BIOSENSIT: Real-time signal processing of label-free biosensor signals for robustness and speed of measurement improvement

• Unité de recherche: INNOSUISSE
• Numéro de projet: 14658.1;6 PFNM-NM
• Titre du projet anglais: BIOSENSIT: Real-time signal processing of label-free biosensor signals for robustness and speed of measurement improvement

Description succincte (Anglais)

BIOSENSIT: Real-time signal processing of label-free biosensor signals for robustness and speed of measurement improvement

Description succincte (Français)

BIOSENSIT: Real-time signal processing of label-free biosensor signals for robustness and speed of measurement improvement

Résumé des résultats (Abstract) (Anglais)

The objective of the project is the development of a user-friendly and cost-effective bioanalytical device for the detection of water contaminants. The device will be based on a recently developed solution for the fluid handling and bioassay control. To provide shortest detection time and thereby highest effectiveness in water contaminant assessment costs, an innovative process optimization strategy based on a closed loop structure and model based early assessment of the dynamic evolution of reaction kinetics will be developed. The reliability of early assessment shall be ensured through advanced signal processing algorithms providing simultaneously parsimonious model representation and model reliability stratification. In this way, water contaminants assessment time shall be reduced considerably such as to allow environmental monitoring in an autonomous modus at the top end of cost-effectiveness.

Résumé des résultats (Abstract) (Français)

The objective of the project is the development of a user-friendly and cost-effective bioanalytical device for the detection of water contaminants. The device will be based on a recently developed solution for the fluid handling and bioassay control. To provide shortest detection time and thereby highest effectiveness in water contaminant assessment costs, an innovative process optimization strategy based on a closed loop structure and model based early assessment of the dynamic evolution of reaction kinetics will be developed. The reliability of early assessment shall be ensured through advanced signal processing algorithms providing simultaneously parsimonious model representation and model reliability stratification. In this way, water contaminants assessment time shall be reduced considerably such as to allow environmental monitoring in an autonomous modus at the top end of cost-effectiveness.