1 citations · 1 across the 5 of their papers we have counts for
5 papers
Neuromorphic Deployment of Spiking Neural Networks for Cognitive Load Classification in Air Traffic Control
Jiahui An, Chonghao Cai, Olympia Gallou +3
This paper presents a neuromorphic system for cognitive load classification in a real-world setting, an Air Traffic Control (ATC) task, using a hardware implementation of Spiking N…
Spiking Neural Networks for Mental Workload Classification with a Multimodal Approach
Jiahui An, Sara Irina Fabrikant, Giacomo Indiveri +1
Accurately assessing mental workload is crucial in cognitive neuroscience, human-computer interaction, and real-time monitoring, as cognitive load fluctuations affect performance a…
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…
Towards spiking analog hardware implementation of a trajectory interpolation mechanism for smooth closed-loop control of a spiking robot arm
Daniel Casanueva-Morato, Chenxi Wu, Giacomo Indiveri +2
Neuromorphic engineering aims to incorporate the computational principles found in animal brains, into modern technological systems. Following this approach, in this work we propos…