Projects

The possibility to chronically monitor the brain 24/7 in daily-life activities would revolutionize human-machine interactions through the use of brain-computer interfaces (BCI). Such chronic systems must satisfy challenging energy and miniaturization constraints, leading to modular designs in which multiple networked miniature neuro-sensor modules form a ‘neuro-sensor network’ (NSN). However, current multi-channel neural signal processing ...

Recent technological advances in analogue and digital electronics as well as in hardware miniaturization have taken wireless sensing devices to another level by introducing low-power communication protocols, improved digital signal processing capabilities and compact sensors. When these devices perform a certain pre-defined signal processing (SP) task such as the estimation or detection of phenomena of interest, a cooperative scheme through ...

Electroencephalography or EEG can be used in a wide range of applications like diagnosing disorders like epilepsy, Brain Computer Interfaces or in neural prostheses. These mentioned applications require continuous EEG monitoring. They are what we call chronic neuromonitoring applications. Chronic neuromonitoring is impractical with traditional bulky EEG headsets. But recent surge of miniature EEG devices make it possible. But these devices ...

Signal processing algorithms for the acquisition, analysis, and reproduction of sound fields, generally rely on the availability of some geometric information on the sound scene in the form of sound source and microphone positions. In this PhD project, we will use mathematical tools from Euclidian geometry and multi-dimensional scaling to redesign these signal processing algorithms by replacing the required position information by distance ...

Extending the reach of DSL services (VDSL2, G.FAST, G.mgFAST) into previously unserved areas requires additional physical layer signal processing algorithms, to compensate for longer channel impulse responses that are otherwise no longer compatible with the used modulation formats. The project is aimed at developing such signal processing algorithms, in particular for channel shortening in combination with current multi-user vectoring schemes ...

The possibility to chronically monitor the brain 24/7 in daily-life activities would revolutionize human-machine interactions through the use of brain-computer interfaces (BCI) and would allow for ambulant monitoring of patients with neurological disorders. Such chronic systems must satisfy challenging energy and miniaturization constraints, leading to modular designs in which multiple networked miniature neuro-sensor modules are ...

The objective of this PhD project is to challenge the widely accepted premise that single-microphone audio analysis cannot rely on spatial or wavenumber domain signal representations. This premise implies that the spatial diversity of acoustic environments (e.g. spatial spreading of sound sources) cannot be exploited in single-microphone devices, hence limiting their applicability in a wide variety of speech and audio applications, including ...

The ambulatory electrocardiography (AECG) records the ECG while the patient is doing real-life activities. It allows the study of transient phenomena and cases of fatal arrhythmic events, including sudden cardiac death. However, noise and artifacts can corrupt the AECG signal which downgrades the underlying diagnostic information. This research focuses on the development of new machine-learning-based methods for improving the processing of ...