Research on Human Machine Coupling Simulation of Lower Limb Exoskeleton Robot Based on OpenSim

Research on Human Machine Coupling Simulation of Lower Limb Exoskeleton Robot Based on OpenSim | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Research on Human Machine Coupling Simulation of Lower Limb Exoskeleton Robot Based on OpenSim Chao An This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7268235/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In the field of lower limb rehabilitation and gait assistance, exoskeleton robots have gradually become an important technical means to improve walking ability. However, due to the complexity of the human body and ethical limitations, some existing experimental methods are difficult to measure the mechanical response and metabolic changes of internal muscles in the human body after wearing exoskeletons. OpenSim has sophisticated musculoskeletal modeling and mechanical analysis capabilities, capable of simulating human muscle activity and energy metabolism under exoskeleton intervention. This article adopts the Gait2354 model in OpenSim to construct a human-machine coupling system combined with lower limb exoskeleton structure, and uses the walking data provided by OpenSim for simulation analysis. By comparing the changes in muscle force during walking before and after wearing exoskeletons, the assistive effect of the designed exoskeleton structure is evaluated to verify the structural design rationality of the lower limb exoskeleton robot designed in this article. OpenSim Exoskeleton Human-Machine coupling Muscle force Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction OpenSim is an open-source software developed by Stanford University for modeling, simulation, and analysis of musculoskeletal systems. It allows users to build musculoskeletal models and analyze the effects on them under different conditions. In recent years, it has been widely used in the field of exoskeleton research[ 1 ].Feng Bolin's[ 2 ]team at the Northwest Institute of Mechanical and Electrical Engineering established a human-machine coupling model of flexible lower limb exoskeletons through OpenSim. They compared the single joint and multi joint assistance effects and found that ankle joint assistance schemes can significantly reduce energy consumption and muscle burden during human walking.Han Hong[ 3 ] from Nankai University analyzed joint torque and metabolic energy consumption at different speeds and slopes using OpenSim, constructed a cost function based on muscle activity, and optimized ankle exoskeleton assistance parameters using particle swarm optimization algorithm to achieve personalized gait adaptation.The team led by Shi Chuanqi[ 4 ] from Nanjing University of Engineering used OpenSim to build a lower limb exoskeleton robot and musculoskeletal model, and studied the average muscle activation level and joint output torque of muscle groups before and after wearing exoskeletons.Christopher L.Dembia [ 5 ] used the OpenSim musculoskeletal model to predict how hypothetical devices affect muscle activity and metabolic costs during weight-bearing walking. The research results showed that hip flexion, knee flexion, and hip abduction wearable robotic devices can reduce metabolic energy.OpenSim plays an increasingly important role in exoskeleton simulation optimization and has become the core platform for optimizing design, verifying performance, and expanding application scenarios in exoskeleton development. 2. Design of lower limb exoskeleton based on pneumatic muscle drive Pneumatic flexible joint is a type of joint that utilizes pneumatic elastic elements such as PAM for driving, multiple PAMs are used to simulate the structure of organism. The antagonistic pneumatic flexible joint is shown in Fig. 1 , which has the characteristics of simple structure, mechanical flexibility, and a large load/self weight ratio [ 6 , 7 ]. In this paper, four groups of antagonistic pneumatic flexible joints are used to drive the hip and knee joints of the lower limb respectively. The designed structure is shown in Fig. 2 . 3. Modeling and simulation implementation of lower limb exoskeleton human-machine coupling The coupling simulation of human-machine systems in the OpenSim environment is mainly divided into two typical coupling forms: forward coupling strategy and reverse coupling strategy. Forward coupling strategy: setting the exoskeleton system as the dominant mechanism, driving the entire human-machine system forward by controlling the motion trajectory of each joint of the exoskeleton, while the human musculoskeletal model serves as the passive structure, generating corresponding responses based on the actions of the exoskeleton. Reverse coupling strategy: With a muscle driven human body model as the core, autonomous movement of the human body is achieved through muscle activation control, and the motion rules that the exoskeleton system should cooperate with are derived [ 1 , 8 ].The coupling strategy adopted in this article is forward coupling, which focuses on assisting the human body in completing gait by actively controlling the motion of the exoskeleton robot, thereby achieving the goal of reducing muscle energy consumption and alleviating exercise burden. In this mode, the exoskeleton system takes on the driving task, while the human model presents a passive response state. To construct a forward coupled dynamic model, in OpenSim, the rigid structure of the exoskeleton needs to be set as the parent body, while the relevant bone segments in the musculoskeletal model are bound and coupled as child bodies to achieve effective connection between motion and power transmission. This article uses the standard model Gait2354 provided by OpenSim software as the simulated lower limb model of the human body. This model is based on a healthy adult male who is approximately 1.80 meters tall and weighs 75 kilograms. It has 23 degrees of freedom and 54 muscle tendon units, and can comprehensively simulate the main muscle groups that control lower limb movement, such as rectus femoris, lateral femoris, medial femoris, semimembranosus, etc. For the simulation object of this article, an individual with a height of about 175cm, reference is made to the typical human body size ratio data in the "Chinese Adult Human Body Size Standards" [ 9 ], and proportional adjustments are made to ensure that the skeletal structure is consistent with the target wearer's body shape during the simulation process. The final coupled model is shown in Fig. 3 . The purpose of Computed Muscle Control (CMC) is to calculate a set of muscle excitation points, enabling a dynamic musculoskeletal model to track the expected action under a given external force. It is achieved through a combination of proportional derivative (PD) control and static optimization. After the establishment of the human-machine coupling model, the gait2354 gait dataset provided in OpenSim can be imported, and then the CMC calculation task can be executed. During this process, the system will automatically adjust the activation levels of each muscle to track the input target motion trajectory as accurately as possible. In the simulation visualization interface, the color depth of muscles will dynamically reflect the current activation level, intuitively presenting the load status of muscles. The dynamic process of CMC simulation is shown in Fig. 4 . 4. Analysis of lower limb muscle force 4.1 Distribution of lower limb muscles in the human body The lower limb muscle groups of the human body mainly include knee extensor muscle group, knee flexor muscle group, dorsal flexor muscle group, and plantar flexor muscle group[ 10 ].The knee extensor muscle group mainly undertakes the stretching movement of the knee, and is composed of rectus femoris, vastus lateralis muscle, vastus medial muscle, and vastus intermedius muscle. The knee flexion muscles control knee flexion, mainly including semitendinosus and semimembranosus. The dorsal flexor muscle group is mainly responsible for controlling the upward movement of the foot, including the tibialis anterior muscle, extensor digitorum longus muscle, etc. Among them, the tibialis anterior muscle is the most important muscle in the dorsal flexor muscle group. The plantar flexor muscle group is responsible for the plantar flexion movement of the ankle joint, which involves pressing the toe downwards and lifting the heel, mainly including the gastrocnemius, soleus, the tibialis posterior muscles, among which the gastrocnemius and soleus are the main force producing muscles. The distribution of muscles in the lower limbs of the human body is shown in Fig. 5 . 