An alternative for human gait modelling using the Bond Graph Technique

The systematic analysis of the human gait with a skeletal or neuromuscular disorder is a valuable clinical instrument to determine the nature and severity of the disease. At present, there are many institutions that have developed a series of numerical models that simulate and analyze biomechanics systems such as the human gait. Many of these models require diverse and segmented programming to incorporate various effects of the dynamics of the body such as the performance of the muscles and tendons, the passive and active resistance to movement, and other physiological effects. One of the alternatives to simulate biomechanical systems is the use of the Bond Graph modeling technique. The modular modeling with multi-domains, a feature of the Bond Graph technique, is one of its potential advantages compare to other methods. The equations generated with the use of this technique are equivalent to those techniques developed with more traditional methods, but the modules can be easier and more comfortable to use in conjunction with models of neuromuscular control functions, models that incorporate the elasticity properties in the bones and tendons, etc. The proposed model, comprised of seven segments, is developed to estimate the torque and the power in the joints. This model is simulated and validated using the processed experimental data of a normal gait in GCD (Gait Cycle Data) format file

SIMBIO-M 2014, SIMulation technologies in the fields of BIO-Sciences and Multiphysics: BioMechanics, BioMaterials and BioMedicine, Marseille, France, june 2014

Proceedings de la 3ème édition de la conférence internationale Simbio-M (2014). Organisée conjointement par l'IFSTTAR, Aix-Marseille Université, l'université de Coventry et CADLM, cette conférence se concentre sur les progrès des technologies de simulation dans les domaines des sciences du vivant et multiphysiques: Biomécanique, Biomatériaux et Biomédical. L'objectif de cette conférence est de partager et d'explorer les résultats dans les techniques d'analyse numérique et les outils de modélisation mathématique. Cette approche numérique permet des études prévisionnelles ou exploratoires dans les différents domaines des biosciences

Development of an instrumented customizable total knee prosthesis for experimental tests.

Total knee arthroplasty (TKA) has revolutionized the life of millions of patients and it is the most efficient treatment in cases of osteoarthritis. The increase in life expectancy has lowered the average age of the patient, which requires a more enduring and performing prosthesis. To improve the design of implants and satisfying the patient's needs, a deep understanding of the knee Biomechanics is needed. To overcome the uncertainties of numerical models, recently instrumented knee prostheses are spreading. The aim of the thesis was to design and manifacture a new prototype of instrumented implant, able to measure kinetics and kinematics (in terms of medial and lateral forces and patellofemoral forces) of different interchangeable designs of prosthesis during experiments tests within a research laboratory, on robotic knee simulator. Unlike previous prototypes it was not aimed for industrial applications, but purely focusing on research. After a careful study of the literature, and a preliminary analytic study, the device was created modifying the structure of a commercial prosthesis and transforming it in a load cell. For monitoring the kinematics of the femoral component a three-layers, piezoelettric position sensor was manifactured using a Velostat foil. This sensor has responded well to pilot test. Once completed, such device can be used to validate existing numerical models of the knee and of TKA and create new ones, more accurate.It can lead to refinement of surgical techniques, to enhancement of prosthetic designs and, once validated, and if properly modified, it can be used also intraoperatively

