171006 20260430151736.0 doi 10.1098/rsfs.2025.0063 sideral 149075 ART-2026-149075 eng Grison, Agnese Intramuscular microelectrode arrays enable highly accurate neural decoding of finger tasks 2026 Decoding the activity of the nervous system is a critical challenge in neuroscience and neural interfacing. In this study, we present a neuromuscular recording system that enables large-scale sampling of muscle activity using microelectrode arrays with over 100 channels embedded in forearm muscles. These arrays captured intramuscular high-density signals that were decoded into patterns of activation of spinal motoneurons. In two healthy participants, we recorded high-density intramuscular activity during single- and multi-digit contractions, revealing distinct motoneuron recruitment patterns specific to each task. Based on these patterns, we achieved perfect classification accuracy (100%) for 12 single- and multi-digit tasks and over approximately 96% accuracy for up to 16 tasks, significantly outperforming state-of-the-art electromyogram classification methods. This intramuscular high-density system and classification method represent an advancement in neural interfacing, with the potential to improve human–computer interaction and the control of assistive technologies, particularly for replacing or restoring impaired motor function. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/EC/HORIZON EUROPE/101077693/EU/Extracting the Human Motor Null Space from Muscles - A new framework to measure human neural activity/ECHOES info:eu-repo/grantAgreement/ES/MICINN/CNS2022-135366 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Ibáñez, Jaime Universidad de Zaragoza (orcid)0000-0001-8439-151X Muceli, Silvia Kundu, Aritra Baracat, Farah Ashraf Moustafa Mahmoud Indiveri, Giacomo Donati, Elisa Farina, Dario 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 16, 1 (2026), [15 pp.] Interface focus Interface focus 2042-8898 8341600 http://zaguan.unizar.es/record/171006/files/texto_completo.pdf Versión publicada 2622121 http://zaguan.unizar.es/record/171006/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:171006 articulos driver 2026-04-30-13:58:53 ARTICLE