Foot–ground contact modeling within human gait simulations: from Kelvin–Voigt to hyper-volumetric models

The final publication is available at Springer via http://dx.doi.org/10.1007/s11044-015-9467-6This study describes the development of a multibody foot–ground contact model consisting of spherical volumetric models for the surfaces of the foot. The developed model is two-dimensional and consists of two segments, the hind-foot, mid-foot, and fore-foot as one rigid body and the phalanges collectively as the second rigid body. The model has four degrees of freedom: ankle x and y, foot orientation, and metatarsal-phalangeal joint angle. Three different types of contact elements are targeted: Kelvin–Voigt, linear volumetric, and hyper-volumetric. The models are kinematically driven at the ankle and the metatarsal joints, and simulated horizontal and vertical ground reaction forces as well as center of pressure location are compared against experimental quantities acquired from barefoot measurements during a human gait cycle. Parameter identification is performed for finding optimal contact parameters and locations of the contact elements. The hyper-volumetric foot–ground contact model was found to be a suitable choice for foot/ground interaction modeling within human gait simulations; this model showed 75 % and 62 % improvement on the matching quality over the point contact and linear volumetric models, respectively.Natural Sciences and Engineering Research Council of Canada (NSERC

Optimal Control and Multibody Dynamic Modelling of Human Musculoskeletal Systems

Musculoskeletal dynamics is a branch of biomechanics that takes advantage of interdisciplinary models to describe the relation between muscle actuators and the corresponding motions of the human body. Muscle forces play a principal role in musculoskeletal dynamics. Unfortunately, these forces cannot be measured non-invasively. Measuring surface EMGs as a non-invasive technique is recognized as a surrogate to invasive muscle force measurement; however, these signals do not reflect the muscle forces accurately. Instead of measurement, mathematical modelling of the musculoskeletal dynamics is a well established tool to simulate, predict and analyse human movements. Computer simulations have been used to estimate a variety of variables that are difficult or impossible to measure directly, such as joint reaction forces, muscle forces, metabolic energy consumption, and muscle recruitment patterns. Musculoskeletal dynamic simulations can be divided into two branches: inverse and forward dynamics. Inverse dynamics is the approach in which net joint moments and/or muscle forces are calculated given the measured or specified kinematics. It is the most popular simulation technique used to study human musculoskeletal dynamics. The major disadvantage of inverse dynamics is that it is not predictive and can rarely be used in the cause-effect interpretations. In contrast with inverse dynamics, forward dynamics can be used to determine the human body movement when it is driven by known muscle forces. The musculoskeletal system (MSS) is dynamically under-determinate, i.e., the number of muscles is more than the degrees of freedom (dof) of the system. This redundancy will lead to infinite solutions of muscle force sets, which implies that there are infinite ways of recruiting different muscles for a specific motion. Therefore, there needs to be an extra criterion in order to resolve this issue. Optimization has been widely used for solving the redundancy of the force-sharing problem. Optimization is considered as the missing consideration in the dynamics of the MSS such that, once appended to the under-determinate problem, \human-like" movements will be acquired. \Human-like" implies that the human body tends to minimize a criterion during a movement, e.g., muscle fatigue or metabolic energy. It is commonly accepted that using those criteria, within the optimization necessary in the forward dynamic simulations, leads to a reasonable representation of real human motions. In this thesis, optimal control and forward dynamic simulation of human musculoskeletal systems are targeted. Forward dynamics requires integration of the differential equations of motion of the system, which takes a considerable time, especially within an optimization framework. Therefore, computationally efficient models are required. Musculoskeletal models in this thesis are implemented in the symbolic multibody package MapleSim that uses Maple as the leverage. MapleSim generates the equations of motion governing a multibody system automatically using linear graph theory. These equations will be simplified and highly optimized for further simulations taking advantage of symbolic techniques in Maple. The output codes are the best form for the equations to be applied in optimization-based simulation fields, such as the research area of this thesis. The specific objectives of this thesis were to develop frameworks for such predictive simulations and validate the estimations. Simulating human gait motion is set as the end goal of this research. To successfully achieve that, several intermediate steps are taken prior to gait modelling. One big step was to choose an efficient strategy to solve the optimal control and muscle redundancy problems. The optimal control techniques are benchmarked on simpler models, such as forearm flexion/extension, to study the efficacy of the proposed approaches more easily. Another major step to modelling gait is to create a high-fidelity foot-ground contact model. The foot contact model in this thesis is based on a nonlinear volumetric approach, which is able to generate the experimental ground reaction forces more effectively than the previously used models. Although the proposed models and approaches showed strong potential and capability, there is still room for improvement in both modelling and validation aspects. These cutting-edge future works can be followed by any researcher working in the optimal control and forward dynamic modelling of human musculoskeletal systems.1 yea

