Modeling of human muscle and its deformation

There is a lack of volume preserving and reasonable deformation of human muscles during bones and joints movement in the field of digital orthopedics. A novel approach for modeling of human muscle and its deformation was put forward to effectively assist doctors in guiding patients to carry out rehabilitation exercises. Firstly, based on Magnetic Resonance Imaging (MRI) data, the generated slice images were used to extract the outer contour lines and then the corresponding contour lines and optimal matching points of the adjacent layer images were connected to construct the three-dimensional (3D) geometric models of the muscles; Secondly, the mapping relationship between parameters can be established through hierarchical definition of the muscle characteristics to realize the volume-preserving deformation of muscle; Finally, the movement of human joints can be realized based on the constraint range of joint movement, and the vector-valued dynamic fourth-order differential equation was proposed to make the characteristic curve dynamically simulate the process of muscle deformation, thereby forming the corresponding relationship between bone movement and muscle deformation. The effectiveness and feasibility of this method have been verified in our experiments with biceps brachii and triceps brachii as examples. The maximum volume errors of biceps brachii and triceps brachii during the deformation process were less than 0.6%, which can be ignored within a certain allowable error range, reflecting that the parametric method was used to realize the reasonable volume-preserving deformation of human muscle.

Estimation of the force-velocity properties of individual muscles from measurement of the combined plantarflexor properties

The force-velocity (F-V) properties of isolated muscles or muscle fibers have been well studied in humans and other animals. However, determining properties of individual muscles in vivo remains a challenge because muscles usually function within a synergistic group. Modeling has been used to estimate the properties of an individual muscle from the experimental measurement of the muscle group properties. While this approach can be valuable, the models and the associated predictions are difficult to validate. In this study, we measured the in situ F-V properties of the maximally activated kangaroo rat plantarflexor group and used two different assumptions and associated models to estimate the properties of the individual plantarflexors. The first model (Mdl1) assumed that the percent contributions of individual muscles to group force and power were based upon the muscles' cross-sectional area and were constant across the different isotonic loads applied to the muscle group. The second model (Mdl2) assumed that the F-V properties of the fibers within each muscle were identical, but because of differences in muscle architecture, the muscles' contributions to the group properties changed with isotonic load. We compared the two model predictions with independent estimates of the muscles' contributions based upon sonomicrometry measurements of muscle length. We found that predictions from Mdl2 were not significantly different from sonomicrometry-based estimates while those from Mdl1 were significantly different. The results of this study show that incorporating appropriate fiber properties and muscle architecture is necessary to parse the individual muscles' contributions to the group F-V properties.

Hierarchical modeling of force generation in cardiac muscle

Performing physiologically relevant simulations of the beating heart in clinical context requires to develop detailed models of the microscale force generation process. These models, however, may reveal difficult to implement in practice due to their high computational costs and complex calibration. We propose a hierarchy of three interconnected muscle contraction models-from the more refined to the more simplified-that are rigorously and systematically related to each other, offering a way to select, for a specific application, the model that yields a good trade-off between physiological fidelity, computational cost and calibration complexity. The three model families are compared to the same set of experimental data to systematically assess what physiological indicators can be reproduced or not and how these indicators constrain the model parameters. Finally, we discuss the applicability of these models for heart simulation.

Skeletal muscle mechanics, energetics and plasticity

The following papers by Richard Lieber (Skeletal Muscle as an Actuator), Thomas Roberts (Elastic Mechanisms and Muscle Function), Silvia Blemker (Skeletal Muscle has a Mind of its Own: a Computational Framework to Model the Complex Process of Muscle Adaptation) and Sabrina Lee (Muscle Properties of Spastic Muscle (Stroke and CP) are summaries of their representative contributions for the session on skeletal muscle mechanics, energetics and plasticity at the 2016 Biomechanics and Neural Control of Movement Conference (BANCOM 2016). Dr. Lieber revisits the topic of sarcomere length as a fundamental property of skeletal muscle contraction. Specifically, problems associated with sarcomere length non-uniformity and the role of sarcomerogenesis in diseases such as cerebral palsy are critically discussed. Dr. Roberts then makes us aware of the (often neglected) role of the passive tissues in muscles and discusses the properties of parallel elasticity and series elasticity, and their role in muscle function. Specifically, he identifies the merits of analyzing muscle deformations in three dimensions (rather than just two), because of the potential decoupling of the parallel elastic element length from the contractile element length, and reviews the associated implications for the architectural gear ratio of skeletal muscle contraction. Dr. Blemker then tackles muscle adaptation using a novel way of looking at adaptive processes and what might drive adaptation. She argues that cells do not have pre-programmed behaviors that are controlled by the nervous system. Rather, the adaptive responses of muscle fibers are determined by sub-cellular signaling pathways that are affected by mechanical and biochemical stimuli; an exciting framework with lots of potential. Finally, Dr. Lee takes on the challenging task of determining human muscle properties in vivo. She identifies the dilemma of how we can demonstrate the effectiveness of a treatment, specifically in cases of muscle spasticity following stroke or in children with cerebral palsy. She then discusses the merits of ultrasound based elastography, and the clinical possibilities this technique might hold. Overall, we are treated to a vast array of basic and clinical problems in skeletal muscle mechanics and physiology, with some solutions, and many suggestions for future research.

