Decoding motor neuron activity from epimysial thin-film electrode recordings following targeted muscle reinnervation
Artikel i vetenskaplig tidskrift, 2019

Objective. Surface electromyography (EMG) is currently used as a control signal for active prostheses in amputees who underwent targeted muscle reinnervation (TMR) surgery. Recent research has shown that it is possible to access the spiking activity of spinal motor neurons from multi-channel surface EMG. In this study, we propose the use of multi-channel epimysial EMG electrodes as an interface for decoding motor neurons activity following TMR. Approach. We tested multi-channel epimysial electrodes (48 detection sites) built with thin-film technology in an animal model of TMR. Eight animals were tested 12 weeks after reinnervation of the biceps brachii lateral head by the ulnar nerve. We identified the position of the innervation zone and the muscle fiber conduction velocity of motor units decoded from the multi-channel epimysial recordings. Moreover, we characterized the pick-up volume by the distribution of the motor unit action potential amplitude over the epimysium surface. Main results. The electrodes provided high quality signals with average signal-to-noise ratio >30 dB across 95 identified motor units. The motor unit action potential amplitude decreased with increasing distance of the electrode from the muscle fibers (P 0.001). The decrease was more pronounced for bipolar compared to monopolar derivations. The average muscle fiber conduction velocity was 2.46 ± 0.83 m s -1 . Most of the neuromuscular junctions were close to the region where the nerve was neurotized, as observed from the EMG recordings and imaging data. Significance. These results show that epimysial electrodes can be used for selective recordings of motor unit activities with a pick-up volume that included the entire muscle in the rat hindlimb. Epimysial electrodes can thus be used for detecting motor unit activity in muscles with specific fascicular territories associated to different functions following TMR surgery.


Silvia Muceli

Imperial College London

Konstantin D Bergmeister

Medizinische Universität Wien

Klaus-Peter Hoffmann

Fraunhofer-Institut fur Biomedizinische Technik (IBMT)

Martin Aman

Medizinische Universität Wien

Ivan Vukajlija

Imperial College London

Oskar C Aszmann

Medizinische Universität Wien

Dario Farina

Imperial College London

Journal of Neural Engineering

1741-2560 (ISSN) 17412552 (eISSN)

Vol. 16 1 016010







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