A review of simulation methods for human movement dynamics with emphasis on gait

Ezati, Mahdokht; Ghannadi, Borna; McPhee, John

doi:10.1007/s11044-019-09685-1

Cited by 54 publications

(41 citation statements)

References 118 publications

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“…To our knowledge, no studies have yet predicted three-dimensional full-cycle crutch walking patterns using a full-body model. Moreover, there are few studies where novel gait motions are predicted without tracking any experimental data [39].…”

Section: Discussionmentioning

confidence: 99%

“…For the different walking patterns, the same formulation (cost function and constraints) could converge or not depending on the initial guess. Since this is a common limitation in direct collocation methods, as the convergence relies on having good initial guesses [39], more research is needed on how to objectively define this initial guess. Moreover, the obtained solutions could be local minima, because for different combinations of IPOPT and mesh tolerances that we tested (for the four-point nonalternating gait pattern), each cost function converged to different solutions.…”

Section: Discussionmentioning

confidence: 99%

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Prediction of three-dimensional crutch walking patterns using a torque-driven model

et al. 2020

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Computational prediction of 3D crutch-assisted walking patterns is a challenging problem that could be applied to study different biomechanical aspects of crutch walking in virtual subjects, to assist physiotherapists to choose the optimal crutch walking pattern for a specific subject, and to help in the design and control of exoskeletons, when crutches are needed for balance. The aim of this work is to generate a method to predict three-dimensional crutch-assisted walking motions following different patterns without tracking any experimental data. To achieve this goal, we collected gait data from a healthy subject performing a four-point non-alternating crutch walking pattern, and developed a 3D torque-driven full-body model of the subject including the crutches and foot-and crutch-ground contact models. First, we developed a predictive (i.e., no tracking of experimental data) optimal control problem formulation to predict crutch walking cycles following the same pattern as the experimental data collected, using different cost functions. To reduce errors with respect to reference data, a cost function combining minimisation terms of angular momentum, mechanical power, joint jerk and torque change was chosen. Then, the problem formulation was adapted to handle different foot-and crutch-ground conditions to make it capable of predicting three new crutch walking patterns, one of them at different speeds. A key aspect of our algorithm is that having ground reactions as additional controls allows to define phases inside the cycle without the need of formulating a multiple-phase problem, thus facilitating the definition of different crutch walking patterns.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Prediction of three-dimensional crutch walking patterns using a torque-driven model

et al. 2020

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“…Inverse dynamics analysis (IDA), which is derived from Newton-Euler Equations [60,[64][65][66][67][68], aims to calculate unknown kinetic information (the net joint forces and moments) from measured kinematic information (e.g., position, velocities and accelerations of joints) and measured kinetic information (e.g., ground reaction forces). As illustrated in Figure 5, given joint locations…”

Section: Formulating Musculoskeletal Kinetic Featuresmentioning

confidence: 99%

“…To balance the training of generator and discriminator for decent output, this work investigates the following strategies: (1) Application of Wasserstein distance to formulate the loss function [46,112]. (2) Application of visible neural network by incorporating the biomechanics theory (inverse dynamics and the transient dynamics simulation of human body [60,68]) in the formulation of generator and discriminator. The neural network is personalized using boundary and initial conditions of human dynamics.…”

Section: Movement Choreography Based On Visible Ganmentioning

confidence: 99%

VIGOR: A Versatile, Individualized and Generative ORchestrator to Motivate the Movement of the People with Limited Mobility

Yu¹,

Wu²,

Ledesma³

et al. 2022

Smart and Pervasive Healthcare

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Physical inactivity is a major national concern, particularly among individuals with chronic conditions and/or disabilities. There is an urgent need to devise practical and innovative fitness methods, designed and grounded in physical, psychological and social considerations that will effectively promote physical fitness participation among individuals of all age groups with chronic health condition(s) and/or disabilities. This research is dedicated to achieving Versatile, Individualized, and Generative ORchestrator (VIGOR) to motivate the movement of the people with limited mobility. Tai-Chi is a traditional mind–body wellness and healing art, and its clinical benefits have been well documented. This work presents a Tai-Chi based VIGOR under development. Through the use of Helping, Pushing and Coaching (HPC) functions by following Tai-Chi kinematics, the VIGOR system is designed to make engagement in physical activity an affordable, individually engaging, and enjoyable experience for individuals who live with mobility due to disease or injury. VIGOR consists of the following major modules: (1) seamless human-machine interaction based on the acquisition, transmission, and reconstruction of 4D data (XYZ plus somatosensory) using affordable I/O instruments such as Kinect, Sensor and Tactile actuator, and active-orthosis/exoskeleton; (2) processing and normalization of kinetic data; (3) Identification and grading of kinetics in real time; (4) adaptive virtual limb generation and its reconstruction on virtual reality (VR) or active-orthosis/exoskeleton; and (5) individualized physical activity choreography (i.e., creative movement design). Aiming at developing a deep-learning-enabled rehab and fitness modality through infusing the domain knowledge (physical therapy, medical anthropology, psychology, electrical engineering, bio-mechanics, and athletic aesthetics) into deep neural network, this work is transformative in that the technology can be applied to the broad research areas of intelligent systems, human-computer interaction, and cyber-physical human systems. The resulting VIGOR has significant potentials as both rehabilitative and fitness modalities and can be adapted to other movement modalities and chronic medical conditions (e.g., yoga and balance exercise; fibromyalgia, multiple sclerosis, Parkinson disease).

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“…In recent years, interest in musculoskeletal simulation to reconstruct and predict human movements has been growing 1 . Motion reconstruction based on captured data yields insight into further variables of interest, e.g.…”

Section: Introductionmentioning

confidence: 99%

Efficient trajectory optimization for curved running using a 3D musculoskeletal model with implicit dynamics

Nitschke

Dorschky

Heinrich

et al. 2020

Sci Rep

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Trajectory optimization with musculoskeletal models can be used to reconstruct measured movements and to predict changes in movements in response to environmental changes. It enables an exhaustive analysis of joint angles, joint moments, ground reaction forces, and muscle forces, among others. However, its application is still limited to simplified problems in two dimensional space or straight motions. The simulation of movements with directional changes, e.g. curved running, requires detailed three dimensional models which lead to a high-dimensional solution space. We extended a full-body three dimensional musculoskeletal model to be specialized for running with directional changes. Model dynamics were implemented implicitly and trajectory optimization problems were solved with direct collocation to enable efficient computation. Standing, straight running, and curved running were simulated starting from a random initial guess to confirm the capabilities of our model and approach: efficacy, tracking and predictive power. Altogether the simulations required 1 h 17 min and corresponded well to the reference data. The prediction of curved running using straight running as tracking data revealed the necessity of avoiding interpenetration of body segments. In summary, the proposed formulation is able to efficiently predict a new motion task while preserving dynamic consistency. Hence, labor-intensive and thus costly experimental studies could be replaced by simulations for movement analysis and virtual product design.

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A review of simulation methods for human movement dynamics with emphasis on gait

Cited by 54 publications

References 118 publications

Prediction of three-dimensional crutch walking patterns using a torque-driven model

Prediction of three-dimensional crutch walking patterns using a torque-driven model

VIGOR: A Versatile, Individualized and Generative ORchestrator to Motivate the Movement of the People with Limited Mobility

Efficient trajectory optimization for curved running using a 3D musculoskeletal model with implicit dynamics

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