Descripción del proyecto
Una manera inteligente de monitorizar el cerebro
Los algoritmos del procesamiento de señales neuronales (NSP, por sus siglas en inglés) distribuidos y modulables permiten que los módulos de una red de neurosensores (NSN, por sus siglas en inglés) procese conjuntamente los datos neuronales registrados mediante la fusión de datos en red y con un intercambio mínimo de datos. Eso permitiría a los médicos monitorizar el cerebro a lo largo de todo el día, en las actividades cotidianas y, a su vez, revolucionar las interacciones persona-máquina y la asistencia sanitaria. El proyecto DISPATCH Neuro-Sense, financiado con fondos europeos, trabajará para diseñar estos nuevos algoritmos NSP. Se centrará en establecer un nuevo concepto NSN no invasivo basado en la electroencefalografía (EEG). La combinación de múltiples módulos de mini-EEG «inteligentes» en una «red de sensores EEG» (EEG-Net) paliará la falta de información espacial recogida por los actuales dispositivos mini-EEG independientes, sin comprometer la «ponibilidad».
Objetivo
The possibility to chronically monitor the brain 24/7 in daily-life activities would revolutionize human-machine interactions and health care, e.g. in the context of neuroprostheses, neurological disorders, and 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 (NSP) algorithms were designed for traditional neuro-sensor arrays with central access to all channels. These algorithms are not suited for NSNs, as they require unrealistic bandwidth budgets to centralize the data, yet a joint neural data analysis across NSN modules is crucial.
The central idea of this project is to remove this algorithm bottleneck by designing novel scalable, distributed NSP algorithms to let the modules of an NSN jointly process the recorded neural data through in-network data fusion and with a minimal exchange of data.
To guarantee impact, we mainly focus on establishing a new non-invasive NSN concept based on electroencephalography (EEG). By combining multiple ‘smart’ mini-EEG modules into an ‘EEG sensor network’ (EEG-Net), we compensate for the lack of spatial information captured by current stand-alone mini-EEG devices, without compromising in ‘wearability’. Equipping such EEG-Nets with distributed NSP algorithms will allow to process high-density EEG data at viable energy levels, which is a game changer towards high-performance chronic EEG for, e.g. epilepsy monitoring, neuroprostheses, and BCI.
We will validate these claims in an EEG-Net prototype in the above 3 use cases, benefiting from ongoing collaborations with the KUL university hospital. In addition, to demonstrate the general applicability of our novel NSP algorithms, we will validate them in other emerging NSN types as well, such as modular or untethered neural probes.
Ámbito científico
- natural sciencescomputer and information sciencesdata science
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsignal processing
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorssmart sensors
- medical and health sciencesbasic medicineneurology
Palabras clave
Programa(s)
Régimen de financiación
ERC-STG - Starting GrantInstitución de acogida
3000 Leuven
Bélgica