Intramuscular microelectrode arrays enable highly accurate neural decoding of finger tasks
Artikel i vetenskaplig tidskrift, 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.
motor control
intramuscular electromyogram
human-machine interfaces
motoneuron
Författare
Agnese Grison
Imperial College London
Jaime Ibanez
Universidad de Zaragoza
CIBER - Centro de Investigación Biomédica en Red
Silvia Muceli
Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik
Aritra Kundu
Imperial College London
Farah Ashraf Moustafa Mahmoud Baracat
Eidgenössische Technische Hochschule Zürich (ETH)
Universität Zürich
Giacomo Indiveri
Eidgenössische Technische Hochschule Zürich (ETH)
Universität Zürich
Elisa Donati
Eidgenössische Technische Hochschule Zürich (ETH)
Universität Zürich
Dario Farina
Imperial College London
Interface Focus
2042-8898 (ISSN) 2042-8901 (eISSN)
Vol. 16 1 20250063Hybrid neuroscience based on cerebral and muscular information for motor rehabilitation and neuromuscular disorders
Europeiska kommissionen (EU) (EC/HE/101079392), 2022-12-01 -- 2025-12-31.
Ämneskategorier (SSIF 2025)
Neurovetenskaper
Fysiologi och anatomi
DOI
10.1098/rsfs.2025.0063