Publications by authors named "M E Mononen"
Site-specific differences in the compressive properties of tibiofemoral joint articular cartilage are well-documented, while exploration of tensile and frictional properties in humans remains limited. Thus, this study aimed to characterize and compare the tensile, compressive and frictional properties of articular cartilage across different sites of the tibiofemoral joint, and to establish relationships between these properties and cartilage degeneration. We cut human tibiofemoral joint (N = 5) cartilage surfaces into tensile testing samples (n = 155) and osteochondral plugs (n = 40) to determine the tensile, friction and compressive properties, as well as OARSI grades.
View Article and Find Full Text PDFArticle Synopsis
- The dataset includes motion capture, inertial measurement unit data, and sagittal-plane video from 51 healthy participants walking at three speeds (slow, comfortable, fast) with around 60 trials each.
- It contains detailed data such as ground reaction forces from force plates, 3D trajectories from motion capture markers, and accelerometer readings from lower limbs and pelvis, alongside 2D keypoint trajectories analyzed through the OpenPose algorithm.
- The dataset also includes participant demographics and anatomical measurements, making it useful for musculoskeletal modeling, kinematics, and kinetics analysis, as well as for comparing data across different capture methods.
Background: Interstitial lung diseases (ILD) include a wide range of diseases impacting lung parenchyma and leading to fibrosis and architectural distortion. Chronic cough and dyspnea are common symptoms which affect the quality of life (QoL) in ILD patients. The mechanisms of cough in ILD patients are still unknown.
View Article and Find Full Text PDFPurpose: Estimating loading of the knee joint may be helpful in managing degenerative joint diseases. Contemporary methods to estimate loading involve calculating knee joint contact forces using musculoskeletal modeling and simulation from motion capture (MOCAP) data, which must be collected in a specialized environment and analyzed by a trained expert. To make the estimation of knee joint loading more accessible, simple input predictors should be used for predicting knee joint loading using artificial neural networks.
View Article and Find Full Text PDFArticle Synopsis
- * The study analyzed data from 115 obese individuals and found that predictions of cartilage degeneration were more accurate for the medial compartment of the knee compared to the lateral compartment.
- * Results indicated that using personalized joint geometry improved the accuracy of OA predictions more significantly than tailoring gait data, emphasizing the importance of individual characteristics in understanding knee OA.