Validation of a Spine Musculoskeletal Model During Submaximal Heavy Lifting in OpenSim

Validation of a Spine Musculoskeletal Model During Submaximal Heavy Lifting in 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 Validation of a Spine Musculoskeletal Model During Submaximal Heavy Lifting in OpenSim Amir Sadeghi Golafzani, Raghad Mimar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8063259/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 Low back pain is a significant health issue with substantial societal costs. Manual handling guidelines often prove impractical in certain occupations. Musculoskeletal modeling plays a crucial role in assessing injury risks, but gaps remain in understanding spinal injuries and muscle activity under heavy loads. OpenSim software has advanced from spine-specific to full-body models, with recent enhancements to the fully articulated thoracolumbar spine model validated for small load tasks. This study aims to validate the model for submaximal heavy lifting in athletes. Sixteen young male participants performed Conventional and Romanian Deadlift tasks. Trunk muscle activity was measured experimentally and compared with model predictions using metrics like Root Mean Square Error (RMSE), Maximum Absolute Normalized Cross-Correlation (MANCC), and Pearson Correlation. The results demonstrated strong temporal similarity and high prediction accuracy, with a robust linear relationship between experimental and model data. This validates the model for submaximal lifting tasks, providing insights into athletic performance and heavy lifting scenarios. Spine OpenSim Lifting Validation Musculoskeletal Modeling Figures Figure 1 Figure 2 Figure 3 Introduction Low Back Pain (LBP) is a global health challenge with significant clinical and economic implications (Balagué et al., 2012 ). In the U.S., annual costs associated with LBP are estimated at $ 100–200 billion, comparable to the economic impact of Hurricane Katrina (Katz, 2006 ). Weightlifters frequently experience back pain, often attributed to squat and deadlift techniques(Ross et al., 2023 ). Conventional Deadlift (DL), Romanian Deadlift (RDL), and squat techniques are foundational in athletic training programs. Hence, lumbar-straining postures are common in sports, and manual load handling (MLH) guidelines are impractical (Waters et al., 1993 ).Understanding spinal loads is critical for optimizing lifting techniques (Jäger and Luttmann, 1989 ), assessing injury risks (Ramirez et al., 2023 ), and evaluating the cost-benefit of athlete preparation and physical activities(Gabbett et al., 2016 ). Direct measurements of spinal loads using invasive methods, such as intradiscal pressure (Wilke et al., 1999 ) and implanted strain gauges (Rohlmann et al., 2007 ), face limitations, underscoring the need for non-invasive musculoskeletal (MSK) modeling techniques(Dreischarf et al., 2016 ). Despite computational advancements, research on near-maximal external loads remains limited, raising concerns about estimation accuracy (Ramirez et al., 2022 ). MSK modeling requires detailed muscle property data, yet athlete-specific data and imaging evaluations are scarce(Anderson et al., 2012 ). Many studies omit muscle activity (Eltoukhy et al., 2015 ; Swinton et al., 2011 ), simplify muscle representations (Cholewicki et al., 1991 ), or rely on kinematics-driven methods (Ramirez et al., 2023 ). Fully dynamic multibody approaches remain underexplored. OpenSim, an open-source MSK modeling tool, has become integral in the past two decades (Delp et al., 2007 ). It supports inverse dynamics analysis (Winter, 2009 ), muscle force estimation based on muscle properties )Thelen, 2003 ; Zajac, 1989 (, and dynamic equilibrium optimization (Erdemir et al., 2007 ). Full-body spine models for lifting tasks have been validated in recent years (Beaucage-Gauvreau et al., 2019 ; Bruno et al., 2015 ) Model accuracy depends on measurement limitations and task-specific validation (Hicks et al., 2015 ) Validation approaches for spinal models include comparing measured in vivo loads with model predictions(Akhavanfar et al., 2023 ; Bruno et al., 2015 ) and comparing recorded surface activity (Alemi et al., 2023 ). The Fully Articulated Thoracolumbar Spine Model has been tested under static lifting conditions(Bruno et al., 2015 ) and dynamic daily activities (Alemi et al., 2023 ), This model was enhanced in kinematics and kinetics and validated using a novel method that correlates time-series data from implanted sensors with estimated forces(Akhavanfar et al., 2023 ). but validation for Submaximal Heavy Lifting (SHL) tasks is lacking. This study validates the Enhanced Fully Articulated Thoracolumbar Spine Model (EFALTS) for DL and RDL tasks under SHL conditions in young, active men. Materials and Methods Data collection Sixteen young men (age: 26 ± 3 years; weight: 82.5 ± 2.75 kg; height: 187 ± 5 cm) experienced in DL and RDL tasks participated. Physical readiness was confirmed via an ACSM questionnaire(Medicine et al., 2006 ). Participants with no vertebral surgery, fractures, or LBP in the past year were included. Radiographic imaging confirmed normal spinal anatomy and measured lumbar lordosis angles. DL and RDL movements were performed with minimal clothing and a standard 15 kg barbell. Rest periods of at least 5 minutes ensured recovery between trials. The task cycle involved lifting the barbell from a squat to standing and returning. Loads of 15 kg, 45 kg, 75 kg, and 105 kg (< 85% 1RM) were used. Kinematic and kinetic data were captured using eight motion capture cameras (MXF-20, Vicon), two force plates (BP400600, AMTI), and a wireless EMG system (Myon AG). Reflective markers were placed on body segments )Beaucage-Gauvreau et al., 2019 (. EMG signals and force plate data were sampled at 1000 Hz; kinematic data were sampled at 100 Hz. Bilateral EMG sensors were placed on six muscles: longissimus erector spinae, iliocostalis erector spinae, multifidus, external oblique, rectus abdominis, and internal oblique (Arjmand et al., 2009 ). Electrodes were applied using SF07 adhesive following skin preparation(Tankisi et al., 2020 ). EMG data were normalized using maximal voluntary isometric contraction (MVC) tests for flexors and extensors(Vera-Garcia et al., 2010 ). Data processing Signals were filtered using a Butterworth band-pass filter (20–450 Hz, 6th order) to remove noise and minimize skin artifacts. No significant power line or ECG interference was detected; therefore, no additional filtering was applied. Signals were full-wave rectified, low-pass filtered at 3 Hz (6th order) to obtain the linear envelope, and normalized to MVC values. Inverse dynamics and static optimization were performed in OpenSim 4.3 using the EFALTS model. Models were scaled based on anatomical markers. The mass load is added to each