![]() His main research interests include biomedical signal processing, nonlinear analysis, and machine learning. Before that, he held a Postdoctoral position at Massachusetts General Hospital and Harvard University, Boston, MA, USA until 2020. He is currently a Research Fellow in biomedical signal processing and machine learning at The Centre for Addiction and Mental Health, Toronto University, Toronto, ON, CA. degree in biomedical signal processing from the Institute for Digital Communication, University of Edinburgh, U.K., in 2018. Within these fields, he co-authored eight book chapters and more than ~250 peer-reviewed publications, receiving more than 6000 citations (h-index: 46 font: Scholar). His research focuses on multivariate time series analysis and information theory applied to cardiovascular neuroscience, brain connectivity, brain-heart interactions, and network physiology. He is Specialty Chief Editor for Frontiers in Network Physiology, and Associate Editor for IEEE Transactions on Biomedical Engineering and Entropy. Faes is Senior Member of the IEEE, member of the IEEE Engineering in Medicine and Biology Society (IEEE-EMBS) and of the Technical Committee of Biomedical Signal Processing, and member of the European Study Group on Cardiovascular Oscillations (ESGCO). He has previously been with the Department of Physics of the University of Trento, Italy, and visiting scientist at the State University of New York, Worcester Polytechnic Institute, University of Gent, University of Minas Gerais, and Boston University. Luca Faes is Professor of Biomedical Engineering at the University of Palermo, Italy, where he teaches courses on Statistical Analysis of Biomedical Signals, Biosensors and Biomedical Devices. She has been guest editor for special issues in journals as Entropy, Complexity, and Computational and Mathematical Methods in Medicine. She is also member of the IEEE-EMBS Technical Community on Cardiopulmonary Systems and Physiology-based Engineering. She is member of the editorial board for the journal Entropy and area editor on Signal Processing for the IEEE Open Journal of Engineering in Medicine and Biology. She is associate editor for IEEE Transactions on Biomedical Circuits and Systems, for Frontiers in Network Physiology - Information Theory, Causality & Control, and for the Engineering Medicine and Biological Society Conference. Her main applications are related to the biomedical field. Her research interests include signal and image processing, mainly multiscale and entropy-based analyses, and data-driven methods. She is currently a full professor in Engineering with the University of Angers, France. Time: 6:30 pm CET | 12:30 pm EST | 1:30 am CST Asia (10 March 2023)Īnne Humeau-Heurtier received the PhD degree in Biomedical Engineering in France. Moreover, the very recent applications of entropy measures to graphs will be developed. Furthermore, an extension to multidimensional and multivariate data will be discussed. The theoretical backgrounds of entropy measures will be presented and the most recent algorithms to quantify the irregularity and complexity of time series will be developed. In this webinar, we will talk with three of the leading experts in entropy measures to hear their perspectives on the recent advances, and challenges of entropy measures. Moreover, the analysis of entropy measures over several temporal or spatial scales are now commonly used to quantify the complexity of systems. Extensions of these nonlinear measures to multidimensional and/or multivariate data have also led to many papers from several areas. $$Ĭonclusion: Now we get the expected result.2 nd Entropy Webinar Entropy Measures to Assess Irregularity and Complexity of Time Series and Multidimensional DataĮntropy-based metrics issued from information theory have found an increasing interest in the dynamical analysis of different kinds of systems. As shown at How does entropy depend on location and scale?, the integral is easily reduced (via an appropriate change of variable) to the case $\gamma=1$, for which
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |