Journal articles: 'Opensim'

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Mihradi, Sandro, Ferryanto Ferryanto, and Samuel J. Harjanto. "Modeling Muscle Activities of Squat Motion using OpenSIM." Jurnal Teknik Mesin Indonesia 19, no. 02 (2024): 125–31. http://dx.doi.org/10.36289/jtmi.v19i02.756.

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Human beings need to be able to monitor their muscle health. Muscle health can be assessed by directly measuring its signal using an electromyography sensor or, recently, from a musculoskeletal modeling software such as OpenSIM. OpenSIM is an open-source platform for modeling, simulating, and analyzing the neuromusculoskeletal system. This work aims to simulate muscle forces during squat movement using OpenSIM simulation and validate the results using electromyography sensors attached to the body. The squat movement data generated from the optical motion capture system and the force plate will be used as inputs for the OpenSIM software. OpenSIM can provide output, such as a graph of the working muscle forces. That graph will be compared and analyzed with a surface electromyography sensor results graph. Based on the analysis results, the chart of working muscle forces generated by the OpenSIM software has shown a similar trend to the graph of muscle activity resulting from surface electromyography sensor reading. Therefore, the simulation results from the OpenSIM software were validated, and it was implied that the data collection process and the modeling were done correctly.

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Perera, Indika, Dulani Meedeniya, Colin Allison, and Alan Miller. "User Support for Managed Immersive Education: An Evaluation of in-World Training for OpenSim." JUCS - Journal of Universal Computer Science 20, no. (12) (2014): 1690–707. https://doi.org/10.3217/jucs-020-12-1690.

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Supporting users for a competent interaction with 3 dimensional virtual worlds can increase their user experience within the immersive education environment. User manuals and other guide documents are popular supporting instruments for training new users of a software system. Quite often these documents have many screenshots of the application user interface which are used to steer a new user through sequential orders of actions. However, for complex scenarios of user interactions, such as those found in virtual worlds, these types of documents can become unhelpfully lengthy and unintuitive. The first part of this research was a comparative analysis of traditional document-based user support with an in-world approach; a prototype training island was developed in OpenSim and evaluated for its training support against the OpenSim user guide documents. The results suggested in-world training can be a better option of training for OpenSim than training documents. Second part of this research was to evaluate a completed training environment, which consist of two OpenSim islands, one for basic user training and one for training advanced OpenSim management. The results suggested that training for advanced OpenSim management, which is not covered in user guide documents, make users competent for managing their immersive environment. The final part of the research, a case study, examined the effective use of this complete training environment for module teaching and learner support. The results suggest that for learning the skills essential for productive use of OpenSim-based educational environments, an in-world approach covering advanced management functions of OpenSim is likely to be a better option than traditional user manuals for the future needs for immersive education as a mainstream practice.

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Dembia, Christopher L., Nicholas A. Bianco, Antoine Falisse, Jennifer L. Hicks, and Scott L. Delp. "OpenSim Moco: Musculoskeletal optimal control." PLOS Computational Biology 16, no. 12 (2020): e1008493. http://dx.doi.org/10.1371/journal.pcbi.1008493.

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Musculoskeletal simulations are used in many different applications, ranging from the design of wearable robots that interact with humans to the analysis of patients with impaired movement. Here, we introduce OpenSim Moco, a software toolkit for optimizing the motion and control of musculoskeletal models built in the OpenSim modeling and simulation package. OpenSim Moco uses the direct collocation method, which is often faster and can handle more diverse problems than other methods for musculoskeletal simulation. Moco frees researchers from implementing direct collocation themselves—which typically requires extensive technical expertise—and allows them to focus on their scientific questions. The software can handle a wide range of problems that interest biomechanists, including motion tracking, motion prediction, parameter optimization, model fitting, electromyography-driven simulation, and device design. Moco is the first musculoskeletal direct collocation tool to handle kinematic constraints, which enable modeling of kinematic loops (e.g., cycling models) and complex anatomy (e.g., patellar motion). To show the abilities of Moco, we first solved for muscle activity that produced an observed walking motion while minimizing squared muscle excitations and knee joint loading. Next, we predicted how muscle weakness may cause deviations from a normal walking motion. Lastly, we predicted a squat-to-stand motion and optimized the stiffness of an assistive device placed at the knee. We designed Moco to be easy to use, customizable, and extensible, thereby accelerating the use of simulations to understand the movement of humans and other animals.

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Kim, Heesung, and Fengfeng Ke. "OpenSim-Supported Virtual Learning Environment." Journal of Educational Computing Research 54, no. 2 (2015): 147–72. http://dx.doi.org/10.1177/0735633115620197.

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Gautam, Kamal, Mohamed S. Hefzy, Abdul A. Mustapha, and Behrens Kyle. "Comparison of OpenSim and AnyBody modeling system™ predictions in biomechanical modeling of upper extremities." International Journal of Research in Orthopaedics 10, no. 4 (2024): 717–24. http://dx.doi.org/10.18203/issn.2455-4510.intjresorthop20241695.

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Background: The study of muscle forces in upper extremities is pivotal for advancements in biomechanical modeling, contributing significantly to the field of orthopedics, rehabilitation, and sports science. Despite the prominence of OpenSim and AnyBody modeling system™ in this domain, a gap persists in comparative analyses specifically targeting muscle force predictions in upper extremity motions. Methods: This study compares the predictions of muscle forces in static elbow flexion, shoulder flexion, and shoulder abduction using OpenSim and AnyBody modeling systemTM, hypothesizing significant differences in predictions attributable to their distinct modeling methodologies and assumptions. This work utilized generic models without subject-specific data and conducted simulations in both software environments, focusing on the magnitude and activation of major muscle forces under predefined kinematics. Results: OpenSim and AnyBody modeling systemTM produced similar results when simulating elbow flexion, with both software predicting forces in the major muscles required to maintain the posture. However, discrepancies were observed between the two software for muscle force predictions during the shoulder flexion and abduction movements. AnyBody modeling systemTM appeared to be more robust as it included all the upper extremity muscles and predicted the major muscles forces required for these movements more accurately compared to OpenSim. Conclusions: The results of this study show significant differences in muscle force predictions between OpenSim and AnyBody modeling systemTM, attributed to the unique modeling approaches, especially in representing muscle-tendon complexes and joint dynamics.

