i-IronIC - Implantable/Wearable System for on-line Monitoring of Human Metabolic Conditions
Personalized therapies require accurate and frequent monitoring of the metabolic response of living tissues to treatments. On-line monitoring of patients with specific physiological conditions (e.g., heart, cardiovascular, cancer diseases) is a key factor to provide better, more rationale, effective and ultimately low-cost health care. This is also required in professionals and recreational sportsmen training, as well as in elderly or disabled citizen care. Metabolism monitoring is a complex, slow and expensive process, mainly because of the unavailability of accurate, fast and affordable sensing devices that can detect and quantify multiple active compounds in parallel and several times a day. Indeed, systems available on the market use wearable devices (accelerometers, heartbeat monitoring system, etc) but do not measure metabolites. The only available real-time, implantable/ wearable systems for metabolic control are limited to glucose monitoring and used by diabetic patients. However, many different molecules present crucial relevance in human metabolism. They are monitored daily in general hospital practice by automatic blood sampling, but the analysis involves using off-line, large and expensive laboratory equipments. This project seeks to develop research in the field of integrated smart biosensors for online metabolism analysis that significantly improves the quality and reliability of human measurements, while at the same time reducing analysis time and cost. The new system will investigate many different metabolic compounds of interest in cardiovascular diseases as well as inflammatory diseases and personalized nutrition, such as lactate, cholesterol, ATP, and others. To pursue this aim, an innovative technology will be developed by integrating software/hardware/ RF/micro/nano/bio systems in three devices: a fully implantable sensors array for data acquisition, a wearable station for remote powering and signal processing and a remote station for data collection and storage. Apart from multi-panel sensors capable of sensing several metabolites in parallel and in real-time, the expected major breakthroughs include new software algorithms for decoupling different contributions from different metabolites on the same sensor spot as well as a new CMOS design for the fully-implanted, complex and low consumption electronics for sensing and remote powering.