Muscle Synergy Analysis in Transtibial Amputee during Ramp Ascending Activity

In developed countries, the highest number of amputees are elderly with transtibial amputation. Walking on inclined surfaces is difficult for amputees due to loss of muscle volume and strength thereby transtibial amputees (TA) rely on the intact limb to maintain stability. The aim of this study was to use the concatenated non-negative matrix factorization (CNMF) technique to calculate muscle synergy components and compare the difference in muscle synergies and their associated activation profiles in the healthy and amputee groups during ramp ascending (RA) activity. Healthy subjects' dominant leg and amputee's intact leg (IL) were considered for recording surface electromyography (sEMG). The muscle synergies comparison showed a reasonable correlation between the healthy and amputee groups. This suggests the central nervous system (CNS) activates the same group of muscles synergistically. However, the activation coefficient profile (C) results indicated statistically significant difference (p <; 0.05) in some parts of the gait cycle (GC) in healthy and amputee groups. The difference exhibited in activation profiles of amputee's IL could be due to the instability of the prosthetic leg during the GC which resulted in alteration of the IL muscles activations. This information will be useful in rehabilitation and in the future development of prosthetic devices by using the IL muscles information to control the prostheses

Do Muscle Synergies Improve Optimization Prediction of Muscle Activations During Gait?

[Abstract]: Determination of muscle forces during motion can help to understand motor control, assess pathological movement, diagnose neuromuscular disorders, or estimate joint loads. Difficulty of in vivo measurement made computational analysis become a common alternative in which, as several muscles serve each degree of freedom, the muscle redundancy problem must be solved. Unlike static optimization (SO), synergy optimization (SynO) couples muscle activations across all time frames, thereby altering estimated muscle co-contraction. This study explores whether the use of a muscle synergy structure within an SO framework improves prediction of muscle activations during walking. A motion/force/electromyography (EMG) gait analysis was performed on five healthy subjects. A musculoskeletal model of the right leg actuated by 43 Hill-type muscles was scaled to each subject and used to calculate joint moments, muscle–tendon kinematics, and moment arms. Muscle activations were then estimated using SynO with two to six synergies and traditional SO, and these estimates were compared with EMG measurements. Synergy optimization neither improved SO prediction of experimental activation patterns nor provided SO exact matching of joint moments. Finally, synergy analysis was performed on SO estimated activations, being found that the reconstructed activations produced poor matching of experimental activations and joint moments. As conclusion, it can be said that, although SynO did not improve prediction of muscle activations during gait, its reduced dimensional control space could be beneficial for applications such as functional electrical stimulation or motion control and prediction.Ministerio de Ciencia, Innovación y Universidades; PGC2018-095145-B-I0

THE EFFECTS OF CONSTRAINING OPENSIM INVERSE KINEMATICS TO A BONE PIN MARKER DEFINED RANGE

The aim of this study was to apply bone pin kinematic constraints to an OpenSim model to determine differences in knee joint kinematics and kinetics beween the constrained and unconstrained solutions. In vivo data from healthy, anterior cruciate ligament deficient and reoonstructed patients completing a forward jump lunge were combined with bone pin data from a past study to redefine ranges that the knee degrees of freedom were constrained to. Differences between the constrained and unconstrained solutions existed for all participants at various points of the jump lunge movement, especially at the time of impact. Soft tissue artifact was most apparent in transverse plane translations. In conclusion, musculoskeletal modelling based solely on surface marker positions is inherently affected by soft tissue artifact and thus, results from these analyses should be interpreted with caution

Changes in synergy of transtibial amputee during gait: A pilot study

The number of lower limb amputations is increasing significantly in developed countries. The knowledge of muscle synergy in subjects with loss of muscles could help to understand the general neural strategy underlying muscle coordination in walking. The aim of this study was to investigate the differences in healthy subject's dominant leg, amputee's intact leg (IL) and the amputee's prosthetic leg (PL) muscles using synergy analysis. Concatenated non-negative matrix factorization (CNMF) was performed to divide the surface electromyography (sEMG) data obtained from 6 upper knee and 4 shank muscles into muscle synergy (S) and activation coefficient profile (C) during walking. The difference in S showed low to high correlations inter-subjectively. The high correlation suggests that the central nervous system (CNS) activates the same groups of muscles synergistically. Amputee's muscle alterations due to inadequate proprioceptive feedback, weight bearing deficiency in PL and prosthesis type could lead to a low correlation in S between groups. The C showed to be statistically significantly different in some regions of the gait cycle (GC). These findings could provide valuable information for rehabilitation purposes and development of a synergy-based controller from sEMG for future generations of prostheses

