1 citations · 1 across the 2 of their papers we have counts for
4 papers
LightBeam: An Accurate and Memory-Efficient CTC Decoder for Speech Neuroprostheses
Ebrahim Feghhi, Junlin Hu, Nima Hadidi +1
A promising pathway for restoring communication in patients with dysarthria and anarthria is speech neuroprostheses, which directly decode speech from cortical neural activity. Two…
Re-evaluating Position and Velocity Decoding for Hand Pose Estimation with Surface Electromyography
Nima Hadidi, Johannes Lee, Ebrahim Feghhi +2
Recent progress in real-time hand pose estimation from surface electromyography (sEMG) has been driven by the emg2pose benchmark, whose original baseline study concluded that veloc…
Time-Masked Transformers with Lightweight Test-Time Adaptation for Neural Speech Decoding
Ebrahim Feghhi, Shreyas Kaasyap, Nima Hadidi +1
Speech neuroprostheses aim to restore communication for people with severe paralysis by decoding speech directly from neural activity. To accelerate algorithmic progress, a recent…
SplashNet: Split-and-Share Encoders for Accurate and Efficient Typing with Surface Electromyography
Nima Hadidi, Jason Chan, Ebrahim Feghhi +1
Surface electromyography (sEMG) at the wrists could enable natural, keyboard-free text entry, yet the state-of-the-art emg2qwerty baseline still misrecognizes of character…