2 citations · 3 across the 4 of their papers we have counts for
4 papers
Spiking Neural Network Decoders of Finger Forces from High-Density Intramuscular Microelectrode Arrays
Farah Baracat, Agnese Grison, Dario Farina +2
Restoring naturalistic finger control in assistive technologies requires the continuous decoding of motor intent with high accuracy, efficiency, and robustness. Here, we present a…
Finger Force Decoding from Motor Units Activity on Neuromorphic Hardware
Farah Baracat, Giacomo Indiveri, Elisa Donati
Accurate finger force estimation is critical for next-generation human-machine interfaces. Traditional electromyography (EMG)-based decoding methods using deep learning require lar…
Heterogeneous Population Encoding for Multi-joint Regression using sEMG Signals
Farah Baracat, Luca Manneschi, Elisa Donati
Regression-based decoding of continuous movements is essential for human-machine interfaces (HMIs), such as prosthetic control. This study explores a feature-based approach to enco…
Intramuscular microelectrode arrays enable highly-accurate neural decoding of hand movements
Agnese Grison, Jaime Ibanez Pereda, Silvia Muceli +5
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…