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Mutka, Matt W., and Philip K. McKinley. "Supporting a Simulation Environment with OpenSim." SIMULATION 61, no. 4 (1993): 223–35. http://dx.doi.org/10.1177/003754979306100402.

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Sankar, Krishnakumar, Shantanu Patil, and Sridhar Krishnamurthy. "Analysis of grip and pinch strength using inverse dynamics simulation technique." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 232, no. 11 (2018): 1063–70. http://dx.doi.org/10.1177/0954411918798400.

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Grip strength is the function of musculotendinous action across the finger joints and varies while dealing objects of varying size and shape. Increasing object size requires greater effort by the fingers to grip. The main objective of this study is to analyse the variation in grip and pinch strength exerted on objects of various sizes and shapes in a short span of time. OpenSim 3.3 is open-source musculoskeletal modelling software used for performing simulations in a dynamic environment. The generic wrist model in OpenSim has movements on index finger and thumb only, for study purpose. Objects of various sizes were designed and imported in OpenSim. This study determines the joint moments exerted by the fingers during grip activities. Original model was modified and custom joints were placed in the proximal and distal phalanx joints of the fingers. This allowed the finger segments to undergo translational and rotational movements. Coordinates of the custom joints were adjusted to provide constraints in the joint movement to hold the objects in position. For grip strength, objects of various sizes and shapes were imported to OpenSim. Simulation was carried out for gripping the objects for a specified time period. The force generated by the synergistic movements of finger segments was compared among grip and pinch of different objects. This method is used to determine the grip and pinch strength by handling objects of different shapes and sizes under the influence of time.

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Gautam, Kamal, Mohamed Samir Hefzy, Kyle Behrens, and Abdul A. Mustapha. "Predictions of Muscle Forces During the Cross-Body Adduction and Hand-Behind-the-Back Tests to Assess Osteoarthritis of the Acromioclavicular Joint." Applied Sciences 15, no. 2 (2025): 967. https://doi.org/10.3390/app15020967.

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Acromioclavicular joint osteoarthritis is prevalent in middle-aged and older people, causing shoulder pain and functional limitations. Despite its prevalence, there are inconsistencies in the physical diagnosis procedures practiced in clinical tests. A recent study introduced a novel hand-behind-the-back (HBB) test, a promising alternative to the traditional cross-body adduction (CBA) test. However, further study was suggested to validate the results obtained. So, this study predicted muscle forces for the cross-body adduction and hand-behind-the-back tests using OpenSim and the AnyBody Modeling System™. This work redefined the joint kinematics for the tests and performed an inverse dynamics analysis to solve the muscle redundancy problem using the generic upper extremity dynamic models available in OpenSim and AnyBody Modeling System™. The results revealed some agreements and significant discrepancies in most muscle force predictions between the OpenSim and AnyBody Modeling SystemTM. Thus, this study underscores the necessity of integrating multiple modeling approaches and comprehensive validation, including experimental data, to enhance the accuracy and reliability of muscle force predictions in shoulder biomechanics during CBA and HBB tests.

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Nguyen, Ngoc Hong. "Simulating the Generative Process of Urban Form: An Application Using OpenSim." Journal of Planning Education and Research 40, no. 4 (2018): 393–404. http://dx.doi.org/10.1177/0739456x18772069.

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This article aims to investigate the generative process of urban development using simulation methods. The open-source platform OpenSim was used to allow participants to build immersive virtual environments representing the ancient town of Hoian, Vietnam. Patterns and urban properties are implemented as rules of generative process in urban design. This research not only corroborates Alexander’s methods but significantly improves his and colleagues’ method in providing a clear approach in generative process in urban design. Through the immersive environment of OpenSim, communities are able to establish effective public participation in planning their neighborhood as well as build and test urban codes.

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Reinbolt, Jeffrey A., Ajay Seth, and Scott L. Delp. "Simulation of human movement: applications using OpenSim." Procedia IUTAM 2 (2011): 186–98. http://dx.doi.org/10.1016/j.piutam.2011.04.019.

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Van der Krogt, Marjolein, Ajay Seth, Katherine Steele, et al. "A model of muscle spasticity in opensim." Gait & Posture 38 (November 2013): S16. http://dx.doi.org/10.1016/j.gaitpost.2013.07.039.

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Mahadas, Srikrishnaraja, Kausalendra Mahadas, and George K. Hung. "Biomechanics of the golf swing using OpenSim." Computers in Biology and Medicine 105 (February 2019): 39–45. http://dx.doi.org/10.1016/j.compbiomed.2018.12.002.

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Daliet, Oliver J., Kristín Briem, Sigurður Brynjólfsson, and Haraldur B. Sigurðsson. "Combined Effects of External Moments and Muscle Activations on ACL Loading during Numerical Simulations of a Female Model in OpenSim." Applied Sciences 11, no. 24 (2021): 11971. http://dx.doi.org/10.3390/app112411971.

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Background: Anterior cruciate ligament (ACL) injuries have been studied using a variety of methods and tools. However, each is hindered by specific limitations with respect to its application. Aim: To assess the combined effects of external moments and muscle activations on ACL loading using serial, forward dynamics (FD) simulations of single leg, hyperextension landings in OpenSim. Methods: The FD tool of OpenSim was iteratively run using different combinations of knee-spanning muscle activation levels, internal rotation and valgus knee moment magnitudes. A regression was conducted on the data in order to predict ACL loading under different conditions. Results: A purely abduction moment leads to greater mean ACL loading than a purely internal rotation moment or any combination of the two. Additionally, the generalized boosted regression model using both external moments and certain knee muscles identified the internal rotation moment as the most important variable in predicting the ACL load (R2 = 0.9; p < 0.0001). Conclusion: This study demonstrated a novel and practical application of an OpenSim musculoskeletal model that supports the ACL injury mechanism of landing with low knee flexion angles, high muscle forces of the Quadriceps muscles and an external knee valgus moment, though further investigation is needed.