Equivalent linear damping characterization in linear and nonlinear force-stiffness muscle models

In the current research, the muscle equivalent linear damping coefficient which is introduced as the force-velocity relation in a muscle model and the corresponding time constant are investigated. In order to reach this goal, a 1D skeletal muscle model was used. Two characterizations of this model using a linear force-stiffness relationship (Hill-type model) and a nonlinear one have been implemented. The OpenSim platform was used for verification of the model. The isometric activation has been used for the simulation. The equivalent linear damping and the time constant of each model were extracted by using the results obtained from the simulation. The results provide a better insight into the characteristics of each model. It is found that the nonlinear models had a response rate closer to the reality compared to the Hill-type models.

Physiologically corrected coupled motion during gait analysis using a model-based approach

Gait analysis is used in daily clinics for patients' evaluation and follow-up. Stereophotogrammetric devices are the most used tool to perform these analyses. Although these devices are accurate results must be analyzed carefully due to relatively poor reproducibility. One of the major issues is related to skin displacement artifacts. Motion representation is recognized reliable for the main plane of motion displacement, but secondary motions, or combined, are less reliable because of the above artifacts. Model-based approach (MBA) combining accurate joint kinematics and motion data was previously developed based on a double-step registration method. This study presents an extensive validation of this MBA method by comparing results with a conventional motion representation model. Thirty five healthy subjects participated to this study. Gait motion data were obtained from a stereophotogrammetric system. Plug-in Gait model (PiG) and MBA were applied to raw data, results were then compared. Range-of-motion, were computed for pelvis, hip, knee and ankle joints. Differences between PiG and MBA were then computed. Paired-sample t-tests were used to compare both methods. Normalized root-mean square errors were also computed. Shapes of the curves were compared using coefficient of multiple correlations. The MBA and PiG approaches shows similar results for the main plane of motion displacement but statistically significative discrepancies appear for the combined motions. MBA appear to be usable in applications (such as musculoskeletal modeling) requesting better approximations of the joints-of-interest thanks to the integration of validated joint mechanisms.

Identification of the neural component of torque during manually-applied spasticity assessments in children with cerebral palsy

Clinical assessment of spasticity is compromised by the difficulty to distinguish neural from non-neural components of increased joint torque. Quantifying the contributions of each of these components is crucial to optimize the selection of anti-spasticity treatments such as botulinum toxin (BTX). The aim of this study was to compare different biomechanical parameters that quantify the neural contribution to ankle joint torque measured during manually-applied passive stretches to the gastrocsoleus in children with spastic cerebral palsy (CP). The gastrocsoleus of 53 children with CP (10.9 ± 3.7 y; females n = 14; bilateral/unilateral involvement n = 28/25; Gross Motor Functional Classification Score I-IV) and 10 age-matched typically developing (TD) children were assessed using a manually-applied, instrumented spasticity assessment. Joint angle characteristics, root mean square electromyography and joint torque were simultaneously recorded during passive stretches at increasing velocities. From the CP cohort, 10 muscles were re-assessed for between-session reliability and 19 muscles were re-assessed 6 weeks post-BTX. A parameter related to mechanical work, containing both neural and non-neural components, was compared to newly developed parameters that were based on the modeling of passive stiffness and viscosity. The difference between modeled and measured response provided a quantification of the neural component. Both types of parameters were reliable (ICC > 0.95) and distinguished TD from spastic muscles (p < 0.001). However, only the newly developed parameters significantly decreased post-BTX (p = 0.012). Identifying the neural and non-neural contributions to increased joint torque allows for the development of individually tailored tone management.