4.2 Analysis of simulation results of lower limb muscle force Due to the symmetry of the left and right legs of the human body, this article selects the muscle of the right leg as the analysis object. There are two curves in the simulation result graph, representing the data fitting when wearing exoskeletons (Exo) and when not wearing lower limb exoskeletons (No-Exo), corresponding to Exo and No-Exo in the graph. The muscle force simulation results of the main muscles in the lower limbs are shown in Fig. 6. From the muscle force curves shown in Figs. 6 (a), (b), and (d), it can be seen that after wearing the lower limb exoskeleton during the gait cycle, the peak muscle forces of rectus femoris (Figure a), vastus intermedius muscle (Figure b), and vastus medial muscle (Figure d) in the human model decreased by approximately 52.22%, 14.29%, and 47.5%, respectively. This indicates that during walking, the exoskeleton provides torque compensation to the knee extensor muscle group, effectively reducing the muscle force of this muscle group. The peak of vastus lateralis muscle (Figure c) showed a slight increase compared to when no exoskeleton was worn, with an increase of about 7.03%. The increase in muscle strength is due to the lack of proper support provided in the lateral direction of the stabilizing knee joint, resulting in an increase in force exerted by the vastus lateralis muscle to maintain knee joint stability. From the muscle force curves shown in (e) and (f) of Fig. 6, it can be seen that under the condition of wearing lower limb exoskeletons, the muscle forces of semimembranosus (Figure e) and semitendinosus (Figure f) both show a significant decrease, with peak muscle forces decreasing by about 58.67% and 68.16% respectively compared to the non wearing state. This indicates that exoskeletons play a significant assisting role in knee flexion movements. From the muscle force curve shown in Fig. 6 (g), it can be seen that the maximum muscle force of the tibialis anterior muscle decreased by about 55.51%, indicating that the exoskeleton effectively shared the load of this muscle group during dorsiflexion. From Figs. 6 (h), (i), and (j), it can be seen that the peak muscle forces of the medial head of gastrocnemius (Figure h), lateral head of gastrocnemius (Figure i), and soleus (Figure j) decreased by approximately 52.22%, 17.29%, and 16.25%, respectively, indicating that the exoskeleton effectively shared the load of the main plantar flexor muscles during the gait pedaling phase, significantly reducing their mechanical burden. 5. Conclusion This paper uses the Gait2354 model in OpenSim to construct a human-machine coupling system combined with lower limb exoskeleton structures. Through simulation analysis on the OpenSim platform, it was found that after wearing the lower limb exoskeleton, the peak muscle force of the main muscles in the lower limb muscle group decreased to varying degrees. Among them, rectus femoris muscle strength decreased by about 52.22%, vastus intermedius muscle strength decreased by about 14.29%, vastus medial muscle strength decreased by about 47.5%, semimembranosus muscle strength decreased by about 58.67%, semitendinosus muscle strength decreased by about 68.16%, tibialis anterior muscle strength decreased by about 55.51%, medial head of gastrocnemius muscle strength decreased by about 52.22%, lateral head of gastrocnemius muscle strength decreased by about 17.29%, and soleus muscle strength decreased by about 16.25%. From the data, it can be seen that after wearing the exoskeleton, the muscle peak values of most muscles significantly decreased, reaching up to 68.16%. The analysis results indicate that the design of the lower limb exoskeleton robot is relatively reasonable and has good assistance effect. Relatively speaking, the muscle strength of Vastus lateralis muscle showed a slight increase, with an increase of about 7.03%. Through analysis, it was found that this was due to the lack of reasonable support provided in the lateral direction of stabilizing the knee joint, resulting in the Vastus Lateralis muscle increasing its force to maintain knee joint stability. The analysis results also provide a basis for further optimizing the lower limb exoskeleton robot. Declarations Conflicts of Interest: The authors declare no conflicts of interest. Clinical trial number not applicable. Ethics, Consent to Participate, and Consent to Publish declarations not applicable. Funding: The Article Processing Charges for this article are taken in charge by the Science and Technology Research Program of the Chongqing Municipal Education Commission (Grant No. KJQN202201336). Author Contribution An Chao completed the thesis writing and all simulations and charts. I declare: The figures in the manuscript are fully compliant with requirements. Detailed information of the submitting authors, including their institutional affiliations, has been provided. This paper contains no experiments involving live subjects, ethical issues, or related concerns. There exist no conflicts of interest whatsoever. Acknowledgement I declare: The figures in the manuscript are fully compliant with requirements. Detailed