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Becker, Joanne, Emmanuel Mermoz, and Jean-Marc Linares. "Determination of biological joint reaction forces from in-vivo experiments using a hybrid combination of biomechanical and mechanical engineering software." Mechanics & Industry 21, no. 6 (2020): 623. http://dx.doi.org/10.1051/meca/2020088.

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In biomechanical field, several studies used OpenSim software to compute the joint reaction forces from kinematics and ground reaction forces measurements. The bio-inspired joints design and their manufacturing need the usage of mechanical modeling and simulation software tools. This paper proposes a new hybrid methodology to determine biological joint reaction forces from in vivo measurements using both biomechanical and mechanical engineering softwares. The methodology has been applied to the horse forelimb joints. The computed joint reaction forces results would be compared to the results obtained with OpenSim in a previous study. This new hybrid model used a combination of measurements (bone geometry, kinematics, ground reaction forces…) and also OpenSim results (muscular and ligament forces). The comparison between the two models showed values with an average difference of 8% at trotting and 16% at jumping. These differences can be associated with the differences between the modelling strategies. Despite these differences, the mechanical modeling method allows the computation of advanced simulations to handle contact conditions in joints. In future, the proposed mechanical engineering methodology could open the door to define a biological digital twin of a quadruped limb including the real geometry modelling of the joint.

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Voss, Gleizer Bierhalz, Felipe Becker Nunes, Fabrício Herpich, and Roseclea Duarte Medina. "Ambientes virtuais de aprendizagem e ambientes imersivos." Tecnologias, Sociedade e Conhecimento 2, no. 1 (2021): 24–42. http://dx.doi.org/10.20396/tsc.v2i1.14448.

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A utilização da tecnologia na educação acarretou em importantes mudanças nos métodos e técnicas aplicadas, assim como na utilização de tecnologias de computação móvel em ambientes virtuais de aprendizagem e mundos virtuais. Este artigo é uma versão estendida de Voss et al. (2013) e apresenta um estudo acerca das soluções existentes para o acesso via dispositivos móveis ao AVA Moodle em conjunto com o mundo virtual OpenSim, com o acréscimo de novas e atualizadas ferramentas. Os resultados mostraram-se satisfatórios, com o uso do tema Bootstrap para o Moodle e o viewer Lumiya para o OpenSim, no entanto algumas limitações técnicas precisam ser superadas para o uso em grande escala.

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Lee, Leng-Feng, and Brian R. Umberger. "Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB." PeerJ 4 (January 26, 2016): e1638. http://dx.doi.org/10.7717/peerj.1638.

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Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1–2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility.

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Wechsler, Iris, Alexander Wolf, Sophie Fleischmann, et al. "Method for Using IMU-Based Experimental Motion Data in BVH Format for Musculoskeletal Simulations via OpenSim." Sensors 23, no. 12 (2023): 5423. http://dx.doi.org/10.3390/s23125423.

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Biomechanical simulation allows for in silico estimations of biomechanical parameters such as muscle, joint and ligament forces. Experimental kinematic measurements are a prerequisite for musculoskeletal simulations using the inverse kinematics approach. Marker-based optical motion capture systems are frequently used to collect this motion data. As an alternative, IMU-based motion capture systems can be used. These systems allow flexible motion collection without nearly any restriction regarding the environment. However, one limitation with these systems is that there is no universal way to transfer IMU data from arbitrary full-body IMU measurement systems into musculoskeletal simulation software such as OpenSim. Thus, the objective of this study was to enable the transfer of collected motion data, stored as a BVH file, to OpenSim 4.4 to visualize and analyse the motion using musculoskeletal models. By using the concept of virtual markers, the motion saved in the BVH file is transferred to a musculoskeletal model. An experimental study with three participants was conducted to verify our method’s performance. Results show that the present method is capable of (1) transferring body dimensions saved in the BVH file to a generic musculoskeletal model and (2) correctly transferring the motion data saved in the BVH file to a musculoskeletal model in OpenSim 4.4.

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Raveendranathan, Vishal, Vera G. M. Kooiman, and Raffaella Carloni. "Musculoskeletal model of osseointegrated transfemoral amputees in OpenSim." PLOS ONE 18, no. 9 (2023): e0288864. http://dx.doi.org/10.1371/journal.pone.0288864.

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This study presents a generic OpenSim musculoskeletal model of people with an osseointegrated unilateral transfemoral amputation wearing a generic prosthesis. The model, which consists of seventy-six musculotendon units and two ideal actuators at the knee and ankle joints of the prosthesis, is tested by designing an optimal control strategy that guarantees the tracking of experimental amputee data during level-ground walking while finding the actuators’ torques and minimizing the muscle forces. The model can be made subject-specific and, as such, is able to reproduce the kinematics and dynamics of both healthy and amputee subjects. The model provides a tool to analyze the biomechanics of level-ground walking and to understand the contribution of the muscles and of the prosthesis’ actuators. The proposed OpenSim musculoskeletal model is released as support material to this study.

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Humphrey, Quentin, Manoj Srinivasan, Syed T. Mubarrat, and Suman K. Chowdhury. "Development of a Full-body OpenSim Musculoskeletal Model Incorporating Head-mounted Virtual Reality Headset." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (2021): 477–81. http://dx.doi.org/10.1177/1071181321651270.

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In this study, we developed and validated a full-body musculoskeletal model in OpenSim to estimate muscle and joint forces while performing various motor tasks using a virtual reality (VR) system. We compared the results from our developed full-body musculoskeletal model to those from previous studies by simulating kinematic and kinetic data of participants performing pick-and-place lifting tasks using with and without a physically interactive VR system. Results showed that scaling errors between the two environments are comparable, while the overall errors were consistent with previous studies. Overall, the results from the inverse dynamic simulations showed the promise of our developed OpenSim models in determining potential intervention or prevention strategies to reduce the musculoskeletal injury incidences while simulating human-device interaction tasks.