Estimation of Maximum Finger Tapping Frequency Using Musculoskeletal Dynamic Simulations

A model for forward dynamic simulation of the rapid tapping motion of an index finger is presented. The finger model was actuated by two muscle groups: one flexor and one extensor. The goal of this analysis was to estimate the maximum tapping frequency that the index finger can achieve using forward dynamics simulations. To achieve this goal, each muscle excitation signal was parameterized by a seventh-order Fourier series as a function of time. Simulations found that the maximum tapping frequency was 6 Hz, which is reasonably close to the experimental data. Amplitude attenuation (37% at 6 Hz) due to excitation/activation filtering, as well as the inability of muscles to produce enough force at high contractile velocities, are factors that prevent the finger from moving at higher frequencies. Musculoskeletal models have the potential to shed light on these restricting mechanisms and help to better understand human capabilities in motion production

Computational evaluation of psoas muscle influence on walking function following internal hemipelvectomy with reconstruction

An emerging option for internal hemipelvectomy surgery is custom prosthesis reconstruction. This option typically recapitulates the resected pelvic bony anatomy with the goal of maximizing post-surgery walking function while minimizing recovery time. However, the current custom prosthesis design process does not account for the patient’s post-surgery prosthesis and bone loading patterns, nor can it predict how different surgical or rehabilitation decisions (e.g., retention or removal of the psoas muscle, strengthening the psoas) will affect prosthesis durability and post-surgery walking function. These factors may contribute to the high observed failure rate for custom pelvic prostheses, discouraging orthopedic oncologists from pursuing this valuable treatment option. One possibility for addressing this problem is to simulate the complex interaction between surgical and rehabilitation decisions, post-surgery walking function, and custom pelvic prosthesis design using patient-specific neuromusculoskeletal models. As a first step toward developing this capability, this study used a personalized neuromusculoskeletal model and direct collocation optimal control to predict the impact of ipsilateral psoas muscle strength on walking function following internal hemipelvectomy with custom prosthesis reconstruction. The influence of the psoas muscle was targeted since retention of this important muscle can be surgically demanding for certain tumors, requiring additional time in the operating room. The post-surgery walking predictions emulated the most common surgical scenario encountered at MD Anderson Cancer Center in Houston. Simulated post-surgery psoas strengths included 0% (removed), 50% (weakened), 100% (maintained), and 150% (strengthened) of the pre-surgery value. However, only the 100% and 150% cases successfully converged to a complete gait cycle. When post-surgery psoas strength was maintained, clinical gait features were predicted, including increased stance width, decreased stride length, and increased lumbar bending towards the operated side. Furthermore, when post-surgery psoas strength was increased, stance width and stride length returned to pre-surgery values. These results suggest that retention and strengthening of the psoas muscle on the operated side may be important for maximizing post-surgery walking function. If future studies can validate this computational approach using post-surgery experimental walking data, the approach may eventually influence surgical, rehabilitation, and custom prosthesis design decisions to meet the unique clinical needs of pelvic sarcoma patients.Peer ReviewedObjectius de Desenvolupament Sostenible::3 - Salut i BenestarPostprint (published version

The Impact of Different Self-Selected Walking Speeds on Muscle Synergies in Transfemoral Amputees during Transient-State Gait

Facing above-knee amputation poses a significant hurdle due to its profound impact on walking ability. To overcome this challenge, a complex adaptation strategy is necessary at the neuromuscular level to facilitate safe movement with a prosthesis. Prior research conducted on lower-limb amputees has shown a comparable amount of intricacy exhibited by the neurological system, regardless of the level of amputation and state of walking. This research investigated the differences in muscle synergies among individuals with unilateral transfemoral amputations during walking at three different speeds of transient-state gait. Surface electromyography was recorded from eleven male transfemoral amputees’ intact limbs (TFA), and the concatenated non-negative matrix factorization technique was used to identify muscle synergy components, synergy vectors (S), and activation coefficient profiles (C). Results showed varying levels of correlation across paired-speed comparisons in TFA, categorized as poor (S1), moderate (S3 and S4), and strong (S2). Statistically significant differences were observed in all activation coefficients except C3, particularly during the stance phase. This study can assist therapists in understanding muscle coordination in TFA during unsteady gait, contributing to rehabilitation programs for balance and mobility improvement, and designing myoelectric prosthetic systems to enhance their responsiveness to trips or falls