interlimb differences in knee and hip frontal plane moments during gait in patients with knee osteoarthritis and in healthy controls.METHODS: Forty patients with knee osteoarthritis and 19 healthy matched controls were measured during comfortable treadmill walking. Frontal plane joint moments were obtained of both hip and knee joints. Differences in interlimb moments within each group were assessed using statistical parametric mapping and discrete gait parameters.FINDINGS: No interlimb differences were observed in patients with knee osteoarthritis and control subjects at group level. Furthermore, the patients presented similar interlimb variability as the controls. In a small subgroup (n = 12) of patients, the moments in the most painful knee were lower than in the contralateral knee, while the other patients (n = 28) showed higher moments in the most painful knee compared to the contralateral knee. However, no interlimb differences in the hip moments were observed within the subgroups.INTERPRETATION: Patients with knee osteoarthritis do not have interlimb differences in knee and hip joint moments. Patients and healthy subjects demonstrate a similar interlimb variability in the moments of the lower extremities. In this context, differences in knee pain in patients with knee osteoarthritis did not induce any interlimb differences in the frontal plane knee and hip moments.
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.
Binnen het 2-jarige onderzoeksprogramma ‘The Network is the Message’ is voor social media en de marketingcommunicatie branche een kneedbaar’ denkmodel ontwikkeld om de impact van social media binnen het hele bedrijf in kaart te brengen en zodanig effectiever te kunnen inzetten tijdens de hele klantreis van de consument. Binnen het nieuwe, kleinschalige vervolgonderzoek ‘Effectiever met data door MKB’ willen we dat model verder ontwikkelen tot een eenvoudig, praktisch adviesmodel, zodat niet alleen marcom professionals, maar MKB-ers van alle branches meer data bedreven & gedreven worden, hun prestaties kunnen monitoren en verbeteren en zo effectiever bij het ondernemen. Meer concreet wordt een model ontwikkeld met fasen conform het bedrijf- & marketingplanningsproces en worden per fase zowel MKB-doelstellingen, KPI’s als relevante kwantitatieve -, kwalitatieve - én financiële metrics en mogelijke databronnen binnen en buiten het bedrijf geïdentificeerd, die samengenomen inzicht geven in de concrete ondernemingskansen, naast praktisch verbeteringsadvies en de aanzet tot een meer data gedreven manier van werken. Het model wordt toegepast en meteen geïmplementeerd bij het MKB door 4e jrs. Commerciële Economie studenten van de HU bij het stagebedrijf, waar zij afstuderen, waarmee zij tevens hun toegevoegde waarde aantonen.
