Projects
A new generation of flexible high resolution neural electronic interfaces. KU Leuven
A new generation of flexible high resolution neural electronic interfaces. KU Leuven
SCATMAN : Stroke CAvities Treatment Mechanism with Active Neural interfaces KU Leuven
Cerebrovascular accident (stroke) is the second leading cause of chronic disability and death. New
strokes affect 10.3 million people per year worldwide. The amount of stroke survivors is
increasing, but many remain with severe post-traumatic symptoms. Hence, stroke is a major
economic burden, with a cost of around 45 billion € in Europe in 2017 alone. Only 44% of this cost
is due to the initial treatment, the remaining ...
Neural decoding for brain-machine interfaces KU Leuven
Brain-computer interfaces provide a communication pathway between the human brain and an external machine, typically a computer. Two major approaches exist: invasive or intracranial and non-invasive brain-machine interfaces (BMIs). In the field of intracranial BMIs, attention has mainly been focused on recordings in the motor system.
The aim of this project is to decode neural activity recorded in different cortical areas e.g. the ...
Exploring the neural coding in behaving animals by novel optogenetic, high-density microrecordings and computational approaches: Towards cognitive Brain-Computer Interfaces (ENLIGHTENMENT). University of Antwerp
Engulfment and imaging of 3D diamond nanoelectrode arryas for neural interfaces Hasselt University
Active neural interface system for stroke cavities treatment KU Leuven
Cerebrovascular accident (stroke) is the second leading cause of chronic disability and death. New strokes affect 10.3 million people per year worldwide. The amount of stroke survivors is increasing, but many remain with severe post-traumatic symptoms. Hence, stroke is a major economic burden, with a cost of around 45 billion € in Europe in 2017 alone. Only 44% of this cost is due to the initial treatment, the remaining 56% is related to the ...
Signal processing algorithms for attention decoding of brain responses to natural stimuli in brain-computer interfaces KU Leuven
Brain-computer interfaces (BCI) enable the human brain to interact with machines, opening doors to various high-impact applications. However, most experimental BCI paradigms require the user to concentrate on synthetic and repeated stimuli, inducing fatigue and interfering with natural behavior. This unnatural interaction blocks the widespread usage of BCIs in daily-life situations beyond a few niche clinical applications.
In this ...