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Articular human joint modelling
Copyright @ Cambridge University Press 2009.The work reported in this paper encapsulates the theories and algorithms developed to drive the core analysis modules of the software which has been developed to model a musculoskeletal structure of anatomic joints. Due to local bone surface and contact geometry based joint kinematics, newly developed algorithms make the proposed modeller different from currently available modellers. There are many modellers that are capable of modelling gross human body motion. Nevertheless, none of the available modellers offer complete elements of joint modelling. It appears that joint modelling is an extension of their core analysis capability, which, in every case, appears to be musculoskeletal motion dynamics. It is felt that an analysis framework that is focused on human joints would have significant benefit and potential to be used in many orthopaedic applications. The local mobility of joints has a significant influence in human motion analysis, in understanding of joint loading, tissue behaviour and contact forces. However, in order to develop a bone surface based joint modeller, there are a number of major problems, from tissue idealizations to surface geometry discretization and non-linear motion analysis. This paper presents the following: (a) The physical deformation of biological tissues as linear or non-linear viscoelastic deformation, based on spring-dashpot elements. (b) The linear dynamic multibody modelling, where the linear formulation is established for small motions and is particularly useful for calculating the equilibrium position of the joint. This model can also be used for finding small motion behaviour or loading under static conditions. It also has the potential of quantifying the joint laxity. (c) The non-linear dynamic multibody modelling, where a non-matrix and algorithmic formulation is presented. The approach allows handling complex material and geometrical nonlinearity easily. (d) Shortest path algorithms for calculating soft tissue line of action geometries. The developed algorithms are based on calculating minimum ‘surface mass’ and ‘surface covariance’. An improved version of the ‘surface covariance’ algorithm is described as ‘residual covariance’. The resulting path is used to establish the direction of forces and moments acting on joints. This information is needed for linear or non-linear treatment of the joint motion. (e) The final contribution of the paper is the treatment of the collision. In the virtual world, the difficulty in analysing bodies in motion arises due to body interpenetrations. The collision algorithm proposed in the paper involves finding the shortest projected ray from one body to the other. The projection of the body is determined by the resultant forces acting on it due to soft tissue connections under tension. This enables the calculation of collision condition of non-convex objects accurately. After the initial collision detection, the analysis involves attaching special springs (stiffness only normal to the surfaces) at the ‘potentially colliding points’ and motion of bodies is recalculated. The collision algorithm incorporates the rotation as well as translation. The algorithm continues until the joint equilibrium is achieved. Finally, the results obtained based on the software are compared with experimental results obtained using cadaveric joints
Musculoskeletal discipline science plan
Life sciences research in the musculoskeletal discipline must identify possible consequences of weightlessness on this system, understand the mechanisms of these effects, and develop effective and operationally practical countermeasures to protect crewmembers. The musculoskeletal system is highly plastic in that is possesses the inherent capability to adapt its structural and functional properties in accordance with the type and degree of stimuli imposed on it. Prolonged space travel is essentially a period of significant unloading of the musculoskeletal system. This results in adaptive responses in the structure and function of this system, placing it on the low end of a continuum from one of complete disuse to one of maximal use. There is a high probability that the musculoskeletal system is functionally impaired with increasing duration of weightlessness. The purpose of this Discipline Science Plan is to provide a conceptual strategy for NASA's Life Sciences division research and development activities in the area of musculoskeletal function. This document summarizes the current status of the program, outlines available knowledge, establishes goals and objectives, identifies science priorities, and defines research opportunities, which encompass critical questions in the subdiscipline areas (e.g., muscle, bone, and other musculoskeletal connective tissues). These science activities include ground-based and flight; basic, applied, and operational; and animal and human research and development. This document contains a general plan that will be used by both NASA Headquarters Program Offices and the field centers to review and plan basic, applied, and operational intramural and extramural research and development activities in this area
Cone beam CT of the musculoskeletal system : clinical applications
Objectives: The aim of this pictorial review is to illustrate the use of CBCT in a broad spectrum of musculoskeletal disorders and to compare its diagnostic merit with other imaging modalities, such as conventional radiography (CR), Multidetector Computed Tomography (MDCT) and Magnetic Resonance Imaging.
Background: Cone Beam Computed Tomography (CBCT) has been widely used for dental imaging for over two decades.
