Tianjin University Neuroengineering Team was honored with the first Neuroscan Award by Compumedics Neuroscan, a world-leading developer of research equipment for neuroimaging, as a commending for outstanding achievements in weak EEG feature extraction.
Neuroscan, founded in 1985, is the world’s lead-ing provider of technologies for high-density EEG recordings, electro-magnetic source localization, multi-modal neuroimaging and enhancements to functional MRI. Neuroscan’s products are in use at over 1500 universities, corporate laboratories and national research institutes in approximately 40 countries. For the sake of promoting the development of brain science, Neuroscan Award was established for the first time this year by Neuroscan, which aims to dig and encourage scientific research teams and achievements in the field of neuroimaging and electrophysiological research worldwide.
Gordon J. Haid, Director of Neruoscan Neuroimaging Division, Robert Liao, Technical Director of Asia Pacific, and other guests attended the awards ceremony. Xu Minpeng, a teacher of TJU Neuroengineering Team, and Xiao Xiaolin, a Ph.D. student, accepted the award on behalf of the team. In awarding words, Mr. Gordon spoke highly of the extremely weak event-related potential extraction method developed by Tianjin University. He said that the team first introduced the spatial symmetry law of EEG into the design and construction of spatial filters and realized the accurate identification and efficient application of the weakest EEG control signal (approximately 0.5μV) to date in the world, making a breakthrough in the research of brain-computer interface (BCI) technology.
It is known that the IEEE Biomedical Engineering Newsletter (TBME) reported the research findings of the Tianjin University Neuroengineering Team as May 2018 issue cover image article, A brain-computer interface based on miniature event-related potentials induced by very small lateral visual stimuli. A novel weak EEG feature extraction technique proposed in this paper was the milestone for efficient extraction and application of EEG features below 1μV in the world. At the same time, the results were also selected as Feature Story by the official website of the EMBS Society, with cover story and in-depth reporting.
By: School of Precision Instruments and Optoectronics Engineering
Editor: Qin Mian and Keith Harrington
