A myoelectric digital twin for fast and realistic modelling in deep learning

Muscle electrophysiology has emerged as a powerful tool to drive human machine interfaces, with many new recent applications outside the traditional clinical domains, such as robotics and virtual reality. However, more sophisticated, functional, and robust decoding algorithms are required to meet the fine control requirements of these applications. Deep learning has shown high potential in meeting these demands, but requires a large amount of high-quality annotated data, which is expensive and time-consuming to acquire. Data augmentation using simulations, a strategy applied in other deep learning applications, has never been attempted in electromyography due to the absence of computationally efficient models. We introduce a concept of Myoelectric Digital Twin - highly realistic and fast computational model tailored for the training of deep learning algorithms. It enables simulation of arbitrary large and perfectly annotated datasets of realistic electromyography signals, allowing new approaches to muscular signal decoding, accelerating the development of human-machine interfaces

Subject-specific Finite Element Models of the Human Knee for Transtibial Amputees to Analyze Tibial Cartilage Pressure for Gait, Cycling, and Elliptical Training

It is estimated that approximately 10-12% of the adult population suffers from osteoarthritis (OA), with long reaching burdens personally and socioeconomically. OA also causes mild discomfort to severe pain in those suffering from the disease. The incidence rate of OA for individuals with transtibial amputations is much than average in the tibiofemoral joint (TF). It is well understood that abnormal articular cartilage stress, whether that be magnitude or location, increases the risk of developing OA. Finite element (FE) simulations can predict stress in the TF joint, many studies throughout the years have validated the technology used for this purpose. This thesis is the first to successfully validate a procedure for creating subject-specific FE models for transtibial amputees to simulate the TF joint in gait, cycling and elliptical exercises. Maximum tibial cartilage pressure was extracted post-simulation and compared to historical data. The body weight normalized contact pressure on the tibial articular cartilage for the two amputee participants was larger in magnitude than the control participant in all but the medial compartment in cycling. Additionally, cycling exercise produced the smallest values of contact pressure with elliptical and gait producing similar max values but different areas of effect. The results from this thesis align with the body of work preceding it and further the goal of a FE model that predicts in-vivo articular cartilage stress in the TF joint. Future studies can further refine this methodology and create additional subject-specific models to allow for a statistical analysis of the observed differences to find if the results are significantly different. Refining the methodology could include investigating the full effect of the damping factor on contact pressure and exploring alternative methods of mesh generation

Subject-specific Human Knee FEA Models for Transtibial Amputees Vs Control Tibial Cartilage Pressure in Gait, Cycling and Elliptical Training

Millions of individuals around the globe are impacted by osteoarthritis, which is the prevailing type of arthritis. This condition arises as a result of gradual deterioration of the protective cartilage that safeguards the ends of the bones. This is especially true of transtibial amputees, who have a significantly higher incidence of osteoarthritis of the knee in their intact limb than non-amputees. Engaging in regular physical activity, managing weight effectively, and undergoing specific treatments can potentially slow down the advancement of the disease and enhance pain relief and joint function. Nevertheless, the relationship between the type of exercise and its impact on cartilage stress remains uncertain. In order to address this question, tibiofemoral finite element analysis (FEA) models were developed. The models incorporated more realistic material properties for cartilage, hexahedral elements, and non-linear springs for ligaments. To ensure their accuracy, the models were validated against experimental data obtained from cadaveric studies. The contact loads and flexion angles of two individuals with amputations and one individual without amputation, which were obtained in a previous study conducted at Cal Poly, were implemented in the FEA models for gait, cycling, and elliptical exercises. The FEA models were used to extract the maximum stress values experienced in the tibial contact areas, specifically in the medial and lateral compartments of the knee. In cycling, the normalized contact pressure on the tibial articular cartilage, relative to body weight, was generally higher for the two participants with amputations compared to the control participant, except for the medial compartment. Furthermore, when comparing different exercises, cycling resulted in the lowest contact pressure values, with elliptical and walking exercises producing similar maximum values. The findings indicated that individuals with amputations are at a greater risk of developing OA, regardless of the type of exercise performed. However, among the different exercises studied, cycling was found to exert the lowest levels of compression stress on the tibial cartilage

Development of a continuum mechanics model of passive skeletal muscle

Skeletal muscle force evaluation is difficult to implement in a clinical setting. Muscle force is typically assessed through either manual muscle testing, isokinetic/isometric dynamometry, or electromyography (EMG). Manual muscle testing is a subjective evaluation of a patient’s ability to move voluntarily against gravity and to resist force applied by an examiner. Muscle testing using dynamometers adds accuracy by quantifying functional mechanical output of a limb. However, like manual muscle testing, dynamometry only provides estimates of the joint moment. EMG quantifies neuromuscular activation signals of individual muscles, and is used to infer muscle function. Despite the abundance of work performed to determine the degree to which EMG signals and muscle forces are related, the basic problem remains that EMG cannot provide a quantitative measurement of muscle force. Intramuscular pressure (IMP), the pressure applied by muscle fibers on interstitial fluid, has been considered as a correlate for muscle force. Numerous studies have shown that an approximately linear relationship exists between IMP and muscle force. A microsensor has recently been developed that is accurate, biocompatible, and appropriately sized for clinical use. While muscle force and pressure have been shown to be correlates, IMP has been shown to be non-uniform within the muscle. As it would not be practicable to experimentally evaluate how IMP is distributed, computational modeling may provide the means to fully evaluate IMP generation in muscles of various shapes and operating conditions. The work presented in this dissertation focuses on the development and validation of computational models of passive skeletal muscle and the evaluation of their performance for prediction of IMP. A transversly isotropic, hyperelastic, and nearly incompressible model will be evaluated along with a poroelastic model

