Published in medRxiv, 2025
Short-term variability in chronic musculoskeletal pain is clinically significant, correlating with pain severity and providing insights for personalized pain management.
Recommended citation: Zheng, X., Rajwal, S., Ho, S. Y. S., Ashworth, C., Seymour, B., Shenker, N., & Mancini, F. (2025). Short-term variability of chronic musculoskeletal pain. medRxiv, 2025-01. https://doi.org/10.1101/2025.01.12.25320413
Published in Neurobiology of Language (under review), 2024
Word recognition involves left-lateralized selection and bilateral competition, with concrete words driving competition and semantic features affecting activation without lateralization.
Recommended citation: under review under review
Published in Zenodo, 2024
This continuous pain rating task assesses pain intensity using the open-source software PsychoPy hosted on Pavlovia.
Recommended citation: Zheng, X., Rajwal, S., Ho, S. Y. S., Ashworth, C., Seymour, B., Shenker, N., & Mancini, F. (2024). Psychopy based Continuous Pain Monitoring Task (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.13754802 https://doi.org/10.5281/zenodo.13754802
Published in Computational and Mathematical Methods in Medicine, 2020
The motor-imagery brain-computer interface (MI-BCI) system improves by using command combinations and transfer learning to reduce calibration time and increase accuracy.
Recommended citation: Zheng, X., Li, J., Ji, H., Duan, L., Li, M., Pang, Z., ... & Tianhao, G. (2020). Task Transfer Learning for EEG Classification in Motor Imagery‐Based BCI System. Computational and Mathematical Methods in Medicine, 2020(1), 6056383. https://doi.org/10.1155/2020/6056383
Published in IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020
A motor imagery-based BCI using zero-shot learning reduces calibration time and achieves 91.81% of traditional method accuracy.
Recommended citation: Duan, L., Li, J., Ji, H., Pang, Z., Zheng, X., Lu, R., ... & Zhuang, J. (2020). Zero-shot learning for EEG classification in motor imagery-based BCI system. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(11), 2411-2419. https://doi.org/10.1109/TNSRE.2020.3027004