Richong Pang

Master, research assistant

Email: pangrichong@@gdiist.cn

Personal Profile:

Obtained a bachelor's degree from Dongguan University of Technology in 2020 ,Obtained a master's degree from Foshan University in China in 2023, studied at the Foshan Intelligent Rehabilitation Research Institute from 2021 to 2022. A member of the Foshan Biomedical Engineering Society. Joined the Joint Laboratory of BrainVerse Digitalization, Guangdong Institute of Intelligence Science and Technology in 2023 and served as a research assistant.

Research direction:

Research on brain computer interface decoding from electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) signals using traditional algorithm machine learning algorithms and deep learning algorithms, including motor imagery, steady-state visual evoked potentials, and working memory. Using fNIRS to study stroke rehabilitation techniques, including studying brain network reorganization in stroke patients and establishing a motor function guidance model.

Representative works:

1. Pang R, Wang D, Chen T S R, et al. Reorganization of prefrontal network in stroke patients with dyskinesias: Evidence from resting‐state functional near‐infrared spectroscopy[J]. Journal of Biophotonics, 2022, 15(7): e202200014.

2. Pang R, Sang H, Yi L, et al. Working memory load recognition with deep learning time series classification[J]. Biomedical Optics Express, 2024, 15(5): 2780-2797.

3. Sun J, Pang R, Chen S, et al. Near-infrared spectroscopy as a promising tool in stroke: Current applications and future perspectives[J]. Journal of Innovative Optical Health Sciences, 2021, 14(06): 2130006.

4. Sun J, Wang D, Chen S,Pang R, et al. The behavioral significance of resting state network after stroke: a study via graph theory analysis with near-infrared spectroscopy[J]. Medicine in Novel Technology and Devices, 2021, 11: 100083.