arm as half of the external load. (Akhavanfar et al., 2023 ). Muscle maximum stress was adjusted to 1.4 MPa for young individuals (Beaucage-Gauvreau et al., 2019 ). Spinal curvature was defined using radiographic data in the sagittal plane. We assumed participants would maintain the same spinal arc observed in the standing position during the DL and RDL movements. Muscle activity predictions minimized cubic muscle activity sums while accounting for force-length-velocity relationships. The average fascicle activity was used to represent muscle activity. Muscle activity estimates were unfiltered to match the model’s resolution. Statistical Statistical Analysis Predicted muscle activities were compared with experimental EMG data using four metrics: Pearson Correlation Coefficient, Root Mean Square Error (RMSE), Maximum Absolute Normalized Cross-Correlation (MANCC), and Fisher’s Z Transformation. Statistical analyses were conducted in MATLAB R2023b. Result Figure 1 shows RMSE values, averaging 0.076 for DL and 0.074 for RDL, indicating high model accuracy (~ 10% error). Figure 2 presents MANCC heatmaps, showing strong temporal similarity (values > 0.9) and moderate similarity (0.7–0.9). Posterior muscles exhibited higher similarity than anterior muscles. Figure 3 illustrates Pearson correlation heatmaps, with moderate correlations (0.7–0.9) for posterior muscles. RDL at 105 kg showed values < 0.7. Table 1 summarizes prediction errors, temporal similarity, and correlation differences. Fisher’s Z-transformation averaged correlations. Table 2 presents the peak forces exerted on the lumbosacral joint during DL and RDL across various load conditions. Table 1 Mean MANCC and Pearson Correlation (adjusted using Fisher's Z) alongside the mean and standard deviation of RMSE Task Muscle Group RMSE (MEAN ± SD) MANCC Pearson Correlation (r) Conventional Deadlift Posterior 0.11 ± 0.01 0.93 0.77 Anterior 0.05 ± 0.07 0.93 -0.061 Romanian Deadlift Posterior 0.10 ± 0.07 0.98 0.75 Anterior 0.05 ± 0.07 0.93 -0.065 Table 2 Average maximum compressive and shear forces across participants in the Deadlift and Romanian Deadlift tasks External Load (Kg) Romanian Deadlift Conventional Deadlift compression force (N) shear force (N) Compression force (N) shear force (N) 15 4246 ± 361 320.6 ± 63 4974 ± 823 291 ± 49 45 6328 ± 502 607 ± 21 6184 ± 674 641 ± 32 75 9105 ± 362 914 ± 21 9843 ± 313 1002 ± 100 105 12607 ± 156 1241 ± 45 12445 ± 1043 1218 ± 107 Discussion This study evaluated the validity of the Enhanced Fully Articulated Thoracolumbar Spine (EFATLS) model in simulating submaximal heavy lifting (SHL) activities. While research on spinal biomechanics under heavy loads remains limited—especially in the context of sports heavy lifting is common in various athletic and occupational settings. As such, predictive tools for assessing spinal load patterns are critical. However, the majority of musculoskeletal (MSK) model validations have focused on light manual load handling (MLH) tasks, leaving a gap in understanding spinal mechanics under higher loads. In this study, the EFATLS model predictions were validated against experimental electromyography (EMG) data using indirect statistical methods. The low root mean square error (RMSE) observed suggests high prediction accuracy, while the maximum absolute normalized cross-correlation (MANCC) indicates strong temporal similarity between model predictions and experimental data. However, Pearson correlation coefficients for anterior muscles were somewhat inconsistent. Notably, a low RMSE alongside a low correlation typically implies small absolute errors but a limited ability to capture the data's variations or primary patterns. When compared with previous studies, this research showed similar trends in spinal loading. For instance, (Cholewicki et al., 1991 ) reported maximum compression forces of 11 kN and 15.5 kN at the L4-L5 segment under 260 kg loads in 80 kg and 88 kg males, respectively. Another study (Ramirez et al., 2023 ) estimated compressive forces of 18 kN at L5-S1 under a 68 kg load using a finite element model. In the current study, peak compressive forces during deadlift (DL) and Romanian deadlift (RDL) tasks with a 105 kg load were 12.4 kN and 12.6 kN, respectively, while forces under a 15 kg load were 4.9 kN and 4.2 kN. These results align with earlier biomechanical findings (Beaucage-Gauvreau et al., 2019 ), validating the EFATLS model's reliability. Unlike prior studies focusing on stoop or squat lifting techniques, this research specifically examined DL and RDL tasks, which are widely used in weightlifting to handle higher external loads. The participant cohort comprised young, active individuals, differing significantly from sedentary populations often studied in spinal biomechanics research. The small sample size, a common limitation in similar investigations (Akhavanfar et al., 2023 ; Alemi et al., 2023 ; Beaucage-Gauvreau et al., 2019 ), may constrain the generalizability of findings. Additionally, the assumption of constant lumbar lordosis during tasks may neglect the influence of pelvic-lumbar rhythm on spinal mechanics. This study underscores the practical applicability of the EFATLS model in SHL contexts, making it a valuable tool in both occupational and sports settings. Its insights into musculoskeletal complexities can significantly advance sports biomechanics and health sciences. Declarations Institutional Review Board Statement : The project was approved by Kharazmi University's Ethics Committee for research involving human subjects (Approval Code: [IR.KHU.REC.1403152]). Informed Consent Statement Each participant voluntarily provided written informed consent before participating. Conflicts of Interest: The authors declare no conflict of interest. Author Contribution A.S.G. and R.M. conceived and designed the study, performed the experiments, analyzed the data, and wrote the manuscript. All authors reviewed and approved the final manuscript. Acknowledgement The authors sincerely thank Mr. Iman Khorasani and Mr. Amirali Zareh for their valuable collaboration as assistants in the sampling process. Their support is greatly appreciated. References Akhavanfar M, Mir-Orefice A, Uchida TK, Graham RB (2023) An Enhanced Spine Model Validated for Simulating Dynamic Lifting Tasks in OpenSim. Ann Biomed Eng 1–11. https://doi.org/10.1007/S10439-023-03368-X/METRICS Alemi MM, Banks JJ, Lynch AC, Allaire BT, Bouxsein ML, Anderson DE (2023) EMG Validation of a Subject-Specific Thoracolumbar Spine Musculoskeletal Model During Dynamic Activities in Older Adults. Ann Biomed Eng 51(10):2313–2322. https://doi.org/10.1007/S10439-023-03273-3/METRICS Anderson DE, D’Agostino JM, Bruno AG, Manoharan RK, Bouxsein ML (2012) Regressions for estimating muscle parameters in the thoracic and lumbar trunk for use in musculoskeletal modeling. J Biomech 