Discussion: Current CBCT equipment allows use for imaging of various musculoskeletal applications. Because of its low cost and relatively low irradiation, CBCT may have an emergent role in making a more precise diagnosis, assessment of local extent and follow-up of fractures and dislocations of small bones and joints. Due to its exquisite high spatial resolution, CBCT in combination with arthrography may be the preferred technique for detection and local staging of cartilage lesions in small joints. Evaluation of degenerative joint disorders may be facilitated by CBCT compared to CR, particularly in those anatomical areas in which there is much superposition of adjacent bony structures. The use of CBCT in evaluation of osteomyelitis is restricted to detection of sequestrum formation in chronic osteomyelitis. Miscellaneous applications include assessment of (symptomatic) variants, detection and characterization of tumour and tumour-like conditions of bone.
Teaching Points:
Review the spectrum of MSK disorders in which CBCT may be complementary to other imaging techniques.
Compare the advantages and drawbacks of CBCT compared to other imaging techniques.
Define the present and future role of CBCT in musculoskeletal imaging
Computational Models of Material Interfaces for the Study of Extracorporeal Shock Wave Therapy
Extracorporeal Shock Wave Therapy (ESWT) is a noninvasive treatment for a
variety of musculoskeletal ailments. A shock wave is generated in water and
then focused using an acoustic lens or reflector so the energy of the wave is
concentrated in a small treatment region where mechanical stimulation enhances
healing. In this work we have computationally investigated shock wave
propagation in ESWT by solving a Lagrangian form of the isentropic Euler
equations in the fluid and linear elasticity in the bone using high-resolution
finite volume methods. We solve a full three-dimensional system of equations
and use adaptive mesh refinement to concentrate grid cells near the propagating
shock. We can model complex bone geometries, the reflection and mode conversion
at interfaces, and the the propagation of the resulting shear stresses
generated within the bone. We discuss the validity of our simplified model and
present results validating this approach
Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions.
Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject's self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot-ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject's walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject's walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject's walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations
Assist-as-needed EMG-based control strategy for wearable powered assistive devices
Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)Robotic-based gait rehabilitation and assistance using Wearable Powered Assistive Devices (WPADs), such as orthosis and exoskeletons, has been growing in the rehabilitation area to recover and augment the motor function of neurologically impaired subjects. These WPADs should provide a personalized assistance, since physical condition and muscular fatigue modify from patient to patient. In this field, electromyography (EMG) signals have been used to control WPADs given their ability to infer the user’s motion intention. However, in cases of motor disability conditions, EMG signals present lower magnitudes when compared to EMG signals under healthy conditions. Thus, the use of WPADs managed by EMG signals may not have potential to provide the assistance that the patient requires.
The main goal of this dissertation aims the development of an Assisted-As-Needed (AAN) EMG-based control strategy for a future insertion in a Smart Active Orthotic System (SmartOs). To achieve this goal, the following elements were developed and validated: (i) an EMG system to acquire muscle activity signals from the most relevant muscles during the motion of the ankle joint; (ii) machine learning-based tool for ankle joint torque estimation to serve as reference in the AAN EMG-based control strategy; and (iii) a tool for real EMG-based torque estimation using Tibialis Anterior (TA) and Gastrocnemius Lateralis (GASL) muscles and real ankle joint angles.
EMG system showed satisfactory pattern correlations with a commercial system. The reference ankle joint torque was generated based on predicted reference ankle joint kinematics, walking speed information (from 1 to 4 km/h) and anthropometric data (body height from 1.51 m to 1.83 m and body mass from 52.0 kg to 83.7 kg), using five machine learning algorithms: Support Vector Regression (SVR), Random Forest (RF), Multilayer Perceptron (MLP), Long-Short Term Memory (LSTM) and Convolutional Neural Network (CNN). CNN provided the best performance, predicting the reference ankle joint torque with fitting curves ranging from 74.7 to 89.8 % and Normalized Root Mean Square Errors (NRMSEs) between 3.16 and 8.02 %. EMG-based torque estimation beneficiates of a higher number of muscles, since EMG data from TA and GASL are not enough to estimate the real ankle joint torque.A assistência e reabilitação robótica usando dispositivos de assistência ativos vestíveis (WPADs), como ortóteses e exosqueletos, tem crescido na área da reabilitação com o fim de recuperar e aumentar a função motora de sujeitos com alterações neurológicas. Estes dispositivos devem fornecer uma assistência personalizada, uma vez que a condição física e a fadiga muscular variam de paciente para paciente. Nesta área, sinais de eletromiografia (EMG) têm sido usados para controlar WPADs, dada a sua capacidade de inferir a intenção de movimento do utilizador. Contudo, em casos de deficiência motora, os sinais de EMG apresentam menor amplitude quando comparados com sinais de EMG em condições saudáveis e, portanto, o uso de WPADs geridos por sinais de EMG pode não oferecer a assistência que o paciente necessita.