Bioaéroelasticité d’aéronefs à voilure tournante par bond graphs

Under certain flight conditions, rotorcrafts might suffer from the emergence of undesirable oscillations, potentially unstable phenomena, known as aeroelastic Rotorcraft-Pilot Couplings (RPCs). These phenomena critically affect the safety and performance of rotorcraft designs. Therefore, there is an important interest in being able to predict the emergence of such dynamic phenomena, as soon as possible during the design process of helicopters. A review of the state-of-the-art reveals that these phenomena are the result of interactions between pilots’ biodynamics and helicopters’ aeroelastic behaviors. In order to provide more modularity and granularity in the modeling of complex systems, a bond graph based approach is used. A helicopter aeromechanical model and a pilot upper limb neuromusculoskeletal model are developed using bond graphs. Three original bond graph representations are proposed, to model: quasi-steady aerodynamic forces, lag-flap-pitch joint at blades’ roots, and a Hill-type muscle force model that accounts for muscle reflexive feedback. Encouraging results are found when comparing the pilot biodynamic model transmissibility cyclic lever angle to lateral cockpit accelerations computations to literature experimental results. A linear model of the coupled human-machine bioaeroelastic system around hover is analyzed in terms of stability. It reveals not only the regressing lag mode, as conjectured in literature, but also the advancing lag mode can be destabilized during a lateral-roll aeroelastic RPC. Furthermore, a criterion to assess the stability of the equilibrium of a dynamic system from a linear model limits the possibility to take into account nonlinear physical behaviors, reducing the design space. The first blocks towards a method based on Chetaev functions is proposed, to determine if an equilibrium is unstable, directly from its large nonlinear mathematical model, at a potentially interesting computational cost. The helicopter ‘ground resonance’ case illustrates the soundness of the proposal.Dans certaines conditions de vol, les aéronefs à voilure tournante souffrent parfois de l’émergence d’oscillations indésirables, phénomènes potentiellement instables connus sous le nom de Couplages Pilote-Aéronef aéroélastiques (CPA). Ces phénomènes affectent de manière critique la sécurité et la performance des aéronefs. Par conséquent, il est important d’être capable de prédire l’émergence de tels phénomènes dynamiques, le plus tôt possible dans le processus de conception des hélicoptères. Une revue de la littérature révèle que ces phénomènes sont le résultat d’interactions entre les comportements biodynamique du pilote et aéroélastique des hélicoptères. Afin d’avoir une plus grande modularité et granularité dans le processus de modélisation de systèmes complexes, une approche par bond graphs est adoptée. Un modèle aéromécanique d’hélicoptère et un modèle neuro-musculo-squelettique d’un des membres supérieurs du pilote sont développés en bond graphs. Parmi les représentations proposées, trois sont originales, notamment afin de modéliser : des efforts aérodynamiques quasi-statiques, la liaison traînée-battement-pas entre pale et moyeu rotor, et les efforts musculaires à partir d’un modèle de Hill qui tient compte d’une boucle de rétroaction neuromusculaire. Des résultats encourageants sont obtenus lorsque l’on compare la transmissibilité, entre l’angle de manche de pas cyclique imposé par le pilote et des accélérations latérales de la cabine, calculée à partir du modèle biodynamique, et à partir des résultats expérimentaux tirés de la littérature. Un modèle du système bioaéroélastique homme-machine est linéarisé, au voisinage d’un vol stationnaire, et analysé en termes de stabilité. L’étude révèle, comme conjecturé dans la littérature, que le mode régressif de traînée peut être déstabilisé. De plus, il apparaît que le mode progressif de traînée peut également être déstabilisé lors d’un CPA sur l’axe latéral-roulis. Un critère d’analyse de la stabilité d’un équilibre d’un système dynamique à partir d’un modèle linéaire limite la possibilité de prendre en compte certains comportements non-linéaires et donc réduit l’espace de conception. Les premières pierres vers une méthode basée sur des fonctions de Chetaev sont posées, afin de déterminer si l’équilibre d’un système dynamique est instable, directement à partir d’un modèle mathématique non-linéaire de grande dimension, à un coût de calcul potentiellement intéressant. Afin d’illustrer la pertinence de la proposition, le cas de la résonance sol d’un hélicoptère est présentée

Dynamic Cellular Actuator Arrays and Expanded Fingerprint Method for Dynamic Modeling

Copyright © ElsevierDOI: http://dx.doi.org/10.1016/j.robot.2013.06.013A key step to understanding and producing natural motion is creating a physical, well understood actuator with a dynamic model resembling biological muscle. This actuator can then serve as the basis for building viable, full-strength, and safe muscles for disabled patients, rehabilitation, human force amplification, telerobotics, and humanoid robotic systems. This paper presents a cell-based flexible actuator modeling methodology and the General Fingerprint Method for systematically and efficiently calculating the actuators’ respective dynamic equations of motion. The cellular actuator arrays combine many flexible ‘cells’ in complex and varied topologies for combined large-scale motion. The cells can have varied internal dynamic models and common actuators such as piezoelectric, SMA, linear motor, and pneumatic technologies can fit the model by adding a flexible element in series with the actuator. The topology of the cellular actuator array lends it many of its properties allowing the final muscle to be catered to particular applications. The General Fingerprint Method allows for fast recalculation for different and/or changing structures and internal dynamics, and provides an intuitive base for future controls work. This paper also presents two physical SMA based cellular actuator arrays which validate the presented theory and give a basis for future development

Diagnosis and Prognosis of Occupational disorders based on Machine Learn- ing Techniques applied to Occupational Profiles

