|
|
|
|
|
|
||
|
||||||
|
Objectives The Centre for Brain-ComCBCR) focuses on fundamental and applied
brain-computer interface (BCI) research. Our research aims to understand the
neural mechanisms of motor and cognitive processes and quantify them from the
associated manifestations in brain signals. We are developing robust,
high-performance decoding algorithms using machine learning, especially deep
learning and signal processing approaches. We are interested in making an
impact by applying BCI to clinical applications, for instance,
neuro-rehabilitation, ADHD, anxiety, depression, sleep, and so on, as
assessments or therapeutics. We also aspire to develop digital puting Research (health solutions and tools for mental
health and brain science using Brain-computer Interface (BCI). Research Topics: ·
Cognitive, behavioural, and motor predictions from
brain signal ·
Deep learning algorithms for motor decoding for
non-invasive BCIs ·
Multiple hand functions decoding ·
Continuous motor intention and gait decoding ·
Understanding of cognitive mechanisms and
quantifying brain states from brain signals ·
Continuous attention, stress, fatigue, relaxation
detection ·
Affective computing for multimodal continuous
emotion classification ·
Silent speech decoding from multimodalities
(EEG/MEG/fMRI) ·
Decoding olfactory responses objectively from brain
signals ·
Explainable deep learning models for brain decoding
modelling
Collaborators
|
|
|
