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Muscle and joint forces
Published in Paul Grimshaw, Michael Cole, Adrian Burden, Neil Fowler, Instant Notes in Sport and Exercise Biomechanics, 2019
In dynamics we utilise the acceleration approach to solve problems. Also, remember from Figure D1.1 that inverse dynamics is the computation of muscle and joint forces from kinematics (displacement, velocity and acceleration). Hence, the first and second conditions of equilibrium, which we used for the statics calculations, are now represented as the following dynamic equations.
Motion Sensors in Osteoarthritis: Prospects and Issues
Published in Daniel Tze Huei Lai, Rezaul Begg, Marimuthu Palaniswami, Healthcare Sensor Networks, 2016
A completely different application of accelerometry—that is, activity monitoring—is discussed in the last section of this chapter. Interestingly, accelerometers have another potentially powerful application in human movement analysis. One of the more problematic aspects of camera-based motion analysis, utilizing inverse dynamics to estimate net joint moments (such as the KAM), is the need for body segment acceleration estimates. In marker-based motion analysis systems, these must be derived by double differentiation of segment position, an inherently noisy process. Therefore, accelerometers, which derive this quantity directly, should have a ready advantage for inverse dynamics. However, while the necessary procedures have been published (van den Bogert, Read, and Nigg 1996), this capacity has other practical difficulties (such as the need for multiple accelerometers per body segment) and therefore has rarely been exploited.
Paediatric Biomechanical Modelling Techniques
Published in Mark De Ste Croix, Thomas Korff, Paediatric Biomechanics and Motor Control, 2013
Inverse dynamics is a technique that estimates muscular torques from kinematic and kinetic measures. Kinematic measures include positions, velocities and accelerations of joints and segmental centres of mass. Positional data are typically obtained from motion capture systems or potentiometers and can be mathematically differentiated with respect to time taken to derive velocities and accelerations. Kinetic data used for inverse dynamics are commonly obtained from reaction forces that act on the human body. Measurement devices that allow us to measure reaction forces (e.g. force platforms or force pedals) are typically equipped with force transducers based on piezo-electric or strain gauge technology. Such force transducers measure an electrical charge in response to applied loads, which allows us to make inferences about the reaction forces applied to the human body.
Full body musculoskeletal model for simulations of gait in persons with transtibial amputation
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2023
Andrea M. Willson, Anthony J. Anderson, Chris A. Richburg, Brittney C. Muir, Joseph Czerniecki, Katherine M. Steele, Patrick M. Aubin
There were some limitations to the current functionality of this model. As described previously, the model’s muscle parameters were unaltered from healthy estimates, but individuals with lower-limb amputation exhibit muscle weakness heterogeneously in a variety of muscle groups. Furthermore, this generic amputee model was not analyzed using any running-style prosthetic feet, such as the Flex-Foot Cheetah (Össur Americas, Inc., California USA). Some research has shown that modeling prosthetic ankles as pin joints can be inaccurate and sensitive to marker placement (Fey et al. 2013; Rigney et al. 2016). Although some feet do have a physical pin joint, such as the College Park Venture foot used here, other researchers will need to consider how the model’s ankle pin joint could affect their results, and potentially alter the model for their specific purposes. Additionally, the model in its present form could not be used for forward simulations because the specific energy storage and return characteristics of the foot have not been modeled. Rather, this model generalizes the dynamics of the foot such that inverse dynamics and SO procedures are now available to all researchers of amputee gait.
The impact of anatomical uncertainties on the predictions of a musculoskeletal hand model – a sensitivity study
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2022
Maximilian Melzner, Franz Süß, Sebastian Dendorfer
However, some limitations of this research need to be noted. The comparison of experimentally gained and numerically determined muscle activities introduces crosstalk, which is associated with the measurement of EMG signals (Konrad 2005). The kinematic inaccuracies that inevitably occur during the measurement can also impact model predictions (Myers et al. 2015). In combination with the inverse dynamic, these kinematic inaccuracies can cause unrealistic joint torques approach according to Bailly et al. (2021). In addition, due to the time-independent nature of the static optimization, an inverse dynamic calculation prevents the activation dynamics from being taken into account. Both limitations can be circumvented by the forward dynamic approach. Another limitation of the used inverse dynamics approach is the impossibility of any direct kind of motion prediction.
Numerical optimization method for estimating the individual musculo-tendon forces for ergonomic assessment
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2020
Olfa Jemaa, Sami Bennour, David Daney, Lotfi Romdhane
Musculoskeletal disorders (MSDs) are injuries of the human musculoskeletal system. Occupational diseases represent major problem in the current industry affecting the operator heath, especially the joints and muscles of the upper limb (Zakaria et al. 2002). For determining the risk of MSDs and improving the ergonomics of the workplace, one of the important indicators is to analyze the musculo-tendon forces developed by workers. Since direct measurements of forces are difficult, several indirect methods are developed (Buchanan et al. 2004). For example, one approach is based on an estimation of the forces from the recording of electrical activity. Another method, inverse dynamics followed by static optimization, uses motion capture data as the only input for the estimation of the muscle forces (Cahouet et al. 2002). This method is often used, since the experimental acquisition of kinematic data is possible for most movements. Inverse method followed by static optimization has three main parts: development of a biomechanical model, calculation of joint torques and development of static optimization problem. In this paper, we have developed a static optimization problem with several constraints for estimating the musculo-tendon forces of the human upper limb, which could be used to assist ergonomists to better understand the risk of MSDs. The main advantage of this study is the evaluation of several objective functions by examining their analytical results.