Work-related disorders have a global influence on people’s well-being and quality of life and are a financial burden for organizations because they reduce productivity, increase absenteeism, and promote early retirement. Work-related musculoskeletal disorders, in particular, represent a significant fraction of the total in all occupational contexts. In automotive and industrial settings where workers are exposed to work-related muscu- loskeletal disorders risk factors, occupational physicians are responsible for monitoring workers’ health protection profiles. Occupational technicians report in the Occupational Health Protection Profiles database to understand which exposure to occupational work- related musculoskeletal disorder risk factors should be ensured for a given worker. Occu- pational Health Protection Profiles databases describe the occupational physician states, and which exposure the physicians considers necessary to ensure the worker’s health protection in terms of their functional work ability. The application of Human-Centered explainable artificial intelligence can support the decision making to go from worker’s Functional Work Ability to explanations by integrating explainability into medical (re- striction) and supporting in two decision contexts: prognosis and diagnosis of individual, work related and organizational risk condition. Although previous machine learning ap- proaches provided good predictions, their application in an actual occupational setting is limited because their predictions are difficult to interpret and hence, not actionable. In this thesis, injured body parts in which the ability changed in a worker’s functional work ability status are targeted. On the one hand, artificial intelligence algorithms can help technical teams, occupational physicians, and ergonomists determine a worker’s workplace risk via the diagnosis and prognosis of body part(s) injuries; on the other hand, these approaches can help prevent work-related musculoskeletal disorders by identifying which processes are lacking in working condition improvement and which workplaces have a better match between the remaining functional work abilities. A sample of 2025 for the prognosis part (from the years of 2019 to 2020) and 7857 for the prognosis part of Occupational Health Protection Profiles based on Functional Work Ability textual re- ports in the Portuguese language in automotive industry factory. Machine learning-based Natural Language Processing methods were implemented to extract standardized infor- mation. The prognosis and diagnosis of Occupational Health Protection Profiles factors were developed in reliable Human-Centered explainable artificial intelligence system to promote a trustworthy Human-Centered explainable artificial intelligence system (enti- tled Industrial microErgo application). The most suitable regression models to predict the next medical appointment for the injured body regions were the models based on CatBoost regression, with R square and an RMSLE of 0.84 and 1.23 weeks, respectively. In parallel, CatBoost’s best regression model for most body parts is the prediction of the next injured body parts based on these two errors. This information can help tech- nical industrial teams understand potential risk factors for Occupational Health Protec- tion Profiles and identify warning signs of the early stages of musculoskeletal disorders.Os transtornos relacionados ao trabalho têm influência global no bem-estar e na quali- dade de vida das pessoas e são um ônus financeiro para as organizações, pois reduzem a produtividade, aumentam o absenteísmo e promovem a aposentadoria precoce. Os distúr- bios osteomusculares relacionados ao trabalho, em particular, representam uma fração significativa do total em todos os contextos ocupacionais. Em ambientes automotivos e industriais onde os trabalhadores estão expostos a fatores de risco de distúrbios osteomus- culares relacionados ao trabalho, os médicos do trabalho são responsáveis por monitorar os perfis de proteção à saúde dos trabalhadores. Os técnicos do trabalho reportam-se à base de dados dos Perfis de Proteção da Saúde Ocupacional para compreender quais os fatores de risco de exposição a perturbações músculo-esqueléticas relacionadas com o tra- balho que devem ser assegurados para um determinado trabalhador. As bases de dados de Perfis de Proteção à Saúde Ocupacional descrevem os estados do médico do trabalho e quais exposições os médicos consideram necessária para garantir a proteção da saúde do trabalhador em termos de sua capacidade funcional para o trabalho. A aplicação da inteligência artificial explicável centrada no ser humano pode apoiar a tomada de decisão para ir da capacidade funcional de trabalho do trabalhador às explicações, integrando a explicabilidade à médica (restrição) e apoiando em dois contextos de decisão: prognóstico e diagnóstico da condição de risco individual, relacionado ao trabalho e organizacional . Embora as abordagens anteriores de aprendizado de máquina tenham fornecido boas pre- visões, sua aplicação em um ambiente ocupacional real é limitada porque suas previsões são difíceis de interpretar e portanto, não acionável. Nesta tese, as partes do corpo lesiona- das nas quais a habilidade mudou no estado de capacidade funcional para o trabalho do trabalhador são visadas. Por um lado, os algoritmos de inteligência artificial podem aju- dar as equipes técnicas, médicos do trabalho e ergonomistas a determinar o risco no local de trabalho de um trabalhador por meio do diagnóstico e prognóstico de lesões em partes do corpo; por outro lado, essas abordagens podem ajudar a prevenir distúrbios muscu- loesqueléticos relacionados ao trabalho, identificando quais processos estão faltando na melhoria das condições de trabalho e quais locais de trabalho têm uma melhor correspon- dência entre as habilidades funcionais restantes do trabalho. Para esta tese, foi utilizada uma base de dados com Perfis de Proteção à Saúde Ocupacional, que se baseiam em relató- rios textuais de Aptidão para o Trabalho em língua portuguesa, de uma fábrica da indús- tria automóvel (Auto Europa). Uma amostra de 2025 ficheiros foi utilizada para a parte de prognóstico (de 2019 a 2020) e uma amostra de 7857 ficheiros foi utilizada para a parte de diagnóstico. . Aprendizado de máquina- métodos baseados em Processamento de Lingua- gem Natural foram implementados para extrair informações padronizadas. O prognóstico e diagnóstico dos fatores de Perfis de Proteção à Saúde Ocupacional foram desenvolvidos em um sistema confiável de inteligência artificial explicável centrado no ser humano (inti- tulado Industrial microErgo application). Os modelos de regressão mais adequados para prever a próxima consulta médica para as regiões do corpo lesionadas foram os modelos baseados na regressão CatBoost, com R quadrado e RMSLE de 0,84 e 1,23 semanas, res- pectivamente. Em paralelo, a previsão das próximas partes do corpo lesionadas com base nesses dois erros relatados pelo CatBoost como o melhor modelo de regressão para a mai- oria das partes do corpo. Essas informações podem ajudar as equipes técnicas industriais a entender os possíveis fatores de risco para os Perfis de Proteção à Saúde Ocupacio- nal e identificar sinais de alerta dos estágios iniciais de distúrbios musculoesqueléticos