information of the submitting authors, including their institutional affiliations, has been provided. This paper contains no experiments involving live subjects, ethical issues, or related concerns. There exist no conflicts of interest whatsoever. Data Availability Statement: The data presented in this study are available on request from the corresponding author. References Pu Sixian Biomimetic design and performance research of assistive lower limb exoskeleton [D]. National University of Defense Technology, 2022. Feng Bolin; Song Peng; Li Ruiyuan, wait Design and simulation analysis of flexible lower limb assistive exoskeleton based on OpenSim [J]. Mechanical Transmission, 2024, 48 (05): 62-66. Han Hong Optimization of ankle exoskeleton assisted "human in the loop" under multi gait [D]. Nankai University, 2022. Shi Chuanqi, Han Yali, Chang Jiachen, etc Simulation research on lower limb exoskeleton robot based on OpenSim [J] Journal of Nanjing University of Engineering (Natural Science Edition), 2022, 20 (2): 45-49. Dembia C L, Silder A, Uchida T K, et al. Simulating ideal assistive devices to reduce the metabolic cost of walking with heavy loads[J]. Plos ONE, 2017, 12(7):180-190. Tan Hongwei. Research on antagonistic bionic joint based on pneumatic tendon [D]. Harbin Institute of Technology, 2011. Sui Liming,Zhang Lixun. Research on pneumatic muscle driven exoskeleton device for gait rehabilitation training [J]. Journal of Harbin Engineering University, 2011, 32 (9): 1244-1248. Zhou Rui .Kinematics Analysis and Simulation of Human-machine Coupled Lower Extremity Exoskeleton Robot[D].Lanzhou University of Technology,2020. GB 10000-88, Chinese adult body size [S]. Andrew Bell Complete Book of Human Motor Anatomy [M]. Maple Leaf Society Cultural Publishing House, 2016. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7268235","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":502733617,"identity":"5c1f09a6-a9b0-4889-958b-958fcca2ebbe","order_by":0,"name":"Chao An","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYHACNiC2QWITqSWNdC2HSdDCP7v52YMfFefl+W7kGDB8KDsMFGnAr0XizjFzw54ztw1nArUwzjh3GChygIA1N3LYJHjbbicY3M4xYOZtO8xgIJGAX4c8UIvk37ZzEC1/idFiANQizdt2AKKFkRgthjfSzKRlziQbzrz/rOBgz7l0HokbBLTI3Uh+Jvmmwk6e78zhjQ9+lFnL8c8goAUBDoARAw+x6iFaRsEoGAWjYBRgBQApbELx4Bom1wAAAABJRU5ErkJggg==","orcid":"","institution":"Chongqing University of Arts and Sciences","correspondingAuthor":true,"prefix":"","firstName":"Chao","middleName":"","lastName":"An","suffix":""}],"badges":[],"createdAt":"2025-08-01 07:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7268235/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7268235/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89480080,"identity":"cd6593cc-ec93-4abd-ba02-01c6c8f9e22a","added_by":"auto","created_at":"2025-08-20 11:38:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36118,"visible":true,"origin":"","legend":"\u003cp\u003eAntagonistic pneumatic flexible joint.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7268235/v1/3e21f668d1d5670e445f2cb0.png"},{"id":89480060,"identity":"1778e376-ad28-4226-96d9-680145cb1b13","added_by":"auto","created_at":"2025-08-20 11:38:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":69860,"visible":true,"origin":"","legend":"\u003cp\u003eLower limb exoskeleton robot structure. 1. Foot support; 2. Lower leg member; 3. Ankle rotation device; 4. Lower leg member; 5. Knee joint rotation device; 6. Leg member; 7. Hip joint rotation device; 8. Back frame; 9. Lumbar connector; 10. Pneumatic muscle\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7268235/v1/ef7df747de43dbb5fae8d040.png"},{"id":89480029,"identity":"c2306624-72ef-402f-8bd4-664250ffc2ce","added_by":"auto","created_at":"2025-08-20 11:38:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":320735,"visible":true,"origin":"","legend":"\u003cp\u003eHuman machine coupling model\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7268235/v1/0a2922acf09f889d9485c7d8.png"},{"id":89480017,"identity":"b18f746f-539f-4f73-8403-0e4bf8ae9eeb","added_by":"auto","created_at":"2025-08-20 11:38:48","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":113343,"visible":true,"origin":"","legend":"\u003cp\u003eCMC simulation process\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7268235/v1/e4c69c87f7a05f4abfead24f.jpeg"},{"id":89480067,"identity":"37254c52-fb3f-467f-9974-c8d416fc3e3f","added_by":"auto","created_at":"2025-08-20 11:38:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":341847,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of muscle distribution in the lower limbs of the human