O principal objetivo desta dissertação visa o desenvolvimento de uma estratégia de controlo baseada em EMG capaz de fornecer assistência quando necessário, para futura integração num sistema ortótico ativo e inteligente (SmartOs). Para atingir este objetivo foram desenvolvidos e validados os seguintes elementos: (i) sistema de EMG para adquirir sinais de atividade muscular dos músculos mais relevantes no movimento da articulação do tornozelo; (ii) ferramenta de machine learning para estimação do binário da articulação do tornozelo para servir como referência na estratégia de controlo; e (iii) ferramenta de estimação do binário real do tornozelo considerando sinais de EMG dos músculos Tibialis Anterior (TA) e Gastrocnemius Lateralis (GASL) e ângulo real do tornozelo.
O sistema de EMG apresentou correlações satisfatórias com um sistema comercial. O binário de referência para o tornozelo foi gerado com base no ângulo de referência da mesma articulação, velocidade de marcha (de 1 até 4 km/h) e dados antropométricos (alturas de 1.51 m até 1.83 e massas de 52.0 kg até 83.7 kg), usando cinco algoritmos de machine learning: Support Vector Machine, Random Forest, Multilayer Perceptron, Long-Short Term Memory e Convolutional Neural Network. CNN apresentou a melhor performance, prevendo binários de referência do tornozelo com um fit entre 74.7 e 89.8 % e Normalized Root Mean Square Errors (NRMSE) entre 3.16 e 8.02 %. A estimativa do torque com base em sinais de EMG requer a inclusão de um maior número de músculos, uma vez que sinais de EMG dos músculos TA e GASL não foram suficientes
MRI in multiple myeloma : a pictorial review of diagnostic and post-treatment findings
Magnetic resonance imaging (MRI) is increasingly being used in the diagnostic work-up of patients with multiple myeloma. Since 2014, MRI findings are included in the new diagnostic criteria proposed by the International Myeloma Working Group. Patients with smouldering myeloma presenting with more than one unequivocal focal lesion in the bone marrow on MRI are considered having symptomatic myeloma requiring treatment, regardless of the presence of lytic bone lesions. However, bone marrow evaluation with MRI offers more than only morphological information regarding the detection of focal lesions in patients with MM. The overall performance of MRI is enhanced by applying dynamic contrast-enhanced MRI and diffusion weighted imaging sequences, providing additional functional information on bone marrow vascularization and cellularity. This pictorial review provides an overview of the most important imaging findings in patients with monoclonal gammopathy of undetermined significance, smouldering myeloma and multiple myeloma, by performing a 'total' MRI investigation with implications for the diagnosis, staging and response assessment. Main message aEuro cent Conventional MRI diagnoses multiple myeloma by assessing the infiltration pattern. aEuro cent Dynamic contrast-enhanced MRI diagnoses multiple myeloma by assessing vascularization and perfusion. aEuro cent Diffusion weighted imaging evaluates bone marrow composition and cellularity in multiple myeloma. aEuro cent Combined morphological and functional MRI provides optimal bone marrow assessment for staging. aEuro cent Combined morphological and functional MRI is of considerable value in treatment follow-up
Total or Partial Knee Arthroplasty Trial - TOPKAT : study protocol for a randomised controlled trial
Peer reviewedPublisher PD
Biomechanics of foetal movement.
© 2015, AO Research Institute. All rights reserved.Foetal movements commence at seven weeks of gestation, with the foetal movement repertoire including twitches, whole body movements, stretches, isolated limb movements, breathing movements, head and neck movements, jaw movements (including yawning, sucking and swallowing) and hiccups by ten weeks of gestational age. There are two key biomechanical aspects to gross foetal movements; the first being that the foetus moves in a dynamically changing constrained physical environment in which the freedom to move becomes increasingly restricted with increasing foetal size and decreasing amniotic fluid. Therefore, the mechanical environment experienced by the foetus affects its ability to move freely. Secondly, the mechanical forces induced by foetal movements are crucial for normal skeletal development, as evidenced by a number of conditions and syndromes for which reduced or abnormal foetal movements are implicated, such as developmental dysplasia of the hip, arthrogryposis and foetal akinesia deformation sequence. This review examines both the biomechanical effects of the physical environment on foetal movements through discussion of intrauterine factors, such as space, foetal positioning and volume of amniotic fluid, and the biomechanical role of gross foetal movements in human skeletal development through investigation of the effects of abnormal movement on the bones and joints. This review also highlights computational simulations of foetal movements that attempt to determine the mechanical forces acting on the foetus as it moves. Finally, avenues for future research into foetal movement biomechanics are highlighted, which have potential impact for a diverse range of fields including foetal medicine, musculoskeletal disorders and tissue engineering
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