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Barrett, Jeff M., Colin D. McKinnon, Clark R. Dickerson, and Jack P. Callaghan. "An Electromyographically Driven Cervical Spine Model in OpenSim." Journal of Applied Biomechanics 37, no. 5 (2021): 481–93. http://dx.doi.org/10.1123/jab.2020-0384.

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Relatively few biomechanical models exist aimed at quantifying the mechanical risk factors associated with neck pain. In addition, there is a need to validate spinal-rhythm techniques for inverse dynamics spine models. Therefore, the present investigation was 3-fold: (1) the development of a cervical spine model in OpenSim, (2) a test of a novel spinal-rhythm technique based on minimizing the potential energy in the passive tissues, and (3) comparison of an electromyographically driven approach to estimating compression and shear to other cervical spine models. The authors developed ligament force–deflection and intervertebral joint moment–angle curves from published data. The 218 Hill-type muscle elements, representing 58 muscles, were included and their passive forces validated against in vivo data. Our novel spinal-rhythm technique, based on minimizing the potential energy in the passive tissues, disproportionately assigned motion to the upper cervical spine that was not physiological. Finally, using kinematics and electromyography collected from 8 healthy male volunteers, the authors calculated the compression at C7–T1 as a function of the head–trunk Euler angles. Differences from other models varied from 25.5 to 368.1 N. These differences in forces may result in differences in model geometry, passive components, number of degrees of freedom, or objective functions.

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ITO, Akira, Sota SHIMA, Hiroto MINOURA, and Youjiro TAMURA. "Simulation of Human Lower Limb with OpenSim Software." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2017 (2017): 2P2—K03. http://dx.doi.org/10.1299/jsmermd.2017.2p2-k03.

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Fu, Xun, Jack Withers, Juri A. Miyamae, and Talia Y. Moore. "ArborSim: Articulated, branching, OpenSim routing for constructing models of multi-jointed appendages with complex muscle-tendon architecture." PLOS Computational Biology 20, no. 7 (2024): e1012243. http://dx.doi.org/10.1371/journal.pcbi.1012243.

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Computational models of musculoskeletal systems are essential tools for understanding how muscles, tendons, bones, and actuation signals generate motion. In particular, the OpenSim family of models has facilitated a wide range of studies on diverse human motions, clinical studies of gait, and even non-human locomotion. However, biological structures with many joints, such as fingers, necks, tails, and spines, have been a longstanding challenge to the OpenSim modeling community, especially because these structures comprise numerous bones and are frequently actuated by extrinsic muscles that span multiple joints—often more than three—and act through a complex network of branching tendons. Existing model building software, typically optimized for limb structures, makes it difficult to build OpenSim models that accurately reflect these intricacies. Here, we introduce ArborSim, customized software that efficiently creates musculoskeletal models of highly jointed structures and can build branched muscle-tendon architectures. We used ArborSim to construct toy models of articulated structures to determine which morphological features make a structure most sensitive to branching. By comparing the joint kinematics of models constructed with branched and parallel muscle-tendon units, we found that among various parameters—the number of tendon branches, the number of joints between branches, and the ratio of muscle fiber length to muscle tendon unit length—the number of tendon branches and the number of joints between branches are most sensitive to branching modeling method. Notably, the differences between these models showed no predictable pattern with increased complexity. As the proportion of muscle increased, the kinematic differences between branched and parallel models units also increased. Our findings suggest that stress and strain interactions between distal tendon branches and proximal tendon and muscle greatly affect the overall kinematics of a musculoskeletal system. By incorporating complex muscle-tendon branching into OpenSim models using ArborSim, we can gain deeper insight into the interactions between the axial and appendicular skeleton, model the evolution and function of diverse animal tails, and understand the mechanics of more complex motions and tasks.

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移, 芸婧. "Verification of Lumbar Exoskeleton Assistance Effectiveness Based on OpenSim." Modeling and Simulation 13, no. 05 (2024): 5623–32. http://dx.doi.org/10.12677/mos.2024.135510.

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Lee, Jong Hwa, Deanna S. Asakawa, Jack T. Dennerlein, and Devin L. Jindrich. "Finger Muscle Attachments for an OpenSim Upper-Extremity Model." PLOS ONE 10, no. 4 (2015): e0121712. http://dx.doi.org/10.1371/journal.pone.0121712.

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Hast, Michael W., Brett G. Hanson, and Josh R. Baxter. "Simulating contact using the elastic foundation algorithm in OpenSim." Journal of Biomechanics 82 (January 2019): 392–96. http://dx.doi.org/10.1016/j.jbiomech.2018.11.025.

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Bottini, Ludovica, Giacomo Di Raimondo, Bryce Adrian Killen, Zimi Sawacha, and Ilse Jonkers. "IMU-based ground reaction force estimation using OpenSim Moco." Gait & Posture 106 (September 2023): S48. http://dx.doi.org/10.1016/j.gaitpost.2023.07.061.

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Trivedi, Urvish, Redwan Alqasemi, and Rajiv Dubey. "CARRT—Motion Capture Data for Robotic Human Upper Body Model." Sensors 23, no. 20 (2023): 8354. http://dx.doi.org/10.3390/s23208354.

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In recent years, researchers have focused on analyzing humans’ daily living activities to study various performance metrics that humans subconsciously optimize while performing a particular task. In order to recreate these motions in robotic structures based on the human model, researchers developed a framework for robot motion planning which is able to use various optimization methods to replicate similar motions demonstrated by humans. As part of this process, it will be necessary to record the motions data of the human body and the objects involved in order to provide all the essential information for motion planning. This paper aims to provide a dataset of human motion performing activities of daily living that consists of detailed and accurate human whole-body motion data collected using a Vicon motion capture system. The data have been utilized to generate a subject-specific full-body model within OpenSim. Additionally, it facilitated the computation of joint angles within the OpenSim framework, which can subsequently be applied to the subject-specific robotic model developed MATLAB framework. The dataset comprises nine daily living activities and eight Range of Motion activities performed by ten healthy participants and with two repetitions of each variation of one action, resulting in 340 demonstrations of all the actions. A whole-body human motion database is made available to the public at the Center for Assistive, Rehabilitation, and Robotics Technologies (CARRT)-Motion Capture Data for Robotic Human Upper Body Model, which consists of raw motion data in .c3d format, motion data in .trc format for the OpenSim model, as well as post-processed motion data for the MATLAB-based model.

