{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T19:10:42Z","timestamp":1790968242351,"version":"4.1.0"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T00:00:00Z","timestamp":1755475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioeng. Biotechnol."],"abstract":"\n Introduction<\/jats:title>\n Cross-country sit-skiers are often individuals with spinal cord injuries, cerebral palsy, or lower limb disabilities, relying heavily on upper limb strength to generate propulsion during skiing. However, frequent shoulder joint movements significantly increase the incidence of shoulder joint disorders. Therefore, quantifying muscle forces during movement is crucial for understanding upper limb force generation patterns. Currently, electromyography (EMG)-driven neuromusculoskeletal (NMSK) models are the predominant method for calculating muscle forces and joint moments. However, this approach heavily depends on the quality and quantity of EMG data. Surface electrodes are typically used to collect activity data from superficial muscles, but during dynamic movements, factors such as skin stretching, sweating, or friction may cause electrode detachment or poor contact, leading to EMG signal acquisition failures or data loss. In this study, we propose a synergy-assisted EMG-driven NMSK model to predict the activation patterns of missing muscles for cross-country sit-skiing double poling.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n This method is based on individualized EMG-driven NMSK models constructed for each participant, incorporating data from 10 muscles. By utilizing the activation data of 9 known muscles, the model predicts the activation of one missing muscle through synergy analysis. For synergy method selection, we systematically compared four approaches: Non-negative Matrix Factorization (NMF), Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Factor Analysis (FA).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The results demonstrated NMF\u2019s superior performance at 5 synergies, accurately predicting any missing muscle activation among 10 muscles (\n \n \n \n r<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n = 0.79 \u00b1 0.25 vs. 0.14 \u00b1 0.60-0.45 \u00b1 0.63 for alternatives,\n \n \n \n p<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n &lt; 0.05), with lower errors (RMSE: 0.21 \u00b1 0.11,\n \n \n \n p<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n &lt; 0.05 vs. ICA\/FA,\n \n \n \n p<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n &lt; 0.1 vs. PCA; MAE: 0.17 \u00b1 0.09, all\n \n \n \n p<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n &lt; 0.05).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n This finding validates the effectiveness of the proposed method in predicting upper limb muscle activation during coupled shoulder and elbow joint movements.<\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fbioe.2025.1585127","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T09:14:27Z","timestamp":1755508467000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Assessment of synergy-assisted EMG-driven NMSK model for upper limb muscle activation prediction in cross-country sit-skiing double poling"],"prefix":"10.3389","volume":"13","author":[{"given":"Xue","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongxue","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianzhi","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanxin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenglin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Huo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1055","DOI":"10.1016\/j.jbiomech.2009.12.012","article-title":"Optimality principles for model-based prediction of human gait","volume":"43","author":"Ackermann","year":"2010","journal-title":"J. Biomechanics"},{"key":"B2","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/S0021-9290(00)00155-X","article-title":"Static and dynamic optimization solutions for gait are practically equivalent","volume":"34","author":"Anderson","year":"2001","journal-title":"J. Biomechanics"},{"key":"B3","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1186\/s12984-024-01490-y","article-title":"Comparison of synergy extrapolation and static optimization for estimating multiple unmeasured muscle activations during walking","volume":"21","author":"Ao","year":"2024","journal-title":"J. Neuroengineering Rehabilitation"},{"key":"B4","doi-asserted-by":"publisher","first-page":"588943","DOI":"10.3389\/fncom.2020.588943","article-title":"Evaluation of synergy extrapolation for predicting unmeasured muscle excitations from measured muscle synergies","volume":"14","author":"Ao","year":"2020","journal-title":"Front. Comput. Neurosci."},{"key":"B5","doi-asserted-by":"publisher","first-page":"962959","DOI":"10.3389\/fbioe.2022.962959","article-title":"EMG-driven musculoskeletal model calibration with estimation of unmeasured muscle excitations via synergy extrapolation","volume":"10","author":"Ao","year":"2022","journal-title":"Front. Bioeng. Biotechnol."