Faculty of Education and Human Development
 

Date 2015-01-28
Time 9:30 - 13:30
E-mail ednu@ied.edu.hk
Venue HKIEd Tai Po Campus B2-LP-01

EDNU January Technical Workshop: Using mobile EEG for research
 
Date: 28 Jan 2015 (Wed)
Time: 9:30 - 13:30
Venue: HKIEd Tai Po Campus B2-LP-01
Speakers: Dr. Lingling Yang and Winnie Ka-Yan So (Dept. of Electronic Engineering, City University of Hong Kong)
 
 
Lingling Yang is a research associate in Neural Interface Research Laboratory and Laboratory for Computational Neuroscience, City University of Hong Kong (CityU). She obtained her Ph.d degree in the department of Computer Science, CityU in Oct. 2014. Her research interests include brain computer interfaces, neural prosthetics, biomedical signal processing and machine learning.  She developed an online BCI game based on decoding of users' attention to color stimulus to make option selection using the EEG signal. Also she developed a mathematical model to predict the speed and acceleration of hand movement using EEG signals from movement planning during a reaching task.  Her work contributed to the brain computer interface development by improving the accuracy of movement estimation.  Now she is investigating the relationship between EEG signal and muscle activity for grasping.  
 
 
Winnie So is a graduate student in Laboratory for Computational Neuroscience, Department of Electronic Engineering, CityU. She earned her B.Eng in Biomedical Engineering from CUHK in 2014. She is also the co-founder of IEEE Engineering in Medicine & Biology Society CUHK student chapter. From 2012 to 2014, she worked as a research assistant involving in the biosensor technology related projects in Prof Rosa Chan’s laboratory and Neurosky, a manufacturer of Brain-Computer Interface technologies. Her research interests include bio-signal processing, brain computer interface and machine learning.  In her bachelor’s thesis, she studied EEG signal in sport motor imagery. Currently, she is investigating muscle synergies in sign language, real-time EEG in mental workload and executive function.