4 papers · 1 filter
ReactEMG: Stable, Low-Latency Intent Detection from sEMG via Masked Modeling
Runsheng Wang, Xinyue Zhu, Ava Chen +5
Surface electromyography (sEMG) signals show promise for effective human-machine interfaces, particularly in rehabilitation and prosthetics. However, challenges remain in developin…
Meta-Learning for Fast Adaptation in Intent Inferral on a Robotic Hand Orthosis for Stroke
Pedro Leandro La Rotta, Jingxi Xu, Ava Chen +5
We propose MetaEMG, a meta-learning approach for fast adaptation in intent inferral on a robotic hand orthosis for stroke. One key challenge in machine learning for assistive and r…
ChatEMG: Synthetic Data Generation to Control a Robotic Hand Orthosis for Stroke
Jingxi Xu, Runsheng Wang, Siqi Shang +10
Intent inferral on a hand orthosis for stroke patients is challenging due to the difficulty of data collection. Additionally, EMG signals exhibit significant variations across diff…
Reciprocal Learning of Intent Inferral with Augmented Visual Feedback for Stroke
Jingxi Xu, Ava Chen, Lauren Winterbottom +5
Intent inferral, the process by which a robotic device predicts a user's intent from biosignals, offers an effective and intuitive way to control wearable robots. Classical intent…