body\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7268235/v1/b788f281368ecf869dc38c9b.png"},{"id":89480082,"identity":"e3bb7fc4-18b3-44e8-b828-f6ba1ef7ff05","added_by":"auto","created_at":"2025-08-20 11:38:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":286170,"visible":true,"origin":"","legend":"\u003cp\u003eSimulation results of main muscle forces in lower limb muscle groups\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7268235/v1/f349dfc14d87c8721249878a.png"},{"id":91481326,"identity":"d54c78ae-b885-43ca-891b-e990591881d0","added_by":"auto","created_at":"2025-09-17 03:17:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1723045,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7268235/v1/e61bb676-bb65-46a4-af5a-49abbd123bde.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on Human Machine Coupling Simulation of Lower Limb Exoskeleton Robot Based on OpenSim","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOpenSim is an open-source software developed by Stanford University for modeling, simulation, and analysis of musculoskeletal systems. It allows users to build musculoskeletal models and analyze the effects on them under different conditions. In recent years, it has been widely used in the field of exoskeleton research[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].Feng Bolin's[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]team at the Northwest Institute of Mechanical and Electrical Engineering established a human-machine coupling model of flexible lower limb exoskeletons through OpenSim. They compared the single joint and multi joint assistance effects and found that ankle joint assistance schemes can significantly reduce energy consumption and muscle burden during human walking.Han Hong[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] from Nankai University analyzed joint torque and metabolic energy consumption at different speeds and slopes using OpenSim, constructed a cost function based on muscle activity, and optimized ankle exoskeleton assistance parameters using particle swarm optimization algorithm to achieve personalized gait adaptation.The team led by Shi Chuanqi[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] from Nanjing University of Engineering used OpenSim to build a lower limb exoskeleton robot and musculoskeletal model, and studied the average muscle activation level and joint output torque of muscle groups before and after wearing exoskeletons.Christopher L.Dembia [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] used the OpenSim musculoskeletal model to predict how hypothetical devices affect muscle activity and metabolic costs during weight-bearing walking. The research results showed that hip flexion, knee flexion, and hip abduction wearable robotic devices can reduce metabolic energy.OpenSim plays an increasingly important role in exoskeleton simulation optimization and has become the core platform for optimizing design, verifying performance, and expanding application scenarios in exoskeleton development.\u003c/p\u003e"},{"header":"2. Design of lower limb exoskeleton based on pneumatic muscle drive","content":"\u003cp\u003ePneumatic flexible joint is a type of joint that utilizes pneumatic elastic elements such as PAM for driving, multiple PAMs are used to simulate the structure of organism. The antagonistic pneumatic flexible joint is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, which has the characteristics of simple structure, mechanical flexibility, and a large load/self weight ratio [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In this paper, four groups of antagonistic pneumatic flexible joints are used to drive the hip and knee joints of the lower limb respectively. The designed structure is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"3. Modeling and simulation implementation of lower limb exoskeleton human-machine coupling","content":"\u003cp\u003eThe coupling simulation of human-machine systems in the OpenSim environment is mainly divided into two typical coupling forms: forward coupling strategy and reverse coupling strategy. Forward coupling strategy: setting the exoskeleton system as the dominant mechanism, driving the entire human-machine system forward by controlling the motion trajectory of each joint of the exoskeleton, while the human musculoskeletal model serves as the passive structure, generating corresponding responses based on the actions of the exoskeleton. Reverse coupling strategy: With a muscle driven human body model as the core, autonomous movement of the human body is achieved through muscle activation