45(1):66–75. https://doi.org/10.1016/J.JBIOMECH.2011.10.004 Arjmand N, Gagnon D, Plamondon A, Shirazi-Adl A, Larivière C (2009) Comparison of trunk muscle forces and spinal loads estimated by two biomechanical models. Clin Biomech Elsevier Ltd. https://doi.org/10.1016/j.clinbiomech.2009.05.008 Balagué F, Mannion AF, Pellisé F, Cedraschi C (2012) Non-specific low back pain. In The Lancet (Vol. 379, Issue 9814, pp. 482–491). Lancet. https://doi.org/10.1016/S0140-6736(11)60610-7 Beaucage-Gauvreau E, Robertson WSP, Brandon SCE, Fraser R, Freeman BJC, Graham RB, Thewlis D, Jones CF (2019) Validation of an OpenSim full-body model with detailed lumbar spine for estimating lower lumbar spine loads during symmetric and asymmetric lifting tasks. Comput Methods Biomech BioMed Eng 22(5):451–464. https://doi.org/10.1080/10255842.2018.1564819 Bruno AG, Bouxsein ML, Anderson DE (2015) Development and validation of a musculoskeletal model of the fully articulated thoracolumbar spine and rib cage. J Biomech Eng 137(8). https://doi.org/10.1115/1.4030408 Cholewicki J, McGill SM, Norman RW (1991) Lumbar spine loads during the lifting of extremely heavy weights. Med Sci Sports Exerc 23(10):1179–1186. https://doi.org/10.1249/00005768-199110000-00012 Delp SL, Anderson FC, Arnold AS, Loan P, Habib A, John CT, Guendelman E, Thelen DG (2007) OpenSim: Open-source software to create and analyze dynamic simulations of movement. IEEE Trans Biomed Eng 54(11):1940–1950. https://doi.org/10.1109/TBME.2007.901024 Dreischarf M, Shirazi-Adl A, Arjmand N, Rohlmann A, Schmidt H (2016) Estimation of loads on human lumbar spine: A review of in vivo and computational model studies. J Biomech 49(6):833–845. https://doi.org/10.1016/j.jbiomech.2015.12.038 Eltoukhy M, Travascio F, Asfour S, Elmasry S, Heredia-Vargas H, Signorile J (2015) Examination of a lumbar spine biomechanical model for assessing axial compression, shear, and bending moment using selected Olympic lifts. J Orthop 13(3):210–219. https://doi.org/10.1016/J.JOR.2015.04.002 Erdemir A, McLean S, Herzog W, van den Bogert AJ (2007) Model-based estimation of muscle forces exerted during movements. Clin Biomech Elsevier Ltd 22(2):131–154. https://doi.org/10.1016/J.CLINBIOMECH.2006.09.005 Gabbett HT, Windt J, Gabbett TJ (2016) Cost-benefit analysis underlies training decisions in elite sport. Br J Sports Med 50(21):1291–1292. https://doi.org/10.1136/BJSPORTS-2016-096079 Hicks JL, Uchida TK, Seth A, Rajagopal A, Delp SL (2015) Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement. J Biomech Eng 137(2). https://doi.org/10.1115/1.4029304 Jäger M, Luttmann A (1989) Biomechanical analysis and assessment of lumbar stress during load lifting using a dynamic 19-segment human model. Ergonomics 32(1):93–112. https://doi.org/10.1080/00140138908966070 Katz JN (2006) Lumbar disc disorders and low-back pain: socioeconomic factors and consequences. The Journal of Bone and Joint Surgery. American Volume , 88 Suppl 2 (SUPPL. 2), 21–24. https://doi.org/10.2106/JBJS.E.01273 Medicine AC of S., Whaley MH, Brubaker PH, Otto RM, Armstrong LE (2006) ACSM’s Guidelines for Exercise Testing and Prescription . 366. https://books.google.com/books/about/ACSM_s_Guidelines_for_Exercise_Testing_a.html?id=n2OiofUcHxIC Ramirez V, Ghezelbash F, Shirazi-Adl A, Bazrgari B (2023) Trunk muscle forces and spinal loads during heavy deadlift: Effects of personalization, muscle wrapping, muscle lever arm, and lumbopelvic rhythm. Int J Numer Methods Biomed Eng 39(4). https://doi.org/10.1002/CNM.3680 Ramirez VJ, Bazrgari B, Gao F, Samaan M (2022) Low Back Biomechanics during Repetitive Deadlifts: A Narrative Review. IISE Trans Occup Ergon Hum Factors 10(1):34–46. https://doi.org/10.1080/24725838.2021.2015642 Rohlmann A, Gabel U, Graichen F, Bender A, Bergmann G (2007) An instrumented implant for vertebral body replacement that measures loads in the anterior spinal column. Med Eng Phys 29(5):580–585. https://doi.org/10.1016/J.MEDENGPHY.2006.06.012 Ross R, Han J, Slover J (2023) Chronic Lower Back Pain in Weight Lifters: Epidemiology, Evaluation, and Management. JBJS Reviews 11(6). https://doi.org/10.2106/JBJS.RVW.22.00228 Swinton PA, Stewart A, Agouris I, Keogh JWL, Lloyd R (2011) A biomechanical analysis of straight and hexagonal barbell deadlifts using submaximal loads. J Strength Conditioning Res 25(7):2000–2009. https://doi.org/10.1519/JSC.0B013E3181E73F87 Tankisi H, Burke D, Cui L, de Carvalho M, Kuwabara S, Nandedkar SD, Rutkove S, Stålberg E, van Putten MJAM, Fuglsang-Frederiksen A (2020) Standards of instrumentation of EMG. Clin Neurophysiol 131(1):243–258. https://doi.org/10.1016/J.CLINPH.2019.07.025 Thelen DG (2003) Adjustment of muscle mechanics model parameters to simulate dynamic contractions in older adults. J Biomech Eng 125(1):70–77. https://doi.org/10.1115/1.1531112 Vera-Garcia FJ, Moreside JM, McGill SM (2010) MVC techniques to normalize trunk muscle EMG in healthy women. J Electromyogr Kinesiology: Official J Int Soc Electrophysiological Kinesiol 20(1):10–16. https://doi.org/10.1016/J.JELEKIN.2009.03.010 Waters TR, Putz-Anderson V, Garg A, Fine LJ (1993) Revised NIOSH equation for the design and evaluation of manual lifting tasks. Ergonomics 36(7):749–776. https://doi.org/10.1080/00140139308967940 Wilke HJ, Neef P, Caimi M, Hoogland T, Claes LE (1999) New in vivo measurements of pressures in the intervertebral disc in daily life. Spine 24(8):755–762. https://doi.org/10.1097/00007632-199904150-00005 Winter DA (2009) Biomechanics and Motor Control of Human Movement: Fourth Edition. In Biomechanics and Motor Control of Human Movement: Fourth Edition . https://doi.org/10.1002/9780470549148 Zajac FE (1989) Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit Rev Biomed Eng 17(4):359–411. https://europepmc.org/article/MED/2676342 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-8063259","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":542736489,"identity":"3b6cf9a8-5c2b-4e3f-a585-788a5cc48a20","order_by":0,"name":"Amir Sadeghi Golafzani","email":"data:image/png;base64,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","orcid":"","institution":"Kharazmi University","correspondingAuthor":true,"prefix":"","firstName":"Amir","middleName":"Sadeghi","lastName":"Golafzani","suffix":""},{"id":542736490,"identity":"dbc2e243-eb0d-48ba-8443-7cfa979fb0aa","order_by":1,"name":"Raghad Mimar","email":"","orcid":"","institution":"Kharazmi University","correspondingAuthor":false,"prefix":"","firstName":"Raghad","middleName":"","lastName":"Mimar","suffix":""}],"badges":[],"createdAt":"2025-11-08 10:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8063259/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8063259/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96202879,"identity":"4057cdd5-11f9-47f6-ad51-4e6ce5b6c8c2","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":646595,"visible":true,"origin":"","legend":"","description":"","filename":"GolafzaniMimarmanuscript.doc.docx","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/3dbb0c941401d8a612de4617.docx"},{"id":96202873,"identity":"55197969-0ef1-464e-9c01-af6333a227d1","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4002,"visible":true,"origin":"","legend":"","description":"","filename":"1ed98fc38f1d43c5b9aaaa569dd70a44.json","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/1160d912f4c2b2a68292b010.json"},{"id":96202877,"identity":"dc5011e5-8d20-49f9-b9ac-d02a0452ee88","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":73270,"visible":true,"origin":"","legend":"","description":"","filename":"1ed98fc38f1d43c5b9aaaa569dd70a441enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/86c82cb2d17884cea99d8d8d.xml"},{"id":96252178,"identity":"714a7938-bd8c-4337-b94b-d098317d27ce","added_by":"auto","created_at":"2025-11-19 07:40:36","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":49266,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/5920bd5ffe3e4488d841a2bd.png"},{"id":96202878,"identity":"1a057de6-c0ad-4a08-b583-769d042f76ac","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":41421,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/261b72021f7b0bb2fe59a8a4.png"},{"id":96202881,"identity":"cbef6f1e-c0be-430d-bd50-4f9fae7d668f","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":54932,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/6b7e12f426b50cab533fc06c.png"},{"id":96202883,"identity":"ec3014ef-996f-4344-a89c-f7744c3e5dee","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":72716,"visible":true,"origin":"","legend":"","description":"","filename":"1ed98fc38f1d43c5b9aaaa569dd70a441structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/c0466405608eb88609164225.xml"},{"id":96202882,"identity":"e4dd76ce-0b92-482c-9a6e-052a9eac3a4b","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78382,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/0920577361c2f13b4cca1b85.html"},{"id":96202874,"identity":"b04fa000-b5c3-45e6-829e-670ec57463cb","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":164115,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplot of RMSE comparing model-predicted muscle activity and EMG during DL and RDL. Lower RMSE represents higher prediction accuracy. RLG/LLG: right/left longissimus, RIL/LIL: right/left iliocostalis, RMF/LMF: right/left multifidus, LRAB/RRAB: left t/right rectus abdominis, LEO/REO: left/right external oblique, LIO/RIO: left/right internal oblique, DL15/45/75/105: DL with 15kg/45kg/75kg/105kg. RDL15/45/75/105: RDL with 15kg/45kg/75kg/105kg.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/6fbded9b479ff3a592f23e63.jpeg"},{"id":96250498,"identity":"4f5c4261-9595-4f96-9de5-3679de7621a4","added_by":"auto","created_at":"2025-11-19 07:38:27","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":109758,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of median values for MANCC between model-predicted muscle activity and EMG during DL and RDL. RLG/LLG: right/left longissimus erector spinae, RIL/LIL: right/left iliocostalis er erector spinae, RMF/LMF: right/left multifidus spinae, LRAB/RRAB: left/right rectus abdominis, LEO/REO: left/right external oblique, LIO/RIO: left/right internal oblique, DL15/45/75/105: DL with 15kg/45kg/75kg/105kg. RDL15/45/75/105: RDL with 15kg/45kg/75kg/105kg.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/b5e0b5553e06c78f11daf9c7.jpeg"},{"id":96202875,"identity":"bdfe4562-89bd-49c8-bd78-b8e3c203fdfb","added_by":"auto","created_at":"2025-11-18 16:47:00","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":108802,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of Pearson correlation between model-predicted muscle activity and EMG during DL and RDL. p-values for all correlations are below the computational threshold (p\u0026lt;0.0001), indicating strong statistical significance. RLG/LLG: right/left longissimus erector spinae, RIL/LIL: right/left iliocostalis erector spinae, RMF/LMF: right/left multifidus spinae, LRAB/RRAB: left/right rectus abdominis, LEO/REO: left/right external oblique, LIO/RIO: left/right internal oblique, DL15/45/75/105: Romanian deadlift 15kg/45kg/75kg/105kg\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/eaa951eb4419eb22b78b5855.jpeg"},{"id":96605353,"identity":"ea3b2d56-b7b9-4360-873d-3cbb6a1696fa","added_by":"auto","created_at":"2025-11-24 09:22:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":821676,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8063259/v1/b47bc9ee-8799-48b0-8a97-374a728b067d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Validation of a Spine Musculoskeletal Model During Submaximal Heavy Lifting in OpenSim","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLow Back Pain (LBP) is a global health challenge with significant clinical and economic implications (Balagu\u0026eacute; et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In the U.S., annual costs associated with LBP are estimated at \u003cspan\u003e$\u003c/span\u003e100\u0026ndash;200\u0026nbsp;billion, comparable to the economic impact of Hurricane Katrina (Katz, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWeightlifters frequently experience back pain, often attributed to squat and deadlift techniques(Ross et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Conventional Deadlift (DL), Romanian Deadlift (RDL), and squat techniques are foundational in athletic training programs. Hence, lumbar-straining postures are common in sports, and manual load handling (MLH) guidelines are impractical (Waters et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1993\u003c/span\u003e).Understanding spinal loads is critical for optimizing lifting techniques (J\u0026auml;ger and Luttmann, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), assessing injury risks (Ramirez et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and evaluating the cost-benefit of athlete preparation and physical activities(Gabbett et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Direct measurements of spinal loads using invasive methods, such as intradiscal pressure (Wilke et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) and implanted strain gauges (Rohlmann et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), face limitations, underscoring the need for non-invasive musculoskeletal (MSK) modeling techniques(Dreischarf et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Despite computational advancements, research on near-maximal external loads remains limited, raising concerns about estimation accuracy (Ramirez et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMSK modeling requires detailed muscle property data, yet athlete-specific data and imaging evaluations are scarce(Anderson et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMany studies omit muscle activity (Eltoukhy et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Swinton et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), simplify muscle representations (Cholewicki et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), or rely on kinematics-driven methods (Ramirez et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Fully dynamic multibody approaches remain underexplored.