A computational neuromuscular model of the human upper airway with application to the study of obstructive sleep apnoea

Includes bibliographical references.Numerous challenges are faced in investigations aimed at developing a better understanding of the pathophysiology of obstructive sleep apnoea. The anatomy of the tongue and other upper airway tissues, and the ability to model their behaviour, is central to such investigations. In this thesis, details of the construction and development of a three-dimensional finite element model of soft tissues of the human upper airway, as well as a simplified fluid model of the airway, are provided. The anatomical data was obtained from the Visible Human Project, and its underlying micro-histological data describing tongue musculature were also extracted from the same source and incorporated into the model. An overview of the mathematical models used to describe tissue behaviour, both at a macro- and microscopic level, is given. Hyperelastic constitutive models were used to describe the material behaviour, and material incompressibility was accounted for. An active Hill three-element muscle model was used to represent the muscular tissue of the tongue. The neural stimulus for each muscle group to a priori unknown external forces was determined through the use of a genetic algorithm-based neural control model. The fundamental behaviour of the tongue under gravitational and breathing-induced loading is investigated. The response of the various muscles of the tongue to the complex loading developed during breathing is determined, with a particular focus being placed to that of the genioglossus. It is demonstrated that, when a time-dependent loading is applied to the tongue, the neural model is able to control the position of the tongue and produce a physiologically realistic response for the genioglossus. A comparison is then made to the response determined under quasi-static conditions using the pressure distribution extracted from computational fluid-dynamics results. An analytical model describing the time-dependent response of the components of the tongue musculature most active during oral breathing is developed and validated. It is then modified to simulate the activity of the tongue during sleep and under conditions relating to various possible neural and physiological pathologies. The retroglossal movement of the tongue resulting from the pathologies is quantified and their role in the potential to induce airway collapse is discussed

A novel musculoskeletal joint modelling for orthopaedic applications

This thesis was submitted for the degree of Docter of Philosophy and awarded by Brunel University.The objective of the work carried out in this thesis was to develop analytical and computational tools to model and investigate musculoskeletal human joints. It was recognised that the FEA was used by many researchers in modelling human musculoskeletal motion, loading and stresses. However the continuum mechanics played only a minor role in determining the articular joint motion, and its value was questionable. This is firstly due to the computational cost and secondly due to its impracticality for this application. On the other hand, there isn’t any suitable software for precise articular joint motion analysis to deal with the local joint stresses or non standard joints. The main requirement in orthopaedics field is to develop a modeller software (and its associated theories) to model anatomic joint as it is, without any simplification with respect to joint surface morphology and material properties of surrounding tissues. So that the proposed modeller can be used for evaluating and diagnosing different joint abnormalities but furthermore form the basis for performing implant insertion and analysis of the artificial joints. The work which is presented in this thesis is a new frame work and has been developed for human anatomic joint analysis which describes the joint in terms of its surface geometry and surrounding musculoskeletal tissues. In achieving such a framework several contributions were made to the 6DOF linear and nonlinear joint modelling, the mathematical definition of joint stiffness, tissue path finding and wrapping and the contact with collision analysis. In 6DOF linear joint modelling, the contribution is the development of joint stiffness and damping matrices. This modelling approach is suitable for the linear range of tissue stiffness and damping properties. This is the first of its kind and it gives a firm analytical basis for investigating joints with surrounding tissue and the cartilage. The 6DOF nonlinear joint modelling is a new scheme which is described for modelling the motion of multi bodies joined by non-linear stiffness and contact elements. The proposed method requires no matrix assembly for the stiffness and damping elements or mass elements. The novelty in the nonlinear modelling, relates to the overall algorithmic approach and handling local non-linearity by procedural means. The mathematical definition of joint stiffness is also a new proposal which is based on the mathematical definition of stiffness between two bodies. Based on the joint stiffness matrix properties, number of joint stiffness invariants was obtained analytically such as the centre of stiffness, the principal translational stiffnesses, and the principal rotational stiffnesses. In corresponding to these principal stiffnesses, their principal axes have been also obtained. Altogether, a joint is assessed by six principal axes and six principal stiffnesses and its centre of stiffness. These formulations are new and show that a joint can be described in terms of inherent stiffness properties. It is expected that these will be better in characterising a joint in comparison to laxity based characterisation. The development of tissue path finding and wrapping algorithms are also introduced as new approaches. The musculoskeletal tissue wrapping involves calculating the shortest distance between two points on a meshed surface. A new heuristic algorithm was proposed. The heuristic is based on minimising the accumulative divergence from the straight line between two points on the surface and the direction of travel on the surface (i.e. bone). In contact and collision based development, the novel algorithm has been proposed that detects possible colliding points on the motion trajectory by redefining the distance as a two dimensional measure along the velocity approach vector and perpendicular to this vector. The perpendicular distance determines if there are potentially colliding points, and the distance along the velocity determines how close they are. The closest pair among the potentially colliding points gives the “time to collision”. The algorithm can eliminate the “fly pass” situation where very close points may not collide because of the direction of their relative velocity. All these developed algorithms and modelling theories, have been encompassed in the developed prototype software in order to simulate the anatomic joint articulations through modelling formulations developed. The software platform provides a capability for analysing joints as 6DOF joints based on anatomic joint surfaces. The software is highly interactive and driven by well structured database, designed to be highly flexible for the future developments. Particularly, two case studies are carried out in this thesis in order to generate results relating to all the proposed elements of the study. The results obtained from the case studies show good agreement with previously published results or model based results obtained from Lifemod software, whenever comparison was possible. In some cases the comparison was not possible because there were no equivalent results; the results were supported by other indicators. The modelling based results were also supported by experiments performed in the Brunel Orthopaedic Research and Learning Centre

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018