control, and the motion rules that the exoskeleton system should cooperate with are derived [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].The coupling strategy adopted in this article is forward coupling, which focuses on assisting the human body in completing gait by actively controlling the motion of the exoskeleton robot, thereby achieving the goal of reducing muscle energy consumption and alleviating exercise burden. In this mode, the exoskeleton system takes on the driving task, while the human model presents a passive response state. To construct a forward coupled dynamic model, in OpenSim, the rigid structure of the exoskeleton needs to be set as the parent body, while the relevant bone segments in the musculoskeletal model are bound and coupled as child bodies to achieve effective connection between motion and power transmission.\u003c/p\u003e\u003cp\u003eThis article uses the standard model Gait2354 provided by OpenSim software as the simulated lower limb model of the human body. This model is based on a healthy adult male who is approximately 1.80 meters tall and weighs 75 kilograms. It has 23 degrees of freedom and 54 muscle tendon units, and can comprehensively simulate the main muscle groups that control lower limb movement, such as rectus femoris, lateral femoris, medial femoris, semimembranosus, etc. For the simulation object of this article, an individual with a height of about 175cm, reference is made to the typical human body size ratio data in the \"Chinese Adult Human Body Size Standards\" [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and proportional adjustments are made to ensure that the skeletal structure is consistent with the target wearer's body shape during the simulation process. The final coupled model is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe purpose of Computed Muscle Control (CMC) is to calculate a set of muscle excitation points, enabling a dynamic musculoskeletal model to track the expected action under a given external force. It is achieved through a combination of proportional derivative (PD) control and static optimization. After the establishment of the human-machine coupling model, the gait2354 gait dataset provided in OpenSim can be imported, and then the CMC calculation task can be executed. During this process, the system will automatically adjust the activation levels of each muscle to track the input target motion trajectory as accurately as possible. In the simulation visualization interface, the color depth of muscles will dynamically reflect the current activation level, intuitively presenting the load status of muscles. The dynamic process of CMC simulation is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"4. Analysis of lower limb muscle force","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1 Distribution of lower limb muscles in the human body\u003c/h2\u003e\n \u003cp\u003eThe lower limb muscle groups of the human body mainly include knee extensor muscle group, knee flexor muscle group, dorsal flexor muscle group, and plantar flexor muscle group[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e].The knee extensor muscle group mainly undertakes the stretching movement of the knee, and is composed of rectus femoris, vastus lateralis muscle, vastus medial muscle, and vastus intermedius muscle. The knee flexion muscles control knee flexion, mainly including semitendinosus and semimembranosus. The dorsal flexor muscle group is mainly responsible for controlling the upward movement of the foot, including the tibialis anterior muscle, extensor digitorum longus muscle, etc. Among them, the tibialis anterior muscle is the most important muscle in the dorsal flexor muscle group. The plantar flexor muscle group is responsible for the plantar flexion movement of the ankle joint, which involves pressing the toe downwards and lifting the heel, mainly including the gastrocnemius, soleus, the tibialis posterior muscles, among which the gastrocnemius and soleus are the main force producing muscles. The distribution of muscles in the lower limbs of the human body is shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2 Analysis of simulation results of lower limb muscle force\u003c/h2\u003e\n \u003cp\u003eDue to the symmetry of the left and right legs of the human body, this article selects the muscle of the right leg as the analysis object. There are two curves in the simulation result graph, representing the data fitting when wearing exoskeletons (Exo) and when not wearing lower limb exoskeletons (No-Exo), corresponding to Exo and No-Exo in the graph. The muscle force simulation results of the main muscles in the lower limbs are shown in Fig.