{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T08:19:19Z","timestamp":1788337159766,"version":"build-2803163510"},"reference-count":40,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61431017"],"award-info":[{"award-number":["61431017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["61431017"],"award-info":[{"award-number":["61431017"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>During self-selected overground walking, we examined participant-level surface electromyography (sEMG) descriptors associated with Gross Motor Function Classification System (GMFCS) levels I\u2013III in 38 ambulatory children with spastic cerebral palsy. Eight-muscle sEMG was summarized using a design-locked pool of 16 peak-normalized envelope and exploratory synergy features. Higher GMFCS level was associated most consistently with longer activation duty cycle, stronger distal and proximal peak-normalized co-activation, and greater inter-muscle spatial entropy. Directions were retained across sensitivity analyses. For secondary within-cohort discrimination, the 16-feature pool yielded a quadratic weighted kappa (QWK) of 0.837\u00b10.046 across 50 repeated participant-level nested cross-validation evaluations. Repeating correlation reduction and four-feature selection inside every outer-training fold yielded QWK 0.849\u00b10.029. Both estimates reuse the 38 children and describe resampling performance, not independent-population generalizability. The core-four specification was post hoc. In an open supplementary workbook containing 195 unique participant IDs, directional concordance was strongest for activation duty cycle and distal co-activation, but direct transfer of the internally fitted 16-feature and core-four models was poor (QWK 0.210 and 0.077). Without healthy controls or measured walking speed and stride length, these cross-sectional results identify descriptors associated with ambulatory GMFCS level, not cerebral-palsy-specific biomarkers or evidence of clinical predictive utility.<\/jats:p>","DOI":"10.3390\/s26175434","type":"journal-article","created":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T16:47:13Z","timestamp":1787849233000},"page":"5434","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Activation Duty Cycle and Regional Muscle Co-Activation Across GMFCS Levels in Ambulatory Children with Spastic Cerebral Palsy: An Exploratory Surface EMG Study"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-6053-0626","authenticated-orcid":false,"given":"Peng","family":"Huang","sequence":"first","affiliation":[{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2014-5747","authenticated-orcid":false,"given":"Zhen","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"validation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7516-8313","authenticated-orcid":false,"given":"Yonggang","family":"Tong","sequence":"additional","affiliation":[{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0615-2569","authenticated-orcid":false,"given":"Yingfei","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"resources","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,27]]},"reference":[{"key":"ref_1","first-page":"8","article-title":"A report: The definition and classification of cerebral palsy April 2006","volume":"109","author":"Rosenbaum","year":"2007","journal-title":"Dev. Med. Child Neurol. Suppl."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Cappellini, G., Sylos-Labini, F., Assenza, C., Libernini, L., Morelli, D., Lacquaniti, F., and Ivanenko, Y. (2020). Clinical relevance of state-of-the-art analysis of surface electromyography in cerebral palsy. Front. Neurol., 11.","DOI":"10.3389\/fneur.2020.583296"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Clewes, K., Hammond, C., Dong, Y., Meyer, M., Lowe, E., and Rose, J. (2024). Neuromuscular impairments of cerebral palsy: Contributions to gait abnormalities and implications for treatment. Front. Hum. Neurosci., 18.","DOI":"10.3389\/fnhum.2024.1445793"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1494","DOI":"10.1111\/dmcn.15346","article-title":"Global prevalence of cerebral palsy: A systematic analysis","volume":"64","author":"McIntyre","year":"2022","journal-title":"Dev. Med. Child Neurol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/j.1469-8749.1997.tb07414.x","article-title":"Development and reliability of a system to classify gross motor function in children with cerebral palsy","volume":"39","author":"Palisano","year":"1997","journal-title":"Dev. Med. Child Neurol."},{"key":"ref_6","unstructured":"Gage, J.R., Schwartz, M.H., Koop, S.E., and Novacheck, T.F. (2009). The Identification and Treatment of Gait Problems in Cerebral Palsy, Mac Keith Press. [2nd ed.]."