\u003c/p\u003e\u003cp\u003eOpenSim, an open-source MSK modeling tool, has become integral in the past two decades (Delp et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). It supports inverse dynamics analysis (Winter, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), muscle force estimation based on muscle properties )Thelen, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Zajac, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1989\u003c/span\u003e(, and dynamic equilibrium optimization (Erdemir et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Full-body spine models for lifting tasks have been validated in recent years (Beaucage-Gauvreau et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bruno et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) Model accuracy depends on measurement limitations and task-specific validation (Hicks et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eValidation approaches for spinal models include comparing measured in vivo loads with model predictions(Akhavanfar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Bruno et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and comparing recorded surface activity (Alemi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The Fully Articulated Thoracolumbar Spine Model has been tested under static lifting conditions(Bruno et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and dynamic daily activities (Alemi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), This model was enhanced in kinematics and kinetics and validated using a novel method that correlates time-series data from implanted sensors with estimated forces(Akhavanfar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). but validation for Submaximal Heavy Lifting (SHL) tasks is lacking.\u003c/p\u003e\u003cp\u003eThis study validates the Enhanced Fully Articulated Thoracolumbar Spine Model (EFALTS) for DL and RDL tasks under SHL conditions in young, active men.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eData collection\u003c/p\u003e\u003cp\u003eSixteen young men (age: 26 ± 3 years; weight: 82.5 ± 2.75 kg; height: 187 ± 5 cm) experienced in DL and RDL tasks participated.\u003c/p\u003e\u003cp\u003ePhysical readiness was confirmed via an ACSM questionnaire(Medicine et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Participants with no vertebral surgery, fractures, or LBP in the past year were included. Radiographic imaging confirmed normal spinal anatomy and measured lumbar lordosis angles. DL and RDL movements were performed with minimal clothing and a standard 15 kg barbell. Rest periods of at least 5 minutes ensured recovery between trials. The task cycle involved lifting the barbell from a squat to standing and returning. Loads of 15 kg, 45 kg, 75 kg, and 105 kg (\u0026lt; 85% 1RM) were used.\u003c/p\u003e\u003cp\u003eKinematic and kinetic data were captured using eight motion capture cameras (MXF-20, Vicon), two force plates (BP400600, AMTI), and a wireless EMG system (Myon AG). Reflective markers were placed on body segments )Beaucage-Gauvreau et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e(. EMG signals and force plate data were sampled at 1000 Hz; kinematic data were sampled at 100 Hz. Bilateral EMG sensors were placed on six muscles: longissimus erector spinae, iliocostalis erector spinae, multifidus, external oblique, rectus abdominis, and internal oblique (Arjmand et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Electrodes were applied using SF07 adhesive following skin preparation(Tankisi et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). EMG data were normalized using maximal voluntary isometric contraction (MVC) tests for flexors and extensors(Vera-Garcia et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eData processing\u003c/p\u003e\u003cp\u003eSignals were filtered using a Butterworth band-pass filter (20–450 Hz, 6th order) to remove noise and minimize skin artifacts. No significant power line or ECG interference was detected; therefore, no additional filtering was applied. Signals were full-wave rectified, low-pass filtered at 3 Hz (6th order) to obtain the linear envelope, and normalized to MVC values.\u003c/p\u003e\u003cp\u003eInverse dynamics and static optimization were performed in OpenSim 4.3 using the EFALTS model. Models were scaled based on anatomical markers. The mass load is added to each arm as half of the external load. (Akhavanfar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Muscle maximum stress was adjusted to 1.4 MPa for young individuals (Beaucage-Gauvreau et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Spinal curvature was defined using radiographic data in the sagittal plane. We assumed participants would maintain the same spinal arc observed in the standing position during the DL and RDL movements. Muscle activity predictions minimized cubic muscle activity sums while accounting for force-length-velocity relationships. The average fascicle activity was used to represent muscle activity. Muscle activity estimates were unfiltered to match the model’s resolution.\u003c/p\u003e\u003cp\u003eStatistical\u003c/p\u003e\u003cp\u003eStatistical Analysis Predicted muscle activities were compared with experimental EMG data using four metrics: Pearson Correlation Coefficient, Root Mean Square Error (RMSE), Maximum Absolute Normalized Cross-Correlation (MANCC), and Fisher’s Z Transformation. Statistical analyses were conducted in MATLAB R2023b.\u003c/p\u003e"},{"header":"Result","content":"\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows RMSE values, averaging 0.076 for DL and 0.074 for RDL, indicating high model accuracy (~ 10% error). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents MANCC heatmaps, showing strong temporal similarity (values \u0026gt; 0.9) and moderate similarity (0.7–0.9). Posterior muscles exhibited higher similarity than anterior muscles. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates Pearson correlation heatmaps, with moderate correlations (0.7–0.9) for posterior muscles. RDL at 105 kg showed values \u0026lt; 0.7. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes prediction errors, temporal similarity, and correlation differences. Fisher’s Z-transformation averaged correlations. