ASSISTIVE COMMUNICATION FOR
PEOPLE WITH DISABILITIES
MULTI-INSTITUTE ACADEMIC COURSE
BRAIN-COMPUTER INTERFACES
The course is dedicated to teaching the theory and practice of developing brain-computer interfaces(BCI). The students learn about:
-
EEG sensors and data acquisition
-
Digital preprocessing and feature extraction
-
Machine learning classification algorithms
-
User interfaces and IoT
The course offers Matlab & Python based functions and architecture, ready for implementation using open-source toolboxes.
ALS MENTORS
Through collaboration with the IsrALS foundation, the students are teamed with volunteer ALS mentors. The BCI tools are then individually customized to fit the physical needs of the mentor while the algorithms are optimized to the mentor's
specific brain signals.
COMMUNICATION
SOLUTIONS
People with amyotrophic lateral sclerosis (ALS) gradually lose the ability to communicate, relying on eye-tracking or other assistive communication devices. As the disease progresses, some patients are unable to use these as well, leaving them without any means of expression with their family and caretakers.
We are creating solutions for this problem.
REAL-WORLD
PROBLEM SOLVING
Every ALS patient has specific and individual needs that need identifying and characterizing. Solutions that range from "Help" buttons, playing with their children, and manipulating microscopes. Each challenge is met by a dedicated team of students which work to apply a BCI solution to the problem.
SOCIAL IMPACT
We believe in translational science that harnesses cutting-edge research to transform people's lives, create and encourage beneficial social impact.
COLLABORATIONS
& MORE INFO
We are always looking for collaborators and partners that will allow us to grow and improve the project. We aim to provide the tailor-made BCI systems to the mentors for as long as they are needed.
Meet The Team
National Team
Dr. Oren Shriki
Project academic lead
Oren is the head of the cognitive and brain sciences department at Ben Gurion University. His research uses mathematical analyses of brain activity and a wide range of machine learning algorithms to develop BCI and novel diagnostic tools for neurological and psychiatric disorders.