Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.


On biomedical systems identification

Simple techniques of signal analysis for system identification are applied in a biomedical context with special emphasis to the nervous systems. Time variant and multivariate linear parametric approaches are shown to be useful when applied to analyze signals electro-magnetically recorded form central, as well as autonomous, nervous systems. A linear approximation of possibly stimulated interactions is provided, also capturing total and partial coherence and synchronisation When a model is identified, inverse problems can be approached, like reconstructing the neuroendocrine secretion rate from hormone blood concentrations and deriving handful linear approximations to compute the integral stimulated activity. Understanding of physiology, as well as of cardiologic, simpatho-vagal, psychiatric, neurologic and endocrinologic disorders, does already benefit from the introduced even simple linear techniques. Non linear 'neural' approaches, higher order spectral analysis, logic synthesis for rules inference and non linear modeling, seem to be needed when dealing with more complex problems, like prognosis in oncology, forecasting in agrobiotechnology and mental states recognition, toward hybrid approaches to brain-computer interfacing and neuroengineering. Piecewise linear techniques, ever since used in surgery monitoring, and successfully tested in simple problems like compartmental identification in dialysis, are keen to provide a powerful simpler surrogate to the more costful non linear approaches in complex problems, when embedded in the mixed logic and dynamic context.

Type of Seminar:
Public Seminar
Prof. Diego Liberati
CNR - Politecnico di Milano, Dpt di Elettronica e Informazione - Italy
Jul 03, 2001   17:15

(new date)ETH Zentrum, ETZ E6, Gloriastrasse 35, 8006 Zurich
Contact Person:

Dr. G. Ferrari-Trecate
No downloadable files available.
Biographical Sketch:
Diego Liberati, born in Milano in december 1958, was educated in the Milano Institute of Technology, where he received his Doctorate in Electronic Engineering, summa cum laude, in february 1983. Since 1984 he is with the Italian National Research Council, where he is currently Chief Scientist In 1988 the Italian Ministry for Scientific Research awarded him the first Research Doctorate in Biomedical Engineering Secretary of the Biomedical Engineering Society of the Italian Electrical and Electronic Engineering Association (and Milano prize laureate in 1987), he chairs the Scientific Committee for the Conferences on Information and Control Technologies in Health Systems sponsored by the Italian Control Association. Visiting scientist at Rockefeller University, New York University, University of California and International Computer Science Institute, he has directed joint projects granted by both private (e.g. Hewlett Packard on artificial neural networks in industrial processes monitoring) and public (e.g. European Union on non-linear analysis of brain plasticity) institutions. Having taught signal processing, mathematical modeling, microelectronics and lab instrumentation in european Universities, he has also mentored dozens of pupils toward and beyond their doctorate His main scientific interests in Information and Communication Technologies for life are related to measurement analysis, model identification and synthesis of emulations in natural and artificial complex systems, whose ethical aspects involving the human beings he loves to deal with.