\u0026nbsp;6.\u003c/p\u003e\n \u003cp\u003eFrom the muscle force curves shown in Figs. 6 (a), (b), and (d), it can be seen that after wearing the lower limb exoskeleton during the gait cycle, the peak muscle forces of rectus femoris (Figure a), vastus intermedius muscle (Figure b), and vastus medial muscle (Figure d) in the human model decreased by approximately 52.22%, 14.29%, and 47.5%, respectively. This indicates that during walking, the exoskeleton provides torque compensation to the knee extensor muscle group, effectively reducing the muscle force of this muscle group. The peak of vastus lateralis muscle (Figure c) showed a slight increase compared to when no exoskeleton was worn, with an increase of about 7.03%. The increase in muscle strength is due to the lack of proper support provided in the lateral direction of the stabilizing knee joint, resulting in an increase in force exerted by the vastus lateralis muscle to maintain knee joint stability. From the muscle force curves shown in (e) and (f) of Fig. 6, it can be seen that under the condition of wearing lower limb exoskeletons, the muscle forces of semimembranosus (Figure e) and semitendinosus (Figure f) both show a significant decrease, with peak muscle forces decreasing by about 58.67% and 68.16% respectively compared to the non wearing state. This indicates that exoskeletons play a significant assisting role in knee flexion movements. From the muscle force curve shown in Fig. 6 (g), it can be seen that the maximum muscle force of the tibialis anterior muscle decreased by about 55.51%, indicating that the exoskeleton effectively shared the load of this muscle group during dorsiflexion. From Figs. 6 (h), (i), and (j), it can be seen that the peak muscle forces of the medial head of gastrocnemius (Figure h), lateral head of gastrocnemius (Figure i), and soleus (Figure j) decreased by approximately 52.22%, 17.29%, and 16.25%, respectively, indicating that the exoskeleton effectively shared the load of the main plantar flexor muscles during the gait pedaling phase, significantly reducing their mechanical burden.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis paper uses the Gait2354 model in OpenSim to construct a human-machine coupling system combined with lower limb exoskeleton structures. Through simulation analysis on the OpenSim platform, it was found that after wearing the lower limb exoskeleton, the peak muscle force of the main muscles in the lower limb muscle group decreased to varying degrees. Among them, rectus femoris muscle strength decreased by about 52.22%, vastus intermedius muscle strength decreased by about 14.29%, vastus medial muscle strength decreased by about 47.5%, semimembranosus muscle strength decreased by about 58.67%, semitendinosus muscle strength decreased by about 68.16%, tibialis anterior muscle strength decreased by about 55.51%, medial head of gastrocnemius muscle strength decreased by about 52.22%, lateral head of gastrocnemius muscle strength decreased by about 17.29%, and soleus muscle strength decreased by about 16.25%. From the data, it can be seen that after wearing the exoskeleton, the muscle peak values of most muscles significantly decreased, reaching up to 68.16%. The analysis results indicate that the design of the lower limb exoskeleton robot is relatively reasonable and has good assistance effect. Relatively speaking, the muscle strength of Vastus lateralis muscle showed a slight increase, with an increase of about 7.03%. Through analysis, it was found that this was due to the lack of reasonable support provided in the lateral direction of stabilizing the knee joint, resulting in the Vastus Lateralis muscle increasing its force to maintain knee joint stability. The analysis results also provide a basis for further optimizing the lower limb exoskeleton robot.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflicts of Interest:\u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eClinical trial number\u003c/h2\u003e\n\u003cp\u003enot applicable.\u003c/p\u003e\n\u003ch2\u003eEthics, Consent to Participate, and Consent to Publish declarations\u003c/h2\u003e\n\u003cp\u003enot applicable.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThe Article Processing Charges for this article are taken in charge by the Science and Technology Research Program of the Chongqing Municipal Education Commission (Grant No. KJQN202201336).