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the peak forces exerted on the lumbosacral joint during DL and RDL across various load conditions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"±\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMean MANCC and Pearson Correlation (adjusted using Fisher's Z) alongside the mean and standard deviation of RMSE\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTask\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMuscle Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRMSE\u003c/p\u003e\u003cp\u003e(MEAN ± SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMANCC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePearson Correlation (r)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eConventional\u003c/p\u003e\u003cp\u003eDeadlift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePosterior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\u003cp\u003e0.11 ± 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnterior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\u003cp\u003e0.05 ± 0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRomanian Deadlift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePosterior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\u003cp\u003e0.10 ± 0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnterior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\u003cp\u003e0.05 ± 0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.065\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAverage maximum compressive and shear forces across participants in the Deadlift and Romanian Deadlift tasks\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eExternal Load (Kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eRomanian Deadlift\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eConventional Deadlift\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecompression force (N)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eshear force (N)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCompression force (N)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eshear force (N)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4246 ± 361\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e320.6 ± 63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e4974 ± 823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e291 ± 49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6328 ± 502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e607 ± 21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6184 ± 674\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e641 ± 32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9105 ± 362\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e914 ± 21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e9843 ± 313\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1002 ± 100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12607 ± 156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1241 ± 45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e12445 ± 1043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1218 ± 107\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated the validity of the Enhanced Fully Articulated Thoracolumbar Spine (EFATLS) model in simulating submaximal heavy lifting (SHL) activities. While research on spinal biomechanics under heavy loads remains limited\u0026mdash;especially in the context of sports heavy lifting is common in various athletic and occupational settings. As such, predictive tools for assessing spinal load patterns are critical. However, the majority of musculoskeletal (MSK) model validations have focused on light manual load handling (MLH) tasks, leaving a gap in understanding spinal mechanics under higher loads.\u003c/p\u003e\u003cp\u003eIn this study, the EFATLS model predictions were validated against experimental electromyography (EMG) data using indirect statistical methods. The low root mean square error (RMSE) observed suggests high prediction accuracy, while the maximum absolute normalized cross-correlation (MANCC) indicates strong temporal similarity between model predictions and experimental data. However, Pearson correlation coefficients for anterior muscles were somewhat inconsistent. Notably, a low RMSE alongside a low correlation typically implies small absolute errors but a limited ability to capture the data's variations or primary patterns.\u003c/p\u003e\u003cp\u003eWhen compared with previous studies, this research showed similar trends in spinal loading. For instance, (Cholewicki et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) reported maximum compression forces of 11 kN and 15.5 kN at the L4-L5 segment under 260 kg loads in 80 kg and 88 kg males, respectively. Another study (Ramirez et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) estimated compressive forces of 18 kN at L5-S1 under a 68 kg load using a finite element model. In the current study, peak compressive forces during deadlift (DL) and Romanian deadlift (RDL) tasks with a 105 kg load were 12.4 kN and 12.6 kN, respectively, while forces under a 15 kg load were 4.9 kN and 4.2 kN. These results align with earlier biomechanical findings (Beaucage-Gauvreau et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), validating the EFATLS model's reliability.\u003c/p\u003e\u003cp\u003eUnlike prior studies focusing on stoop or squat lifting techniques, this research specifically examined DL and RDL tasks, which are widely used in weightlifting to handle higher external loads. The participant cohort comprised young, active individuals, differing significantly from sedentary populations often studied in spinal biomechanics research.\u003c/p\u003e\u003cp\u003eThe small sample size, a common limitation in similar investigations (Akhavanfar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Alemi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Beaucage-Gauvreau et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), may constrain the generalizability of findings. Additionally, the assumption of constant lumbar lordosis during tasks may neglect the influence of pelvic-lumbar rhythm on spinal mechanics.\u003c/p\u003e\u003cp\u003eThis study underscores the practical applicability of the EFATLS model in SHL contexts, making it a valuable tool in both occupational and sports settings. Its insights into musculoskeletal complexities can significantly advance sports biomechanics and health sciences.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cb\u003eInstitutional Review Board Statement\u003c/b\u003e: The project was approved by Kharazmi University's Ethics Committee for research involving human subjects (Approval Code: [IR.KHU.REC.1403152]).\u003c/p\u003e\u003ch2\u003eInformed Consent Statement\u003c/h2\u003e\u003cp\u003e\u003cb\u003e\u003c/b\u003eEach participant voluntarily provided written informed consent before participating.