1,721,027 research outputs found
Real-time estimation of knee joint contact forces during walking using OpenSim and a calibrated EMG-driven neuromusculoskeletal model
No full textAssessment of a magneto-inertial sensors driven inverse kinematics approach for the estimate of multibody joint kinematics
No full text
A new method for estimating muscle-tendon parameters for subject specific musculoskeletal models of the lower limb
No full textAn OpenSim plugin to estimate joint angles using inverse kinematics and inertial measurement units
No full textEstimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique.
Full text linkA challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par
MRI-based parallel mechanisms to model subject-specific joint kinematics
No full textSubject-specific musculoskeletal (MSK) computer models can estimate muscle and joint articular forces, enabling the identification of mechanical factors causing joint injury or disease. MSK models include models of skeletal anatomy and joint kinematics that can be created in OpenSim [1]. These models are generic and undergo simple linear scaling to a subject using markers from motion analysis. However, generic scaled MSK models produce less accurate estimates of measured knee articular forces compared to those that are subject-specific [2]. Thus, methods are needed to readily create subject-specific models. Passive tibiofemoral (TFJ), patellofemoral (PFJ) and talocrural (TAJ) kinematics measured in cadavers are well predicted using 3D parallel mechanisms [3,4]. These models integrate the cadaver’s measured bone, ligament and tendon geometries to constrain the joints’ degrees of freedom (DOFs). Using TFJ flexion angle as input, TFJ and PFJ models estimate the tibia’s and patella’s remaining Flex-Extension (FE), Abd-Adduction (AA), Int-External (IE) rotations and Ant-Posterior (AP), Prox-Distal (PD) and Med-Lateral (ML) translations. Similarly, TAJ models use talus flexion angle to estimate kinematics from the other TAJ DOFs. However, these models have only been used in cadavers where the kinematics were accurately measured and used to tune the models geometrical parameters. We aimed to use MRI images of in vivo lower limb bones, cartilages and ligaments to create models’ geometrical parameters. Using previously described mechanisms [3,4] we estimated subject-specific kinematics for use in OpenSim. However, without measured kinematics to tune the model, we created specialized algorithms to solve the mechanisms and then compared the results with those from cadaveric studies
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim
Full text linkReal-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time
- …