\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAn Chao completed the thesis writing and all simulations and charts. I declare: The figures in the manuscript are fully compliant with requirements. Detailed information of the submitting authors, including their institutional affiliations, has been provided. This paper contains no experiments involving live subjects, ethical issues, or related concerns. There exist no conflicts of interest whatsoever.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eI declare: The figures in the manuscript are fully compliant with requirements. Detailed information of the submitting authors, including their institutional affiliations, has been provided. This paper contains no experiments involving live subjects, ethical issues, or related concerns. There exist no conflicts of interest whatsoever.\u003c/p\u003e\n\u003ch2\u003eData Availability Statement:\u003c/h2\u003e\n\u003cp\u003eThe data presented in this study are available on request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePu Sixian Biomimetic design and performance research of assistive lower limb exoskeleton [D]. National University of Defense Technology, 2022.\u003c/li\u003e\n\u003cli\u003eFeng Bolin; Song Peng; Li Ruiyuan, wait Design and simulation analysis of flexible lower limb assistive exoskeleton based on OpenSim [J]. Mechanical Transmission, 2024, 48 (05): 62-66.\u003c/li\u003e\n\u003cli\u003eHan Hong Optimization of ankle exoskeleton assisted \u0026quot;human in the loop\u0026quot; under multi gait [D]. Nankai University, 2022.\u003c/li\u003e\n\u003cli\u003eShi Chuanqi, Han Yali, Chang Jiachen, etc Simulation research on lower limb exoskeleton robot based on OpenSim [J] Journal of Nanjing University of Engineering (Natural Science Edition), 2022, 20 (2): 45-49.\u003c/li\u003e\n\u003cli\u003eDembia C L, Silder A, Uchida T K, et al. Simulating ideal assistive devices to reduce the metabolic cost of walking with heavy loads[J]. Plos ONE, 2017, 12(7):180-190.\u003c/li\u003e\n\u003cli\u003eTan Hongwei. Research on antagonistic bionic joint based on pneumatic tendon [D]. Harbin Institute of Technology, 2011.\u003c/li\u003e\n\u003cli\u003eSui Liming,Zhang Lixun. Research on pneumatic muscle driven exoskeleton device for gait rehabilitation training [J]. Journal of Harbin Engineering University, 2011, 32 (9): 1244-1248.\u003c/li\u003e\n\u003cli\u003eZhou Rui .Kinematics Analysis and Simulation of Human-machine Coupled Lower Extremity Exoskeleton Robot[D].Lanzhou University of Technology,2020.\u003c/li\u003e\n\u003cli\u003eGB 10000-88, Chinese adult body size [S].\u003c/li\u003e\n\u003cli\u003eAndrew Bell Complete Book of Human Motor Anatomy [M]. Maple Leaf Society Cultural Publishing House, 2016.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"OpenSim, Exoskeleton, Human-Machine coupling, Muscle force","lastPublishedDoi":"10.21203/rs.3.rs-7268235/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7268235/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the field of lower limb rehabilitation and gait assistance, exoskeleton robots have gradually become an important technical means to improve walking ability. However, due to the complexity of the human body and ethical limitations, some existing experimental methods are difficult to measure the mechanical response and metabolic changes of internal muscles in the human body after wearing exoskeletons. OpenSim has sophisticated musculoskeletal modeling and mechanical analysis capabilities, capable of simulating human muscle activity and energy metabolism under exoskeleton intervention. This article adopts the Gait2354 model in OpenSim to construct a human-machine coupling system combined with lower limb exoskeleton structure, and uses the walking data provided by OpenSim for simulation analysis. By comparing the changes in muscle force during walking before and after wearing exoskeletons, the assistive effect of the designed exoskeleton structure is evaluated to verify the structural design rationality of the lower limb exoskeleton robot designed in this article.\u003c/p\u003e","manuscriptTitle":"Research on Human Machine Coupling Simulation of Lower Limb Exoskeleton Robot Based on OpenSim","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-20 11:38:36","doi":"10.21203/rs.3.rs-7268235/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"418d989c-c7ca-4d32-bbc7-df9ce32aa12a","owner":[],"postedDate":"August 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-17T03:08:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-20 11:38:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7268235","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7268235","identity":"rs-7268235","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}