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Brambilla, Cristina, and Alessandro Scano. "The Number and Structure of Muscle Synergies Depend on the Number of Recorded Muscles: A Pilot Simulation Study with OpenSim." Sensors 22, no. 22 (2022): 8584. http://dx.doi.org/10.3390/s22228584.

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The muscle synergy approach is used to evaluate motor control and to quantitatively determine the number and structure of the modules underlying movement. In experimental studies regarding the upper limb, typically 8 to 16 EMG probes are used depending on the application, although the number of muscles involved in motor generation is higher. Therefore, the number of motor modules may be underestimated and the structure altered with the standard spatial synergy model based on the non-negative matrix factorization (NMF). In this study, we compared the number and structure of muscle synergies when considering 12 muscles (an “average” condition that represents previous studies) and 32 muscles of the upper limb, also including multiple muscle heads and deep muscles. First, we estimated the muscle activations with an upper-limb model in OpenSim using data from multi-directional reaching movements acquired in experimental sessions; then, spatial synergies were extracted from EMG activations from 12 muscles and from 32 muscles and their structures were compared. Finally, we compared muscle synergies obtained from OpenSim and from real experimental EMG signals to assess the reliability of the results. Interestingly, we found that on average, an additional synergy is needed to reconstruct the same R2 level with 32 muscles with respect to 12 muscles; synergies have a very similar structure, although muscles with comparable physiological functions were added to the synergies extracted with 12 muscles. The additional synergies, instead, captured patterns that could not be identified with only 12 muscles. We concluded that current studies may slightly underestimate the number of controlled synergies, even though the main structure of synergies is not modified when adding more muscles. We also show that EMG activations estimated with OpenSim are in partial (but not complete) agreement with experimental recordings. These findings may have significative implications for motor control and clinical studies.

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Jung, Erik, Victoria Ly, Christopher Cheney, et al. "Design, Construction and Validation of a Proof of Concept Flexible–Rigid Mechanism Emulating Human Leg Behavior." Applied Sciences 11, no. 19 (2021): 9351. http://dx.doi.org/10.3390/app11199351.

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In most robotics simulations, human joints (e.g., hips and knees) are assumed to be revolute joints with limited range rotations. However, this approach neglects the internal flexibility of the joint, which could present a significant drawback in some applications. We propose a tensegrity-inspired robotic manipulator that can replicate the kinematic behavior of the human leg. The design of the hip and knee resembles the musculoskeletal connections within the human body. Our implementation represents muscles, tendons and ligament connections as cables, and bones as rods. This particular design manipulates muscles to replicate a human-like gait, which demonstrates its potential for use as an anatomically correct assistive device (prosthetic, exoskeleton, etc.). Using the OpenSim 3.0 simulation environment, we estimated the kinematics and structural integrity of the proposed flexural joint design and determined the actuation strategies for our prototype. Kinematics for the prototype include the mechanical limitations and constraints derived from the simulations. We compared the simulation, physical prototype, and human leg behaviors for various ranges of motion and demonstrated the potential for using OpenSim 3.0 as a flexible–rigid modeling and simulation environment.

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Goell, Fabian, Bjoern Braunstein, Maike Stemmler, Alessandro Fasse, Dirk Abel, and Kirsten Albracht. "Advancing knee adduction moment prediction for neuromuscular training via functional joint definitions and real–time simulation using OpenSim." PLOS One 20, no. 6 (2025): e0324985. https://doi.org/10.1371/journal.pone.0324985.

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Neuromuscular training to strengthen leg muscles is an important part of the treatment of musculoskeletal disorders and chronic diseases and preventing age–related muscle loss. This study evaluates different individualization approaches and their real–time implementation for OpenSim musculoskeletal models to estimate the external knee adduction moment during a leg–press exercise. A robotic neuromuscular training platform was utilized to perform isometric and dynamic leg extension exercises. Data were collected for 13 subjects using a 3D motion capture system and force plate measurements from the robotic training platform. Functional joint parameters, determined through dynamic reference movements, were integrated into the OpenSim models, allowing a personalized representation of the hip, knee, and ankle joints. This integration was compared with a conventional scaling method. The results indicate that the incorporation of functional joint axes can significantly enhance the accuracy of biomechanical simulations. These methods provide a real–time and a more precise estimate of the external knee adduction moment compared to conventional scaling approaches and underscore the importance of individualized model parameters in biomechanical research.

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Lee, Jong Hwa, Deanna S. Asakawa, Jack T. Dennerlein, and Devin L. Jindrich. "Correction: Finger Muscle Attachments for an OpenSim Upper-Extremity Model." PLOS ONE 17, no. 4 (2022): e0267620. http://dx.doi.org/10.1371/journal.pone.0267620.

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Shachykov, Andrii, Julien Frere, and Patrick Henaff. "Simulation of Spinal Muscle Control in Human Gait Using OpenSim." IEEE Transactions on Medical Robotics and Bionics 4, no. 1 (2022): 254–65. http://dx.doi.org/10.1109/tmrb.2022.3143263.

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Valente, Giordano, Gianluigi Crimi, Nicola Vanella, Enrico Schileo, and Fulvia Taddei. "nmsBuilder : Freeware to create subject-specific musculoskeletal models for OpenSim." Computer Methods and Programs in Biomedicine 152 (December 2017): 85–92. http://dx.doi.org/10.1016/j.cmpb.2017.09.012.

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WANG, Xiaoling, Jiawei JIAN, Qiurong XIE, et al. "Tibiofemoral Joint Contact Force Estimation Based on OpenSim Musculoskeletal Modeling." Rehabilitation Medicine 35, no. 1 (2025): 59–68. https://doi.org/10.3724/sp.j.1329.2025.01015.