Program and Proceedings: The Nebraska Academy of Sciences 1880-2012

PROGRAM FRIDAY, APRIL 20, 2012 REGISTRATION FOR ACADEMY, Lobby of Lecture wing, Olin Hall Aeronautics and Space Science, Session A, Olin 249 Aeronautics and Space Science, Session B, Olin 224 Collegiate Academy, Biology Session A, Olin B Chemistry and Physics, Section A, Chemistry, Olin A Applied Science and Technology, Olin 325 Biological and Medical Sciences, Session A, Olin 112 Biological and Medical Sciences, Session B, Smith Callen Conference Center Junior Academy, Judges Check-In, Olin 219 Junior Academy, Senior High REGISTRATION, Olin Hall Lobby Chemistry and Physics, Section B, Physics, Planetarium Collegiate Academy, Chemistry and Physics, Session A, Olin 324 Junior Academy, Senior High Competition, Olin 124, Olin 131 Aeronautics and Space Science, Poster Session, Olin 249 NWU Health and Sciences Graduate School Fair, Olin and Smith Curtiss Halls Aeronautics and Space Science, Poster Session, Olin 249 MAIBEN MEMORIAL LECTURE, OLIN B Buffalo Bruce McIntosh, Research Ecologist with Western Nebraska Resources Council, The Status of Nebraska\u27s Native Aspen LUNCH, PATIO ROOM, STORY STUDENT CENTER (pay and carry tray through cafeteria line, or pay at NAS registration desk) Aeronautics Group, Conestoga Room Anthropology, Olin 111 Biological and Medical Sciences, Session C, Olin 112 Biological and Medical Sciences, Session D, Smith Callen Conference Center Chemistry and Physics, Section A, Chemistry, Olin A Chemistry and Physics, Section B, Physics, Planetarium Collegiate Academy, Biology Session A, Olin B Collegiate Academy, Biology Session B, Olin 249 Collegiate Academy, Chemistry and Physics, Session B, Olin 324 Earth Science, Olin 224 History/Philosophy of Science, Olin 325 Junior Academy, Judges Check-In, Olin 219 Junior Academy, Junior High REGISTRATION, Olin Hall Lobby Junior Academy, Senior High Competition, (Final), Olin 110 Teaching of Science and Math, Olin 325 Junior Academy, Junior High Competition, Olin 124, Olin 131 NJAS Board/Teacher Meeting, Olin 219 BUSINESS MEETING, OLIN B AWARDS RECEPTION for NJAS, Scholarships, Members, Spouses, and Guests First United Methodist Church, 2723 N 50th Street, Lincoln, N

Towards Molecular Simulations that are Transparent, Reproducible, Usable By Others, and Extensible (TRUE)

Systems composed of soft matter (e.g., liquids, polymers, foams, gels, colloids, and most biological materials) are ubiquitous in science and engineering, but molecular simulations of such systems pose particular computational challenges, requiring time and/or ensemble-averaged data to be collected over long simulation trajectories for property evaluation. Performing a molecular simulation of a soft matter system involves multiple steps, which have traditionally been performed by researchers in a "bespoke" fashion, resulting in many published soft matter simulations not being reproducible based on the information provided in the publications. To address the issue of reproducibility and to provide tools for computational screening, we have been developing the open-source Molecular Simulation and Design Framework (MoSDeF) software suite. In this paper, we propose a set of principles to create Transparent, Reproducible, Usable by others, and Extensible (TRUE) molecular simulations. MoSDeF facilitates the publication and dissemination of TRUE simulations by automating many of the critical steps in molecular simulation, thus enhancing their reproducibility. We provide several examples of TRUE molecular simulations: All of the steps involved in creating, running and extracting properties from the simulations are distributed on open-source platforms (within MoSDeF and on GitHub), thus meeting the definition of TRUE simulations