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.gaitpost.2006.10.015","article-title":"A time\u2013frequency based electromyographic analysis technique for use in cerebral palsy","volume":"26","author":"Lauer","year":"2007","journal-title":"Gait Posture"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1111\/dmcn.14002","article-title":"Lower limb muscle fatigue during walking in children with cerebral palsy","volume":"61","author":"Eken","year":"2019","journal-title":"Dev. Med. Child Neurol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.clinbiomech.2008.07.012","article-title":"Multichannel SEMG in clinical gait analysis: A review and state-of-the-art","volume":"24","author":"Frigo","year":"2009","journal-title":"Clin. Biomech."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"101197","DOI":"10.1016\/j.imu.2023.101197","article-title":"Cerebral palsy classification based on multi-feature analysis using machine learning","volume":"37","author":"AlMasri","year":"2023","journal-title":"Inform. Med. Unlocked"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1109\/TNSRE.2021.3076366","article-title":"Machine-learning-based prediction of gait events from EMG in cerebral palsy children","volume":"29","author":"Morbidoni","year":"2021","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2300845","DOI":"10.1002\/aisy.202300845","article-title":"Wearable sensor-based multi-modal fusion network for automated gait dysfunction assessment in children with cerebral palsy","volume":"6","author":"Tang","year":"2024","journal-title":"Adv. Intell. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1186\/s12938-023-01168-x","article-title":"Interpretable classification for multivariate gait analysis of cerebral palsy","volume":"22","author":"Yoon","year":"2023","journal-title":"Biomed. Eng. Online"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"de Gorostegui, A., Zanin, M., Mart\u00edn-Gonzalo, J.-A., L\u00f3pez-L\u00f3pez, J., G\u00f3mez-Andr\u00e9s, D., Kiernan, D., and Rausell, E. (2025). Entropy, irreversibility, and time-series deep learning of kinematic and kinetic data for gait classification in children with cerebral palsy, idiopathic toe walking, and hereditary spastic paraplegia. Sensors, 25.","DOI":"10.3390\/s25134235"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1016\/j.gaitpost.2018.04.017","article-title":"ESMAC Best Paper 2017: Using machine learning to overcome challenges in GMFCS level assignment","volume":"63","author":"Schwartz","year":"2018","journal-title":"Gait Posture"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"65906","DOI":"10.1109\/ACCESS.2023.3289986","article-title":"Explainable machine learning in human gait analysis: A study on children with cerebral palsy","volume":"11","author":"Slijepcevic","year":"2023","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ahn, Y., Hong, J., Shim, D., Choi, J.-O., and Rha, D.-W. (2023). Comparing the lower-limb muscle activation patterns of simulated walking using an end-effector-type robot with real level and stair walking in children with spastic bilateral cerebral palsy. Sensors, 23.","DOI":"10.3390\/s23146579"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Abdelhady, M., Damiano, D.L., and Bulea, T.C. (2024). Knee angle estimation from surface EMG during walking using attention-based deep recurrent neural networks: Feasibility and initial demonstration in cerebral palsy. Sensors, 24.","DOI":"10.3390\/s24134217"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"106008","DOI":"10.1016\/j.clinbiomech.2023.106008","article-title":"Dynamic electromyography findings of the lower leg muscles during walking in spastic cerebral palsy children with hindfoot valgus","volume":"106","author":"Wang","year":"2023","journal-title":"Clin. Biomech."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Gagnat, Y., Br\u00e6ndvik, S.M., and Roeleveld, K. (2020). Surface electromyography normalization affects the interpretation of muscle activity and coactivation in children with cerebral palsy during walking. Front. Neurol., 11.","DOI":"10.3389\/fneur.2020.00202"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.gaitpost.2023.11.012","article-title":"Muscle coactivation during gait in children with and without cerebral palsy","volume":"108","author":"Ippersiel","year":"2024","journal-title":"Gait Posture"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1680","DOI":"10.1152\/jn.00580.2018","article-title":"Gait synergetic neuromuscular control in children with cerebral palsy at different Gross Motor Function Classification System levels","volume":"121","author":"Yu","year":"2019","journal-title":"J. Neurophysiol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1111\/dmcn.15068","article-title":"Muscle synergy structure and gait patterns in children with spastic cerebral palsy","volume":"64","author":"Goudriaan","year":"2022","journal-title":"Dev. Med. Child Neurol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1111\/dmcn.12826","article-title":"Muscle synergies and complexity of neuromuscular control during gait in cerebral palsy","volume":"57","author":"Steele","year":"2015","journal-title":"Dev. Med. Child Neurol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Bekius, A., Bach, M.M., van der Krogt, M.M., de Vries, R., Buizer, A.I., and Dominici, N. (2020). Muscle synergies during walking in children with cerebral palsy: A systematic review. Front. Physiol., 11.","DOI":"10.3389\/fphys.2020.00632"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Shuman, B.R., Schwartz, M.H., and Steele, K.M. (2017). Electromyography data processing impacts muscle synergies during gait for unimpaired children and children with cerebral palsy. Front. Comput. Neurosci., 11.","DOI":"10.3389\/fncom.2017.00050"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Graci, V., O\u2019Neill, M., Bloss, M., Akkem, R., Paremski, A.C., Sanders, O., and Prosser, L.A. (2024). A new methodological approach to characterize selective motor control in children with cerebral palsy. Front. Hum. Neurosci., 18.","DOI":"10.3389\/fnhum.2024.1330315"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/j.gaitpost.2023.07.002","article-title":"Muscle co-contraction and co-activation in cerebral palsy during gait: A scoping review","volume":"105","author":"Arvisais","year":"2023","journal-title":"Gait Posture"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/S1050-6411(00)00027-4","article-title":"Development of recommendations for SEMG sensors and sensor placement procedures","volume":"10","author":"Hermens","year":"2000","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"102438","DOI":"10.1016\/j.jelekin.2020.102438","article-title":"Consensus for experimental design in electromyography (CEDE) project: Amplitude normalization matrix","volume":"53","author":"Besomi","year":"2020","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_31","first-page":"135","article-title":"Quantitative assessment of co-contraction at the ankle joint in walking","volume":"25","author":"Falconer","year":"1985","journal-title":"Electromyogr. Clin. Neurophysiol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1007\/s001670000130","article-title":"Dynamic stability after ACL injury: Who can hop?","volume":"8","author":"Rudolph","year":"2000","journal-title":"Knee Surg. Sport. Traumatol. Arthrosc."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.jbiomech.2017.03.029","article-title":"Comparison of methodologies to assess muscle co-contraction during gait","volume":"57","author":"Souissi","year":"2017","journal-title":"J. Biomech."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Varma, S., and Simon, R. (2006). Bias in error estimation when using cross-validation for model selection. BMC Bioinform., 7.","DOI":"10.1186\/1471-2105-7-91"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","article-title":"Extremely randomized trees","volume":"63","author":"Geurts","year":"2006","journal-title":"Mach. Learn."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1639","DOI":"10.1016\/j.jbiomech.2008.03.015","article-title":"The effect of walking speed on the gait of typically developing children","volume":"41","author":"Schwartz","year":"2008","journal-title":"J. Biomech."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.1016\/j.jelekin.2013.06.002","article-title":"Walking speed effects on the lower limb electromyographic variability of healthy children aged 7\u201316 years","volume":"23","author":"Tirosh","year":"2013","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_38","unstructured":"Goudriaan, M. (2026, July 07). Dataset. Figshare. Available under CC BY 4.0. Available online: https:\/\/figshare.com\/articles\/dataset\/Dataset\/13123175\/1."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Tao, W., Zhang, X., Chen, X., Wu, D., and Zhou, P. (2015). Multi-scale complexity analysis of muscle coactivation during gait in children with cerebral palsy. Front. Hum. Neurosci., 9.","DOI":"10.3389\/fnhum.2015.00367"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.neuroimage.2017.06.061","article-title":"Cross-validation failure: Small sample sizes lead to large error bars","volume":"180","author":"Varoquaux","year":"2018","journal-title":"NeuroImage"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/17\/5434\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T07:53:49Z","timestamp":1788335629000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/17\/5434"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,27]]},"references-count":40,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["s26175434"],"URL":"https:\/\/doi.org\/10.3390\/s26175434","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,27]]}}}