Group Members
Please add @essex.ac.uk to the e-mail addresses shown under the names below
Permanent Academics
Senior
Researchers
Dr. Caterina
Cinel
(ccinel)
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Dr. Mathew
Salvaris
(mssalv)
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Ph.D. Students
(in alphabetical order)
Luz
Maria Alonso V.:
Project: A Virtual Environment
Platform for Simulated BCI-Enabled Independent Living
The aim of this project is to design and develop a Virtual Environment (VE),
involving auditory and visual systems, in order to research several mental
patterns which are elicited by the interaction between the user and the devices
into the VE. The focus will be on brain control of the environment and on the
effects this interaction will have on the brain signals. The platform will
allow for more realistic testing of BCI methods for independent living for
disabled individuals.
Tugce Balli:
Project: Non Linear Methods for
Biomedical Time Series Analysis
Linear modelling techniques have been widely used in the literature for analysis
of biological time series (e.g., EEG) as they are simpler in principle compared
to their non-linear counterpart. However conventionally used linear modelling
techniques would fail to capture the nonlinearities in time series. It is a
known fact that the individual neurons in the brain behave in a nonlinear way
thus we can expect a huge network of those individual neurons to do so. Because
of that, there has been an increasing interest in using nonlinear methods for
analysis of biological time series. In this research we set out to investigate
nonlinear modelling and feature extraction techniques for the analysis of
biological signals.
Navin Cota:
Project: High Security Authentication Using Brain's Electrical Response Patterns
Automatic verification is very important in ensuring security for access to
restricted areas (like control gates and military applications). My proposed
doctoral research will authenticate users using their brain signals in response
to a sequence of on screen stimuli (say pictures). The advantage of using such
brain electrical activity as biometric is its fraud resistance. Objectives for
the proposed research work include developing suitable paradigms and analysis
frameworks for an online BCI based biometric system.
Mathew Dyson:
Project: Mental Tasks and Location Selection for Asynchronous BCIs
Bashar Awwad
Shiekh Hasan:
Project: Adaptive Asynchronous BCIs
The
goal of this project is to develop probabilistic classification models to better
handle the modelling of temporal and spatial information of EEG data within
self-paced BCI settings. Adaptive algorithms of these models will also be
developed to handle the non-stationarity problem of EEG data in general and
especially for motor-imagery self-paced BCI. Intelligent user interfaces will be
investigated to better obtain online labels that can help the BCI system to
adapt better to the ongoing data.
Badr Hubais:
Project: BCI control of Robotic
Arm
The main objective this project is to build a system that can translate brain
activity through EEG to direct commands for a robotic arm. The commands the
systems attempts to translate are the EEG of wrist movement and "imaginary"
wrist movement.
C. S. Louis Tsui:
Project: Adaptive Asynchronous Brain-Actuated Robotic Control
My project aims to develop a motor imagery based
adaptive asynchronous BCI for robotic control. Although self-paced BCIs offer
more natural human machine interaction, the lack of indications of the user's
control intentions and timing brings about challenges in design and performance
evaluation. A new asynchronous BCI paradigm has been designed for providing
information about class labels (user's control intention and timing) during
online experiments, so that online training and adaptation of self-paced BCI can
be effectively investigated.
John Wilson
Project: Visual
and Audio Evoked Potentials for BCIs
Using
Visual (SSVEP) and Audio (ASSR) Steady State Evoked Potentials to build a viable
Brain Computer Interface. By tagging stimuli with distinct temporal frequencies
it is possible to determine the attention of a subject through spectral analysis
of a recorded EEG signal. A subject can then make choices by simply focusing or
listening to the stimuli they desire.
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Former Group Members
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Dr. Ramaswami Palaniappan, 2006-2012, now at the University of Kent
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Dr. Tao Geng, post-doctoral researcher from 2006 to 2008
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Dr. Yusuf
Khan, visiting researcher from Oct. 2007 to April 2008
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Dr. Aleksandra
Vuckovic, post-doctoral researcher until Aug., 2007
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Cristian
Nikolajsen and Esben Wermuth, from Aalborg University, visiting MSc
students in the Autumn 2007
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Dr. Heba
Lakany, lecturer until Aug., 2007
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Dr. Shang-Ming
Zhang, PhD student until 2006
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Israel Navarro,
PhD student in 2004/2005
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