A Data Augmentation Method for Motor Imagery EEG Signals Based on DCGAN-GP Network

X Du, X Ding, M Xi, Y Lv, S Qiu, Q Liu - Brain Sciences, 2024 - mdpi.com
Motor imagery electroencephalography (EEG) signals have garnered attention in brain–
computer interface (BCI) research due to their potential in promoting motor rehabilitation and …

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

J Xu, R Wang, S Shang, A Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
Intent inferral on a hand orthosis for stroke patients is challenging due to the difficulty of data
collection from impaired subjects. Additionally, EMG signals exhibit significant variations …

Inverse distance weighting to rapidly generate large simulation datasets

KM Kearney, JB Harley, JA Nichols - Journal of Biomechanics, 2023 - Elsevier
Obtaining large biomechanical datasets for machine learning is an ongoing challenge.
Physics-based simulations offer one approach for generating large datasets, but many …