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Zhou, Na, and Haiguang Hu. "Rehabilitation management of sports athletes’ muscle injury based on OpenSim technology." Molecular & Cellular Biomechanics 21 (August 6, 2024): 175. http://dx.doi.org/10.62617/mcb.v21.175.

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Due to the rapid development of sports and people’s love for sports, athletes often perform resistance training beyond the body to achieve better results, resulting in frequent muscle injuries. After the injury, the athlete cannot return to the state before the injury in time, which destroys the previous training results and hinders the athlete from improving to the professional level. Therefore, the research of athletes’ post-injury rehabilitation is the central subject of modern sports science research. This paper used OpenSim technology to study the rehabilitation management of sports athletes’ muscle injury. In this paper, the OpenSim skeletal muscle model was first established, followed by muscle modeling and characteristic analysis, and then a muscle rehabilitation system was constructed. The experimental part used the limb rehabilitation device model of this paper to carry out muscle rehabilitation training for patients with muscle injury, and compared it with conventional rehabilitation training. The experimental results showed that the limb rehabilitation device in this paper had a better rehabilitation effect. Compared with the traditional rehabilitation training, the excellent rate of the total active range of motion of the joints and the satisfaction of rehabilitation nursing were both increased by 10%.

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Bedo, Bruno L. S., Alice Mantoan, Danilo S. Catelli, Willian Cruaud, Monica Reggiani, and Mario Lamontagne. "BOPS: a Matlab toolbox to batch musculoskeletal data processing for OpenSim." Computer Methods in Biomechanics and Biomedical Engineering 24, no. 10 (2021): 1104–14. http://dx.doi.org/10.1080/10255842.2020.1867978.

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Leber, Jean-François, and Andreas Jarosch. "OpenSim: A Flexible Distributed Neural Network Simulator with Automatic Interactive Graphics." Neural Networks 10, no. 4 (1997): 693–703. http://dx.doi.org/10.1016/s0893-6080(96)00121-9.

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Trinler, Ursula, Hermann Schwameder, Richard Baker, and Nathalie Alexander. "Muscle force estimation in clinical gait analysis using AnyBody and OpenSim." Journal of Biomechanics 86 (March 2019): 55–63. http://dx.doi.org/10.1016/j.jbiomech.2019.01.045.

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Senteler, Marco, Bernhard Weisse, Dominique A. Rothenfluh, and Jess G. Snedeker. "Intervertebral reaction force prediction using an enhanced assembly of OpenSim models." Computer Methods in Biomechanics and Biomedical Engineering 19, no. 5 (2015): 538–48. http://dx.doi.org/10.1080/10255842.2015.1043906.

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Ayodele, K. P., O. T. Akinniyi, A. O. Oluwatope, A. M. Jubril, A. O. Ogundele, and M. A. Komolafe. "A Simulator for Testing Planar Upper Extremity Rehabilitation Robot Control Algorithms." Nigerian Journal of Technology 40, no. 1 (2021): 115–28. http://dx.doi.org/10.4314/njt.v40i1.16.

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In this study, we took advantage of the emergence of accurate biomechanical human hand models to develop a system in which the interaction between a human arm and a rehabilitation robot while performing a planar trajectory tracking task can be simulated. Seven biomechanical arm models were based on the 11-degree-of-freedom Dynamic Arm Simulation model and implemented in OpenSim. The model of the robot was developed in MatlabSimulink and interaction between the arm and robot models was achieved using the OpenSim API. The models were tested by simulating the performance of each model while moving the end effector of a simulated planar robot model through an elliptical trajectory with an eccentricity of 0.94. Without assistance from the robot, the average root-mean-square error (RMSE) for all subjects was 3.98 mm. With the simulated robot providing assistive torque, the average RMSE error reduced to 2.88 mm. The test was repeated after modifying the length of the robot links, and an average RMSE of 2.91 mm recorded. A single-factor ANOVA test revealed that there was no significant difference in the RMSE for the two different robot geometries (p-value = 0.479), revealing that the simulator was not sensitive to robot geometry.

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Roelker, Sarah A., Elena J. Caruthers, Rachel K. Hall, Nicholas C. Pelz, Ajit M. W. Chaudhari, and Robert A. Siston. "Effects of Optimization Technique on Simulated Muscle Activations and Forces." Journal of Applied Biomechanics 36, no. 4 (2020): 259–78. http://dx.doi.org/10.1123/jab.2018-0332.

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Two optimization techniques, static optimization (SO) and computed muscle control (CMC), are often used in OpenSim to estimate the muscle activations and forces responsible for movement. Although differences between SO and CMC muscle function have been reported, the accuracy of each technique and the combined effect of optimization and model choice on simulated muscle function is unclear. The purpose of this study was to quantitatively compare the SO and CMC estimates of muscle activations and forces during gait with the experimental data in the Gait2392 and Full Body Running models. In OpenSim (version 3.1), muscle function during gait was estimated using SO and CMC in 6 subjects in each model and validated against experimental muscle activations and joint torques. Experimental and simulated activation agreement was sensitive to optimization technique for the soleus and tibialis anterior. Knee extension torque error was greater with CMC than SO. Muscle forces, activations, and co-contraction indices tended to be higher with CMC and more sensitive to model choice. CMC’s inclusion of passive muscle forces, muscle activation-contraction dynamics, and a proportional-derivative controller to track kinematics contributes to these differences. Model and optimization technique choices should be validated using experimental activations collected simultaneously with the data used to generate the simulation.

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Tufisi, Cristian, Zeno-Iosif Praisach, Gilbert-Rainer Gillich, Andrade Ionuț Bichescu, and Teodora-Liliana Heler. "Forward Fall Detection Using Inertial Data and Machine Learning." Applied Sciences 14, no. 22 (2024): 10552. http://dx.doi.org/10.3390/app142210552.