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.S.G. and R.M. conceived and designed the study, performed the experiments, analyzed the data, and wrote the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors sincerely thank Mr. Iman Khorasani and Mr. Amirali Zareh for their valuable collaboration as assistants in the sampling process. Their support is greatly appreciated.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkhavanfar M, Mir-Orefice A, Uchida TK, Graham RB (2023) An Enhanced Spine Model Validated for Simulating Dynamic Lifting Tasks in OpenSim. Ann Biomed Eng 1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S10439-023-03368-X/METRICS\u003c/span\u003e\u003cspan address=\"10.1007/S10439-023-03368-X/METRICS\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlemi MM, Banks JJ, Lynch AC, Allaire BT, Bouxsein ML, Anderson DE (2023) EMG Validation of a Subject-Specific Thoracolumbar Spine Musculoskeletal Model During Dynamic Activities in Older Adults. Ann Biomed Eng 51(10):2313\u0026ndash;2322. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/S10439-023-03273-3/METRICS\u003c/span\u003e\u003cspan address=\"10.1007/S10439-023-03273-3/METRICS\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnderson DE, D\u0026rsquo;Agostino JM, Bruno AG, Manoharan RK, Bouxsein ML (2012) Regressions for estimating muscle parameters in the thoracic and lumbar trunk for use in musculoskeletal modeling. J Biomech 45(1):66\u0026ndash;75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.JBIOMECH.2011.10.004\u003c/span\u003e\u003cspan address=\"10.1016/J.JBIOMECH.2011.10.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArjmand N, Gagnon D, Plamondon A, Shirazi-Adl A, Larivi\u0026egrave;re C (2009) Comparison of trunk muscle forces and spinal loads estimated by two biomechanical models. Clin Biomech Elsevier Ltd. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.clinbiomech.2009.05.008\u003c/span\u003e\u003cspan address=\"10.1016/j.clinbiomech.2009.05.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBalagu\u0026eacute; F, Mannion AF, Pellis\u0026eacute; F, Cedraschi C (2012) Non-specific low back pain. In \u003cem\u003eThe Lancet\u003c/em\u003e (Vol. 379, Issue 9814, pp. 482\u0026ndash;491). Lancet. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(11)60610-7\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(11)60610-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeaucage-Gauvreau E, Robertson WSP, Brandon SCE, Fraser R, Freeman BJC, Graham RB, Thewlis D, Jones CF (2019) Validation of an OpenSim full-body model with detailed lumbar spine for estimating lower lumbar spine loads during symmetric and asymmetric lifting tasks. Comput Methods Biomech BioMed Eng 22(5):451\u0026ndash;464. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10255842.2018.1564819\u003c/span\u003e\u003cspan address=\"10.1080/10255842.2018.1564819\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBruno AG, Bouxsein ML, Anderson DE (2015) Development and validation of a musculoskeletal model of the fully articulated thoracolumbar spine and rib cage. J Biomech Eng 137(8). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1115/1.4030408\u003c/span\u003e\u003cspan address=\"10.1115/1.4030408\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCholewicki J, McGill SM, Norman RW (1991) Lumbar spine loads during the lifting of extremely heavy weights. Med Sci Sports Exerc 23(10):1179\u0026ndash;1186. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1249/00005768-199110000-00012\u003c/span\u003e\u003cspan address=\"10.1249/00005768-199110000-00012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDelp SL, Anderson FC, Arnold AS, Loan P, Habib A, John CT, Guendelman E, Thelen DG (2007) OpenSim: Open-source software to create and analyze dynamic simulations of movement. IEEE Trans Biomed Eng 54(11):1940\u0026ndash;1950. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1109/TBME.2007.901024\u003c/span\u003e\u003cspan address=\"10.1109/TBME.2007.901024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDreischarf M, Shirazi-Adl A, Arjmand N, Rohlmann A, Schmidt H (2016) Estimation of loads on human lumbar spine: A review of in vivo and computational model studies. J Biomech 49(6):833\u0026ndash;845. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jbiomech.2015.12.038\u003c/span\u003e\u003cspan address=\"10.1016/j.jbiomech.2015.12.038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEltoukhy M, Travascio F, Asfour S, Elmasry S, Heredia-Vargas H, Signorile J (2015) Examination of a lumbar spine biomechanical model for assessing axial compression, shear, and bending moment using selected Olympic lifts. J Orthop 13(3):210\u0026ndash;219. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.JOR.2015.04.002\u003c/span\u003e\u003cspan address=\"10.1016/J.JOR.2015.04.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eErdemir A, McLean S, Herzog W, van den Bogert AJ (2007) Model-based estimation of muscle forces exerted during movements. Clin Biomech Elsevier Ltd 22(2):131\u0026ndash;154. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.CLINBIOMECH.2006.09.005\u003c/span\u003e\u003cspan address=\"10.1016/J.CLINBIOMECH.2006.09.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGabbett HT, Windt J, Gabbett TJ (2016) Cost-benefit analysis underlies training decisions in elite sport. Br J Sports Med 50(21):1291\u0026ndash;1292. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/BJSPORTS-2016-096079\u003c/span\u003e\u003cspan address=\"10.1136/BJSPORTS-2016-096079\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHicks JL, Uchida TK, Seth A, Rajagopal A, Delp SL (2015) Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement. J Biomech Eng 137(2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1115/1.4029304\u003c/span\u003e\u003cspan address=\"10.1115/1.4029304\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJ\u0026auml;ger M, Luttmann A (1989) Biomechanical analysis and assessment of lumbar stress during load lifting using a dynamic 19-segment human model. Ergonomics 32(1):93\u0026ndash;112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00140138908966070\u003c/span\u003e\u003cspan address=\"10.1080/00140138908966070\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKatz JN (2006) Lumbar disc disorders and low-back pain: socioeconomic factors and consequences. \u003cem\u003eThe Journal of Bone and Joint Surgery. American Volume\u003c/em\u003e, \u003cem\u003e88 Suppl 2\u003c/em\u003e(SUPPL. 2), 21\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2106/JBJS.E.01273\u003c/span\u003e\u003cspan address=\"10.2106/JBJS.E.01273\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMedicine AC of S., Whaley MH, Brubaker PH, Otto RM, Armstrong LE (2006) \u003cem\u003eACSM\u0026rsquo;s Guidelines for Exercise Testing and Prescription\u003c/em\u003e. 366. