ChatEMG: Synthetic Data Generation to Control a Robotic Hand Orthosis for Stroke

• Published in: IEEE robotics and automation letters Vol. 10; no. 2; pp. 907 - 914
• Main Authors: Xu, Jingxi, Wang, Runsheng, Shang, Siqi, Chen, Ava, Winterbottom, Lauren, Hsu, To-Liang, Chen, Wenxi, Ahmed, Khondoker, Rotta, Pedro Leandro La, Zhu, Xinyue, Nilsen, Dawn M., Stein, Joel, Ciocarlie, Matei
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.02.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Context; Data collection; Data models; Datasets; Electromyography; End effectors; Generative AI; Motors; Orthoses; prosthetics and exoskeletons; rehabilitation robotics; Robot control; Robots; Signal generation; Stroke; Stroke (medical condition); Synthetic data; Training; Training data; Urban areas; wearable robotics

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 different conditions, sessions, and subjects, making it hard for classifiers to generalize. Traditional approaches require a...