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Fall risk assessment is becoming an important concern, with the realization that falls, and more importantly fainting occurrences, in most cases require immediate medical attention and can pose huge health risks, as well as financial and social burdens. The development of an accurate inertial sensor-based fall risk assessment tool combined with machine learning algorithms could significantly advance healthcare. This research aims to investigate the development of a machine learning approach for falling and fainting detection, using wearable sensors with an emphasis on forward falls. In the current paper we address the problem of the lack of inertial time-series data to differentiate the forward fall event from normal activities, which are difficult to obtain from real subjects. To solve this problem, we proposed a forward dynamics method to generate necessary training data using the OpenSim software, version 4.5. To develop a model as close to the real world as possible, anthropometric data taken from the literature was used. The raw X and Y axes acceleration data was generated using OpenSim software, and ML fall prediction methods were trained. The machine learning (ML) accuracy was validated by testing with data acquired from six unique volunteers, considering the forward fall type.

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Djoudi, Dalila, and Zakaria Bouzid. "Design of Matlab/Opensim Robust Controller of an Exoskeleton for Disuse Muscular Atrophy Rehabilitation of a Human Arm." Scientific Bulletin of Electrical Engineering Faculty 24, no. 2 (2024): 30–37. https://doi.org/10.2478/sbeef-2024-0018.

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Abstract The mean goal of this paper is to describe the design and control approach of an exoskeleton for rehabilitation of the disuse muscular atrophy of a human arm. This work includes three main parts: Firstly, the exoskeleton model wes design by Autodesk Inventor 3D software. Secondly, the dynamic simulation of the designed exoskeleton model attached to the human arm was performed using OpenSim software and its Matlab API extension, and finally a robust control law was simulated in order to ensure tracking of the rehabilitation trajectories applied by the exoskeleton to the human arm. OpenSim software makes it possible to simulate movements with musculoskeletal models, namely, the human arm. Rehabilitation in this case consists in a precise exercises given by the therapist. In our case, it is the repetitive trajectories given to the exoskeleton that must be controlled. A sliding mode controller was used since it is a robust control and ensures the best solutions to uncertainty issues. Through simulation, we tested some rehabilitation reference trajectories for the elbow and shoulder. The controller ensures high performances in terms of trajectory tracking in the presence of initial errors and also in the presence of model parameter errors. That showed the effectiveness of the exoskeleton control.

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Mejia Bronfield, Arlin, and Karla Miriam Reyes Leiva. "Assessing the Reliability of OpenCap and OpenSim as Open Source Softwares for Biomechanical Analysis in Neurological Rehabilitation: A Case Study." Journal of Biomimetics, Biomaterials and Biomedical Engineering 66 (September 23, 2024): 37–46. http://dx.doi.org/10.4028/p-m7j7bo.

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The neurological rehabilitation focuses on enhancing functional recovery and improving the quality of life for people who have experienced injuries or diseases affecting the central or peripheral nervous system. This functional recovery includes a follow up of the kinematics of the patients limbs. The use of a open source software such as OpenSim, has been previously proposed as a tool for kinematic analysis, this software allows for highly specialized 3D musculoskeletal modeling, facilitates kinematic analysis and the assessment of force and angles in the lower and upper limbs of the human body. In this context, the propose of this research was to test the reliability of OpenSim for kinematic analysis during neurological rehabilitation. For this goal, the Motricity Index test was done by a group of three healthy participants, this values were used for comparison to the stroke patient who is currently undergoing neurological rehabilitation process. The results demonstrates all the limitations in the range of motion of the patient in comparison to the healthy group due his motor issues, such as muscle spasticity and weakness. This research shows the advantages and limitations of this software and its application in neurological rehabilitation. The goal is to contribute to the development of effective and personalized therapeutic strategies to improve the recovery process for these patients.

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Djoudi, Dalila, and Zakaria Bouzid. "Design of Matlab/Opensim Robust Controller of an Exoskeleton for Disuse Muscular Atrophy Rehabilitation of A Human Arm." Scientific Bulletin of Electrical Engineering Faculty 23, no. 2 (2023): 34–41. http://dx.doi.org/10.2478/sbeef-2023-0017.

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Abstract The mean goal of this paper is to describe the design and control approach of an exoskeleton for rehabilitation of the disuse muscular atrophy of a human arm. This work includes three main parts: Firstly, the exoskeleton model wes design by Autodesk Inventor 3D software. Secondly, the dynamic simulation of the designed exoskeleton model attached to the human arm was performed using OpenSim software and its Matlab API extension, and finally a robust control law was simulated in order to ensure tracking of the rehabilitation trajectories applied by the exoskeleton to the human arm. OpenSim software makes it possible to simulate movements with musculoskeletal models, namely, the human arm. Rehabilitation in this case consists in a precise exercises given by the therapist. In our case, it is the repetitive trajectories given to the exoskeleton that must be controlled. A sliding mode controller was used since it is a robust control and ensures the best solutions to uncertainty issues. Through simulation, we tested some rehabilitation reference trajectories for the elbow and shoulder. The controller ensures high performances in terms of trajectory tracking in the presence of initial errors and also in the presence of model parameter errors. That showed the effectiveness of the exoskeleton control.

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Zhang, Song, Hailin Kui, Xiangyu Liu, and Zhonglin Zhang. "Analysis of Musculoskeletal Biomechanics of Lower Limbs of Drivers in Pedal-Operation States." Sensors 23, no. 21 (2023): 8897. http://dx.doi.org/10.3390/s23218897.

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In this study, to establish the biomechanical characteristics of commercial vehicle drivers’ muscles and bones while operating the three pedals, a driver pedal-operation simulator was built, and the real-life situation was reconstructed in OpenSim 3.3 software. We set up three seat heights to investigate the drivers’ lower limbs, and the research proceeded in two parts: experiment and simulation. Chinese adult males in the 95th percentile were selected as the research participants. In the experiment, Delsys wireless surface electromyography (EMG) sensors were used to collect the EMG signals of the four main muscle groups of the lower limbs when the drivers operated the three pedals. Then, we analyzed the muscle activation and the degree of muscle fatigue. The simulation was based on OpenSim software to analyze the driver’s lower limb joint angles and joint torque. The results show that the activation of the hamstrings, gastrocnemius, and rectus femoris muscles were higher in the four muscle groups. In respect of torque, in most cases, hip joint torque > knee joint torque > ankle joint torque. The knee joint angles were the largest, and the ankle joint angles changed the most. The experimental results provide a reference for improving drivers’ handling comfort in commercial vehicles and provide theoretical bases for cab design and layout optimization.