},{"key":"B6","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1080\/17461391.2021.2014573","article-title":"Muscle coordination during archery shooting: a comparison of archers with different skill levels","volume":"23","author":"Baifa","year":"2021","journal-title":"Eur. J. Sport Sci."},{"key":"B7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jbiomech.2017.08.030","article-title":"The influence of ligament modelling strategies on the predictive capability of finite element models of the human knee joint","volume":"65","author":"Beidokhti","year":"2017","journal-title":"J. Biomechanics"},{"key":"B8","volume-title":"The co-ordination and regulation of movements","author":"Bernshtei\u0306n","year":"1967"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.1115\/1.4038199","article-title":"Can measured synergy excitations accurately construct unmeasured muscle excitations?","volume":"140","author":"Bianco","year":"2018","journal-title":"J. Biomech. Eng."},{"key":"B9","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1126\/science.1857964","article-title":"Computations underlying the execution of movement: a biological perspective","volume":"253","author":"Bizzi","year":"1991","journal-title":"Science"},{"key":"B10","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.brainresrev.2007.08.004","article-title":"Combining modules for movement","volume":"57","author":"Bizzi","year":"2008","journal-title":"Brain Res. Rev."},{"key":"B11","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.1109\/TBME.2018.2872833","article-title":"Sensitivity of shoulder musculoskeletal model predictions to muscle-tendon properties","volume":"66","author":"Blache","year":"2019","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"B12","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1123\/jab.20.4.367","article-title":"Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command","volume":"20","author":"Buchanan","year":"2004","journal-title":"J. Appl. Biomechanics"},{"key":"B13","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1007\/s11517-022-02724-8","article-title":"Bilateral upper extremity trunk model for cross-country sit-skiing double poling propulsion: model development and validation","volume":"61","author":"Chen","year":"2023","journal-title":"Med. & Biol. Eng. & Comput."},{"key":"B14","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.medengphy.2018.04.003","article-title":"Evaluation of matrix factorisation approaches for muscle synergy extraction","volume":"57","author":"Ebied","year":"2018","journal-title":"Med. Eng. & Phys."},{"key":"B15","volume-title":"The international ski competition rules (ICR)[S]","year":"2024"},{"key":"B16","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1097\/JSM.0b013e31824202d3","article-title":"A biomechanical approach to paralympic cross-country sit-ski racing","volume":"22","author":"Gastaldi","year":"2012","journal-title":"Clin. J. Sport Med."},{"key":"B17","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1016\/j.jare.2016.10.003","article-title":"Analysis of the pushing phase in paralympic cross-country sit-skiers - class LW10","volume":"7","author":"Gastaldi","year":"2016","journal-title":"J. Adv. Res."},{"key":"B18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/joa.12903","article-title":"The moment arms of the muscles spanning the glenohumeral joint: a systematic review","volume":"234","author":"Hik","year":"2019","journal-title":"J. Anat."},{"key":"B19","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1142\/s0218957708001973","article-title":"Moment arms of the arm muscles at the glenohumeral joint using the tendon excursion method","volume":"11","author":"Itoi","year":"2008","journal-title":"J. Musculoskelet. Res."},{"key":"B20","doi-asserted-by":"publisher","first-page":"110698","DOI":"10.1016\/j.jbiomech.2021.110698","article-title":"The effectiveness of EMG-driven neuromusculoskeletal model calibration is task dependent","volume":"129","author":"Kian","year":"2021","journal-title":"J. Biomechamics"},{"key":"B21","doi-asserted-by":"publisher","first-page":"104178","DOI":"10.1016\/j.bspc.2022.104178","article-title":"An enhanced EMG-driven musculoskeletal model based on non-negative matrix factorization","volume":"79","author":"Li","year":"2023","journal-title":"Biomed. Signal Process. Control"},{"key":"B22","article-title":"An intelligent training system for simulating cross-country sit-skiing","author":"Liu","year":"2020","journal-title":"China"},{"key":"B23","doi-asserted-by":"publisher","first-page":"6093","DOI":"10.1038\/s41598-022-10103-4","article-title":"Upper limb isokinetic muscle strength predicts the performance in cross-country sit-skiing","volume":"12","author":"Liu","year":"2022","journal-title":"Sci. Rep."},{"key":"B24","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1016\/s0021-9290(03)00010-1","article-title":"An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo","volume":"36","author":"Lloyd","year":"2003","journal-title":"J. Biomechanics"},{"key":"B25","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.compbiomed.2016.01.001","article-title":"A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots","volume":"70","author":"Ma","year":"2016","journal-title":"Comput. Biol. Med."