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://books.google.com/books/about/ACSM_s_Guidelines_for_Exercise_Testing_a.html?id=n2OiofUcHxIC\u003c/span\u003e\u003cspan address=\"https://books.google.com/books/about/ACSM_s_Guidelines_for_Exercise_Testing_a.html?id=n2OiofUcHxIC\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRamirez V, Ghezelbash F, Shirazi-Adl A, Bazrgari B (2023) Trunk muscle forces and spinal loads during heavy deadlift: Effects of personalization, muscle wrapping, muscle lever arm, and lumbopelvic rhythm. Int J Numer Methods Biomed Eng 39(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/CNM.3680\u003c/span\u003e\u003cspan address=\"10.1002/CNM.3680\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRamirez VJ, Bazrgari B, Gao F, Samaan M (2022) Low Back Biomechanics during Repetitive Deadlifts: A Narrative Review. IISE Trans Occup Ergon Hum Factors 10(1):34\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/24725838.2021.2015642\u003c/span\u003e\u003cspan address=\"10.1080/24725838.2021.2015642\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRohlmann A, Gabel U, Graichen F, Bender A, Bergmann G (2007) An instrumented implant for vertebral body replacement that measures loads in the anterior spinal column. Med Eng Phys 29(5):580\u0026ndash;585. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.MEDENGPHY.2006.06.012\u003c/span\u003e\u003cspan address=\"10.1016/J.MEDENGPHY.2006.06.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoss R, Han J, Slover J (2023) Chronic Lower Back Pain in Weight Lifters: Epidemiology, Evaluation, and Management. JBJS Reviews 11(6). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2106/JBJS.RVW.22.00228\u003c/span\u003e\u003cspan address=\"10.2106/JBJS.RVW.22.00228\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSwinton PA, Stewart A, Agouris I, Keogh JWL, Lloyd R (2011) A biomechanical analysis of straight and hexagonal barbell deadlifts using submaximal loads. J Strength Conditioning Res 25(7):2000\u0026ndash;2009. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1519/JSC.0B013E3181E73F87\u003c/span\u003e\u003cspan address=\"10.1519/JSC.0B013E3181E73F87\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTankisi H, Burke D, Cui L, de Carvalho M, Kuwabara S, Nandedkar SD, Rutkove S, St\u0026aring;lberg E, van Putten MJAM, Fuglsang-Frederiksen A (2020) Standards of instrumentation of EMG. Clin Neurophysiol 131(1):243\u0026ndash;258. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.CLINPH.2019.07.025\u003c/span\u003e\u003cspan address=\"10.1016/J.CLINPH.2019.07.025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThelen DG (2003) Adjustment of muscle mechanics model parameters to simulate dynamic contractions in older adults. J Biomech Eng 125(1):70\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1115/1.1531112\u003c/span\u003e\u003cspan address=\"10.1115/1.1531112\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVera-Garcia FJ, Moreside JM, McGill SM (2010) MVC techniques to normalize trunk muscle EMG in healthy women. J Electromyogr Kinesiology: Official J Int Soc Electrophysiological Kinesiol 20(1):10\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.JELEKIN.2009.03.010\u003c/span\u003e\u003cspan address=\"10.1016/J.JELEKIN.2009.03.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWaters TR, Putz-Anderson V, Garg A, Fine LJ (1993) Revised NIOSH equation for the design and evaluation of manual lifting tasks. Ergonomics 36(7):749\u0026ndash;776. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00140139308967940\u003c/span\u003e\u003cspan address=\"10.1080/00140139308967940\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilke HJ, Neef P, Caimi M, Hoogland T, Claes LE (1999) New in vivo measurements of pressures in the intervertebral disc in daily life. Spine 24(8):755\u0026ndash;762. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/00007632-199904150-00005\u003c/span\u003e\u003cspan address=\"10.1097/00007632-199904150-00005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWinter DA (2009) Biomechanics and Motor Control of Human Movement: Fourth Edition. In \u003cem\u003eBiomechanics and Motor Control of Human Movement: Fourth Edition\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/9780470549148\u003c/span\u003e\u003cspan address=\"10.1002/9780470549148\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZajac FE (1989) Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit Rev Biomed Eng 17(4):359\u0026ndash;411. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://europepmc.org/article/MED/2676342\u003c/span\u003e\u003cspan address=\"https://europepmc.org/article/MED/2676342\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Spine, OpenSim, Lifting, Validation, Musculoskeletal Modeling","lastPublishedDoi":"10.21203/rs.3.rs-8063259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8063259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLow back pain is a significant health issue with substantial societal costs. Manual handling guidelines often prove impractical in certain occupations. Musculoskeletal modeling plays a crucial role in assessing injury risks, but gaps remain in understanding spinal injuries and muscle activity under heavy loads. OpenSim software has advanced from spine-specific to full-body models, with recent enhancements to the fully articulated thoracolumbar spine model validated for small load tasks. This study aims to validate the model for submaximal heavy lifting in athletes.\u003c/p\u003e\u003cp\u003eSixteen young male participants performed Conventional and Romanian Deadlift tasks. Trunk muscle activity was measured experimentally and compared with model predictions using metrics like Root Mean Square Error (RMSE), Maximum Absolute Normalized Cross-Correlation (MANCC), and Pearson Correlation.\u003c/p\u003e\u003cp\u003eThe results demonstrated strong temporal similarity and high prediction accuracy, with a robust linear relationship between experimental and model data. This validates the model for submaximal lifting tasks, providing insights into athletic performance and heavy lifting scenarios.\u003c/p\u003e","manuscriptTitle":"Validation of a Spine Musculoskeletal Model During Submaximal Heavy Lifting in OpenSim","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-18 16:46:55","doi":"10.21203/rs.3.rs-8063259/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":"6c5ad6e6-41b3-48a9-b070-7c1fa8788278","owner":[],"postedDate":"November 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-23T23:38:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-18 16:46:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8063259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8063259","identity":"rs-8063259","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}