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Park, Sangsoo, Graham E. Caldwell, and Brian R. Umberger. "A direct collocation framework for optimal control simulation of pedaling using OpenSim." PLOS ONE 17, no. 2 (2022): e0264346. http://dx.doi.org/10.1371/journal.pone.0264346.

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The direct collocation (DC) method has shown low computational costs in solving optimization problems in human movements, but it has rarely been used for solving optimal control pedaling problems. Thus, the aim of this study was to develop a DC framework for optimal control simulation of human pedaling within the OpenSim modeling environment. A planar bicycle-rider model was developed in OpenSim. The DC method was formulated in MATLAB to solve an optimal control pedaling problem using a data tracking approach. Using the developed DC framework, the optimal control pedaling problem was successfully solved in 24 minutes to ten hours with different objective function weightings and number of nodes from two different initial conditions. The optimal solutions for equal objective function weightings were successful in terms of tracking, with the model simulated pedal angles and pedal forces within ±1 standard deviation of the experimental data. With these weightings, muscle tendon unit (MTU) excitation patterns generally matched with burst timings and shapes observed in the experimental EMG data. Tracking quality and MTU excitation patterns were changed little by selection of node density above 31, and the optimal solution quality was not affected by initial guess used. The proposed DC framework could easily be turned into a predictive simulation with other objective functions such as fastest pedaling rate. This flexible and computationally efficient framework should facilitate the use of optimal control methods to study the biomechanics, energetics, and control of human pedaling.

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Łysoń-Uklańska, Barbara, Michalina Błażkiewicz, Monika Kwacz, and Andrzej Wit. "Muscle Force Patterns in Lower Extremity Muscles for Elite Discus Throwers, Javelin Throwers and Shot-Putters – A Case Study." Journal of Human Kinetics 78, no. 1 (2021): 5–14. http://dx.doi.org/10.2478/hukin-2021-0026.

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Abstract Optimal release variables, as well as the kinematics and kinetics of athletes, are crucial for the maximization of throwing distance in athletics. Mathematical models and simulations allow throwing techniques to be studied. However, muscle force patterns and the contribution of specific muscle groups in athletics throwing events are not well understood and require detailed research. In this study, important variables of the muscle force generated during the javelin, discus and shot put events were determined using OpenSim software. Musculoskeletal simulations were carried out based on kinematic and kinetic data collected using the Vicon system and Kistler plates with the help of nine top Polish athletes (three in each event). OpenSim software was used to calculate muscle forces and joint velocities. For each discipline, it was found that the main muscle groups involved in the throwing movement were better at distinguishing throwers than joint velocities. The contribution of right ankle plantar flexors at the beginning of the final acceleration phase as well as left hip extensors at the end of the final acceleration phase was given special attention. This work provides a better understanding of the techniques used in athletics throws. Musculoskeletal simulations of throwing styles might help coaches analyze the techniques of individual athletes, resulting in better adjustment of training programmes and injury prevention protocols.

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Fauziah, Syifa, Jenny Zhen Wang, and Thor Besier. "The influence of scaling factors and markers’ weighting in inverse kinematics for human motion analysis." BIO Web of Conferences 166 (2025): 02005. https://doi.org/10.1051/bioconf/202516602005.

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Motion analysis can produce variability due to inconsistency in anatomical markers placements, which can lead to misdiagnosis and affect treatment outcomes. This study examined the impact of scaling and marker weighting on repeatability when acquired inverse kinematic (IK) assessment. OpenSim was used to inversely transform the motion capture outputs to assess joint angles, hip, knee, and ankle. One young-healthy participant was included, assessed by five raters. Uniform body segments parameters and different weighting schemes (equal, 10, and 100) for targeted virtual markers were set before static and dynamic data examination. Joint angles were then quantified accordingly, while the statistical analysis was used to test variability among raters. Significant differences were observed between all joint angles with equal-weighted and weighted models, particularly for the hip and knee joints. Root Mean Square Error (RMSE) values indicated notable variability in knee joint angles with a shank weight of 100 (20.23°). Hip joint angles also showed high variability across all conditions, while ankle joint angles had lower overall variability but showed moderate increment throughout gait cycle. Although all raters demonstrated strong agreement, the variability introduced by different weighting schemes highlights the need for careful markers’ weight selection to minimize error. This study demonstrates that scaling and marker weighting in OpenSim can reduce rater-dependent variability, thereby enhancing the consistency of motion capture analysis.

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Nunes, Felipe Becker, Manuel Constantino Zunguze, Fabrício Herpich, et al. "Perceptions of pre-service teachers about a Science Lab developed in OpenSim." International Journal for Innovation Education and Research 5, no. 5 (2017): 71–94. http://dx.doi.org/10.31686/ijier.vol5.iss5.675.

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With the integration of technology in the educational area, use of virtual learning environments has allowed the adoption of new practices and forms of learning. Areas like Science has an interesting field of research involving the use of Virtual worlds, being possible to integrate virtual tasks with the practical work carried out in the real world, providing features such as immersion, interactivity, virtual reality, collaboration and visualization of phenomena through animated 3D objects. This article presents a virtual world composed of three laboratories for teaching Science in elementary education, whose objective is to demonstrate how it can assist educators in the process of teaching, mixing activities of the real and virtual world. OpenSim was used for the development of the virtual world, which has several types of educational content in the format of videos, slides, texts, questions and 3D simulations of practical experiments. These prototype were tested and validated by pre-service teachers of Science in a federal institution, with the objective of evaluate the benefits and difficulty involving this approach and the resources available in this environment. The results demonstrated a wide acceptance and satisfaction in using this virtual world, showing that the users felt motivated to use in their pedagogical practice and believe that it can assist students in their learning process.

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Journal articles on the topic 'Opensim'

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