3 papers
cs.HC2025
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…
cs.NE2025
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…
cs.HC2025
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…