{"id":21221,"date":"2026-02-11T16:54:48","date_gmt":"2026-02-11T15:54:48","guid":{"rendered":"https:\/\/www.technaid.com\/nuevo-control-del-exoesqueleto-para-interfaces-mas-seguras\/"},"modified":"2026-02-11T17:06:04","modified_gmt":"2026-02-11T16:06:04","slug":"nuevo-control-del-exoesqueleto-para-interfaces-mas-seguras","status":"publish","type":"post","link":"https:\/\/www.technaid.com\/es\/nuevo-control-del-exoesqueleto-para-interfaces-mas-seguras\/","title":{"rendered":"Nuevo control del exoesqueleto para interfaces m\u00e1s seguras"},"content":{"rendered":"\n<p>En su art\u00edculo \u201c<a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0169260724003250\" target=\"_blank\" rel=\"noreferrer noopener\">Design of a brain-machine interface for reducing false activations of a lower-limb exoskeleton based on error related potential<\/a>\u201d, Soriano-Segura y colaboradores abordan uno de los cuellos de botella cl\u00e1sicos de las brain-machine interfaces basadas en imaginaci\u00f3n motora para control de exosqueletos: las falsas activaciones. En lugar de confiar \u00fanicamente en el clasificador de MI, el equipo propone integrar los potenciales relacionados con el error (ErrP) como una capa adicional de supervisi\u00f3n. Para ello dise\u00f1an un protocolo espec\u00edfico para evocar ErrP asociados a activaciones incorrectas del exoesqueleto de miembro inferior, y desarrollan un m\u00e9todo iterativo de selecci\u00f3n de par\u00e1metros que optimiza la detecci\u00f3n de estos potenciales en EEG. El resultado es una BMI capaz de autocorregir comandos err\u00f3neos en tiempo casi real, con un impacto directo sobre la seguridad y la usabilidad del sistema durante la marcha asistida con el <a href=\"https:\/\/www.technaid.com\/es\/productos\/robotic-exoskeleton-exo-h3\/\">Exo-H3<\/a>.   <\/p>\n\n<p>El trabajo m\u00e1s reciente, \u201c<a href=\"https:\/\/link.springer.com\/article\/10.1186\/s12984-025-01833-3https:\/\/link.springer.com\/article\/10.1186\/s12984-025-01833-3\" target=\"_blank\" rel=\"noreferrer noopener\">Characterization of error-related potentials during the command of a lower-limb exoskeleton based on deep learning<\/a>\u201d, se apoya en esa base y da un paso m\u00e1s en dos direcciones clave: caracterizaci\u00f3n detallada del ErrP en tareas de marcha con exoesqueleto y mejora de su detecci\u00f3n mediante deep learning. En este caso, el grupo emplea la red EEG-Inception como modelo convolucional para identificar ErrP durante el inicio y la detenci\u00f3n de la marcha asistida, primero en condiciones est\u00e1ticas y posteriormente en movimiento. Adem\u00e1s, introducen t\u00e9cnicas de data augmentation para abordar el desbalanceo inherente de los datasets de ErrP. Los resultados muestran una mejora en precisi\u00f3n y robustez frente a clasificadores tradicionales, confirmando que la combinaci\u00f3n de modelos profundos y protocolos espec\u00edficos de evocaci\u00f3n permite explotar mejor la se\u00f1al cerebral asociada al error durante el uso del exoesqueleto.   <\/p>\n\n<p>Considerados en conjunto, estos dos estudios avanzan hacia una arquitectura de control de exosqueletos en la que el usuario no solo genera comandos de marcha a trav\u00e9s de la BMI, sino que tambi\u00e9n \u201ceval\u00faa\u201d y corrige de forma impl\u00edcita el comportamiento del robot mediante sus propias respuestas neurales. La integraci\u00f3n de ErrP, primero como mecanismo de reducci\u00f3n de falsas activaciones y despu\u00e9s como se\u00f1al explotada con modelos de deep learning, ilustra un camino claro para aumentar la fiabilidad de las interfaces cerebro-m\u00e1quina en rehabilitaci\u00f3n. M\u00e1s all\u00e1 de la mejora cuantitativa en m\u00e9tricas de clasificaci\u00f3n, la contribuci\u00f3n principal es conceptual: situar la monitorizaci\u00f3n continua de la interacci\u00f3n humano-robot en el centro del dise\u00f1o de control, un enfoque que previsiblemente se extender\u00e1 a futuras generaciones de sistemas de neurorrehabilitaci\u00f3n y exosqueletos rob\u00f3ticos.  <\/p>\n","protected":false},"excerpt":{"rendered":"<p>En su art\u00edculo \u201cDesign of a brain-machine interface for reducing false activations of a lower-limb exoskeleton based on error related potential\u201d, Soriano-Segura y colaboradores abordan uno de los cuellos de [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":21219,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"off","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[305],"tags":[680,307,309,613,679,316,324,308],"class_list":["post-21221","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-noticias-es","tag-bmi","tag-exoesqueletos-es","tag-innovacion-es","tag-investigacion-es","tag-mujeres-en-la-ciencia","tag-neurorrehabilitacion-es","tag-robotica-es","tag-technaid-es"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - 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