},{"key":"B26","doi-asserted-by":"publisher","first-page":"1197","DOI":"10.1016\/s0021-9290(03)00152-0","article-title":"A one-parameter neural activation to muscle activation model: estimating isometric joint moments from electromyograms","volume":"36","author":"Manal","year":"2003","journal-title":"J. Biomechanics"},{"key":"B27","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1007\/s00421-017-3596-y","article-title":"Sitting position affects performance in cross-country sit-skiing","volume":"117","author":"Ohlsson","year":"2017","journal-title":"Eur. J. Appl. Physiology"},{"key":"B28","doi-asserted-by":"publisher","first-page":"3599","DOI":"10.1038\/s41598-022-07541-5","article-title":"A muscle synergy-based method to estimate muscle activation patterns of children with cerebral palsy using data collected from typically developing children","volume":"12","author":"Rabbi","year":"2022","journal-title":"Sci. Rep."},{"key":"B29","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1007\/s10237-024-01825-7","article-title":"Muscle synergy-informed neuromusculoskeletal modelling to estimate knee contact forces in children with cerebral palsy","volume":"23","author":"Rabbi","year":"2024","journal-title":"Biomechanics Model. Mechanobiol."},{"key":"B30","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.jelekin.2016.11.002","article-title":"Biomechanics of simulated versus natural cross-country sit skiing","volume":"32","author":"Rosso","year":"2017","journal-title":"J. Electromyogr. Kinesiol."},{"key":"B31","doi-asserted-by":"publisher","first-page":"e05377","DOI":"10.1016\/j.heliyon.2020.e05377","article-title":"Lower complexity of motor primitives ensures robust control of high-speed human locomotion","volume":"6","author":"Santuz","year":"2020","journal-title":"Heliyon"},{"key":"B32","doi-asserted-by":"publisher","first-page":"3613","DOI":"10.1016\/j.jbiomech.2014.10.009","article-title":"Hybrid neuromusculoskeletal modeling to best track joint moments using a balance between muscle excitations derived from electromyograms and optimization","volume":"47","author":"Sartori","year":"2014","journal-title":"J. Biomechanics"},{"key":"B33","doi-asserted-by":"publisher","first-page":"105","DOI":"10.3389\/fncom.2013.00105","article-title":"The number and choice of muscles impact the results of muscle synergy analyses","volume":"7","author":"Steele","year":"2013","journal-title":"Front. Comput. Neurosci."},{"key":"B34","doi-asserted-by":"publisher","first-page":"011005","DOI":"10.1115\/1.4063899","article-title":"Upper extremity muscle activation pattern prediction through synergy extrapolation and electromyography-driven modeling","volume":"146","author":"Tahmid","year":"2024","journal-title":"J. Biomechanical Eng."},{"key":"B35","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1115\/1.1531112","article-title":"Adjustment of muscle mechanics model parameters to simulate dynamic contractions in older adults","volume":"125","author":"Thelen","year":"2003","journal-title":"J. Biomechanical Eng."},{"key":"B36","doi-asserted-by":"publisher","first-page":"20893","DOI":"10.1038\/s41598-023-48359-z","article-title":"Effects of poling camber angle on the biomechanics of cross-country sit-skiing","volume":"13","author":"Tian","year":"2023","journal-title":"Sci. Rep."},{"key":"B37","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1186\/s12984-018-0434-3","article-title":"Impact of antagonistic muscle co-contraction on in vivo knee contact forces","volume":"15","author":"Trepczynski","year":"2018","journal-title":"J. NeuroEngineering Rehabilitation"},{"key":"B38","doi-asserted-by":"publisher","first-page":"2199","DOI":"10.1152\/jn.00222.2005","article-title":"Matrix factorization algorithms for the identification of muscle synergies: evaluation on simulated and experimental data sets","volume":"95","author":"Tresch","year":"2006","journal-title":"J. Neurophysiology"},{"key":"B39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/8850785","article-title":"Upper-limb muscle synergy features in human-robot interaction with circle-drawing movements","volume":"2021","author":"Wang","year":"2021","journal-title":"Appl. Bionics Biomechanics"},{"key":"B40","first-page":"359","article-title":"Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control","volume":"17","author":"Zajac","year":"1989","journal-title":"Crit. Rev. Biomed. Eng."},{"key":"B41","doi-asserted-by":"publisher","first-page":"732156","DOI":"10.3389\/fnins.2022.732156","article-title":"Evaluation of methods for the extraction of spatial muscle synergies","volume":"16","author":"Zhao","year":"2022","journal-title":"Front. Neurosci."}],"container-title":["Frontiers in Bioengineering and Biotechnology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fbioe.2025.1585127\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T09:14:28Z","timestamp":1755508468000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fbioe.2025.1585127\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,18]]},"references-count":42,"alternative-id":["10.3389\/fbioe.2025.1585127"],"URL":"https:\/\/doi.org\/10.3389\/fbioe.2025.1585127","relation":{},"ISSN":["2296-4185"],"issn-type":[{"value":"2296-4185","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,18]]},"article-number":"1585127"}}