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.

Background: The prevalence of knee osteoarthritis (KOA) in the adult population is high and patients profit from individualized therapy approaches. Just-in-time adaptive interventions (JITAIs) are upcoming digital interventions for behavior change. Objective: This systematic review summarizes the features and effectiveness of existing JITAIs regarding important physiological health outcomes and derives the most promising features for the use case of KOA. Methods: The electronic databases PubMed, Web of Science, Scopus, and EBSCO were searched using keywords related to JITAIs, physical activity (PA), sedentary behavior (SB), physical function, quality of life, pain, and stiffness. JITAIs for adults that focused on the effectiveness of at least 1 of the selected outcomes were included and synthesized qualitatively. Study quality was assessed with the Quality Assessment Tool Effective Public Health Practice Project. Results: A total of 45 studies with mainly weak overall quality were included in this review. The studies were mostly focused on PA and SB and no study examined stiffness. The design of JITAIs varied, with a frequency of decision points from a minute to a day, device-based measured and self-reported tailoring variables, intervention options including audible or vibration prompts and tailored feedback, and decision rules from simple if-then conditions based on 1 variable to more complex algorithms including contextual variables. Conclusions: The use of frequent decision points, device-based measured tailoring variables accompanied by user input, intervention options tailored to user preferences, and simple decision rules showed the most promising results in previous studies. This can be transferred to a JITAI for the use case of KOA by using target variables that include breaks in SB and an optimum of PA considering individual knee load for the health benefits of patients.

Ground reaction forces (GRFs) are crucial for understanding movement biomechanics and for assessing the load on the musculoskeletal system. While inertial measurement units (IMUs) are increasingly used for gait analysis in natural environments, they cannot directly capture GRFs. Machine learning can be applied to predict 3D-GRFs based on IMU data. However, previous studies mainly focused on vertical GRF (vGRF) and isolated movement tasks. This study aimed to systematically evaluate the prediction accuracy of convolutional neural networks (CNNs) for 3D-GRFs using IMUs from single and multiple sensor configurations across various movement tasks. 20 healthy participants performed six movement tasks including walking, stair ascent, stair descent, running, a running step turn and a running spin turn at self-selected speeds. CNNs were trained to predict 3D-GRFs on IMU time series data for different configurations (lower body [7 IMUs], single leg [4 IMUs], femur-tibia [2 IMUs], tibia [1 IMU] and pelvis [1 IMU]). Prediction accuracies were assessed based on leave-one-subject-out cross validations using Pearson correlation (r) and relative root mean squared error (relRMSE). Across all tasks, CNNs predicted vGRF most accurately (r = 0.98, relRMSE ≤ 7.44 %), followed by anterior-posterior GRF (r ≥ 0.92, relRMSE ≤ 14.24 %), with medial-lateral GRF being the least accurate (r ≥ 0.74, relRMSE ≤ 29.46 %). CNNs predicted vGRF consistently across tasks, with similar accuracy for multi IMU (average r = 0.98, average relRMSE: 6.06 %) and single IMU configurations (average r = 0.98, average relRMSE: 6.88 %), supporting single IMU configurations for vGRF in practical applications. During cutting maneuvers, the lower body configuration reduces the relRMSE for mlGRF (5.23-12.46 %) and apGRF (1.53-3.16 %) compared to single IMU configurations. However, for mlGRF and apGRF during cutting tasks, lower body configuration improve accuracy, highlighting a trade-off between simplicity and performance.

Background: The effectiveness of knee orthoses as part of conservative treatment for patients with medial knee osteoarthritis has not been fully explored. The purpose of this study was to evaluate the effects of a novel semi-rigid knee orthosis on pain, physical activity, and functional capacity. Methods: Pain levels, physical activity, and functional capacity were assessed in 24 participants experiencing symptomatic medial knee osteoarthritis one week before (i.e., pretest) initiating a six-week orthosis intervention and again during the final week of the intervention (i.e., post-test). Results: Night pain, pain during walking, pain during stair climbing, and pain during sitting consistently decreased by 41% to 48% while wearing the knee orthosis. Device-based measured physical activity showed a 20.2-min increase in vigorous physical activity during the post-test, while light and moderate physical activity did not show significant changes. After six weeks of orthosis application, there was a 5% increased distance for the six-minute walk test, and participants reported fewer limitations both in everyday and athletic activities, as well as an enhanced quality of life. Conclusions: These findings highlight the potential effectiveness of a semi-rigid knee orthosis to enhancing functional capacity and quality of life. More extensive and longer clinical trials are needed to improve confidence in these findings and understand their impact on disease progression.

Stair walking is more demanding than level walking, and differences have been found between steady-state stair walking and gait-to-stair or stair-to-gait transition. However, there is limited knowledge on steady-state stair walking biomechanics in people with hip osteoarthritis (HOA) as all existing data were obtained during gait-to-stair transition. The aim of the present study was to investigate the effects of mild-to-moderate HOA on hip and trunk biomechanics and dynamic balance during steady-state stair walking. Hip and trunk biomechanics and dynamic balance during steady-state stair walking were assessed in 21 participants with mild-to-moderate HOA and 21 age-matched healthy controls using an optoelectronic motion capture system and a custom-built instrumented six-step staircase. Dynamic balance was assessed using the inverted pendulum model with an extrapolated centre of mass. Differences between the two groups were analysed with an independent t-test either on discrete parameters or on entire time curves using statistical parametric mapping. The HOA group showed longer stride and stance phase durations during stair ascent and descent, and lower peak vertical CoM acceleration during stair descent vs. the control group. Trunk kinematics did not differ between groups. Lower frontal plane hip range of motion and hip internal rotation moment, but greater anterior margin of stability were observed during stair ascent in the HOA vs. control group. Mild-to-moderate HOA reduced frontal hip mobility but did not affect mediolateral dynamic balance during steady-state stair walking. Despite a lack of alterations in sagittal hip or trunk kinematics or dynamics, greater anterior margin of stability in HOA vs. control participants showed a more stable but potentially less efficient motion during stair ascent. Lastly, lower vertical acceleration during stair descent might reduce impact and joint loading at initial contact. Future studies should analyse gait efficiency and joint loading, and the effect of HOA severity and muscle force capacity on steady-state stair walking biomechanics in people with HOA.

Background: With the increasing digitalization of daily life, internet-based entertainment such as gaming and streaming has advanced to one of the megatrends of the 21st century. Besides offering a multitude of controversially discussed opportunities for entertainment and social interaction, there is reasonable concern about health issues caused by the absence of physical activity among activities linked to gaming and streaming. Objective: The aim of this study is to compare the water balance of recreational gamers with and those without compression stockings during a gaming event. Methods: We measured body composition and water balance with 8-electrode bioelectrical impedance analysis among 46 recreational gamers with an average age of 27.1 (SD 6.5) years (5/46, 11% women and 41/46, 89% men) before and after 24 hours at a gaming event. Of the 46 gamers, 23 (50%) gamers wore compression stockings for the duration of the study. Results: Our study shows that prolonged gaming and associated behaviors during a 24-hour time frame lead to an increase in total body water (+0.76 L; P<.001) and a decrease of phase angle in the lower extremities (−0.47°; P<.001) but not in the upper extremities (+0.09°; P=.80), when no compression is used. Gamers using compression socks did not show any significant negative effects on their body composition. Conclusions: Prolonged gaming and streaming are serious risk factors for diseases associated with water retention in the legs, and these risks can be measured by bioelectrical impedance and reduced by wearing compression stockings. We conclude that these findings should be discussed and replicated in larger studies and that there is a considerably large market for compression stockings among gamers and live streamers. Trial Registration: