[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128409-en":3,"doc-seo-128409-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},128409,8796095027276,"Valentina","https://avatar.qwps.com/avatar/d3BzX2FwX3Rlc3RfMjUxMTI2XzAxODA=",8,"Research & Report","A multimodal machine learning approach to forecast upper limb motor recovery after stroke using kinematic and electromyographic data - a pilot study","Forecasting post-stroke rehabilitation outcomes is essential for personalizing therapy, yet clinical assessment scales can be complemented by objective signal-based measures. This study uses multimodal features gathered during robotic assessment sessions conducted before and after one month of rehabilitation to forecast upper-limb motor recovery. A four-week program combining standard physical therapy and the ALEx robot was evaluated in subacute stroke survivors and healthy individuals using kinematics and sEMG features, enabling both recovery regression and anomaly detection.","J NeuroEngineering Rehabil  \n[https://doi.org/10.1186/s12984-025-01796-5](https://doi.org/10.1186/s12984-025-01796-5)  \n\n| Article in Press |\n| --- |\n| A multimodal machine learning approach to forecast upper limb motor recovery after stroke using kinematic and electromyographic data-a pilot-study |\n\nReceived: 9 May 2025  \n\n| Accepted: 29 October 2025 |\n| --- |\n|  |\n\nCite this article as: Privitera L., Lassi M.,  \nDalise S. et al. A multimodal machine learning approach to forecast upper limb motor recovery after stroke using  \nkinematic and electromyographic  \ndata-a pilot-study. JNeuroEngineering Rehabil (2026). [https://doi.org/10.1186/](https://doi.org/10.1186/)[ ](https://doi.org/10.1186/)[s12984-025-01796-5](s12984-025-01796-5)  \nLuigi Privitera, Michael Lassi, Stefania Dalise, Valentina Azzollini, Luca Maggiani, Adrian Guggisberg, Alberto Mazzoni, Carmelo Chisari, Silvestro Micera & Andrea Bandini  \nWe are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.  \nIf this paper is publishing under a Transparent Peer Review model then Peer Review reports will publish with the final article.  \n© The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/) .  \nARTICLE IN PRESS  \nA multimodal machine learning approach to forecast upper limb motor recovery after stroke using kinematic and electromyographic data-A  \npilot-study  \nLuigi Privitera 1,2*, Michael Lassi 1 , Stefania Dalise3 , Valentina Azzollini4 , Luca Maggiani4 , Adrian Guggisberg5,6 , Alberto Mazzoni 1 , Carmelo Chisari3,4 , Silvestro Micera 1,7,8 ,  \nAndrea Bandini 1,9  \n1* The BioRobotics Institute and the Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy.  \n2 School of Advanced Studies, Universit`a di Camerino, Camerino,Italy.  \n3 Neurorehabilitation Unit, Department of Neuroscience, University Hospital of Pisa, Pisa, Italy.  \n4 Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.  \n5 Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital Geneva, Geneva, Switzerland.  \n6 Laboratory of Cognitive Neurorehabilitation, Department of Clinical Neurosciences, Medical School, University of Geneva, Geneva,  \nSwitzerland.  \n7 Modular Implantable Neuroprostheses (MINE) Laboratory, Universit`a Vita-Salute San Raffaele, Milan, Italy.  \n8 Translational Neural Engineering Laboratory, Neuro-X Institute, ´Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland.  \n9 Interdisciplinary Research Center ”Health Science”, Scuola Superiore Sant’Anna, Pisa, Italy.  \n*Corresponding author(s) . E-mail(s): luigi.privitera@santannapisa.it ;  \nARTICLE IN PRESS  \nAbstract  \nBackground: Forecasting post-stroke rehabilitation outcome i","cbCaihKSKT06vPin","https://ap.wps.com/l/cbCaihKSKT06vPin","pdf",2234297,2,1,38,"English","en",105,"# Article in Press\n## Background\n## Methods\n## Results","[{\"question\":\"What problem does the study address?\",\"answer\":\"It targets the need to forecast post-stroke upper-limb rehabilitation outcomes to support more personalized therapeutic strategies.\"},{\"question\":\"What data and tasks were used to build the model?\",\"answer\":\"Kinematic measures and surface electromyography (sEMG) were collected during a 3D reaching task with six target points before and after one month of robotic rehabilitation.\"},{\"question\":\"How does the approach predict motor recovery?\",\"answer\":\"It uses a two-step machine learning pipeline: a regression model predicts post-rehabilitation Fugl-Meyer Assessment for the upper limb (FMA-UL), while an autoencoder-based anomaly detection flags patients with limited or no recovery.\"}]","A multimodal machine learning approach to forecast upper limb motor recovery after stroke using kinematic and electromyographic data - a pilot study | PDF",1785947350,96,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"a-multimodal-machine-learning-approach-to-forecast-upper-limb-motor-recovery-after-stroke-using-kinematic-and-electromyographic-data-a-pilot-study","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/a-multimodal-machine-learning-approach-to-forecast-upper-limb-motor-recovery-after-stroke-using-kinematic-and-electromyographic-data-a-pilot-study/128409/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-28","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem does the study address?","Question",{"text":76,"@type":77},"It targets the need to forecast post-stroke upper-limb rehabilitation outcomes to support more personalized therapeutic strategies.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What data and tasks were used to build the model?",{"text":81,"@type":77},"Kinematic measures and surface electromyography (sEMG) were collected during a 3D reaching task with six target points before and after one month of robotic rehabilitation.",{"name":83,"@type":74,"acceptedAnswer":84},"How does the approach predict motor recovery?",{"text":85,"@type":77},"It uses a two-step machine learning pipeline: a regression model predicts post-rehabilitation Fugl-Meyer Assessment for the upper limb (FMA-UL), while an autoencoder-based anomaly detection flags patients with limited or no recovery.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]