Publications

by Keyword: Robustness


By year:[ 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 ]

Amil, A. F., Maffei, G., Puigbò, J. Y., Arsiwalla, X. D., Verschure, P., (2019). Robust postural stabilization with a biomimetic hierarchical control architecture Biomimetic and Biohybrid Systems 8th International Conference, Living Machines 2019 (Lecture Notes in Computer Science) , Springer, Cham (Nara, Japan) 11556, 321-324

Fast online corrections during anticipatory movements are a signature of robustness in biological motor control. In this regard, a previous study suggested that anticipatory postural control can be recast as a sensory-sensory predictive process, where hierarchically connected cerebellar microcircuits reflect the causal sequence of events preceding a postural disturbance. Hence, error monitoring signals from higher sensory layers inform lower layers about violations of expectations, affording fast corrections when the normal sequence is broken. Here we generalize this insight and prove that the proposed hierarchical control architecture can deal with different types of alterations in the causal structure of the environment, therefore extending the limits of performance.

Keywords: Anticipatory control, Cerebellum, Control architecture, Robustness


Marco, Santiago, (2014). The need for external validation in machine olfaction: emphasis on health-related applications Analytical and Bioanalytical Chemistry Springer Berlin Heidelberg 406, (16), 3941-3956

Over the last two decades, electronic nose research has produced thousands of research works. Many of them were describing the ability of the e-nose technology to solve diverse applications in domains ranging from food technology to safety, security, or health. It is, in fact, in the biomedical field where e-nose technology is finding a research niche in the last years. Although few success stories exist, most described applications never found the road to industrial or clinical exploitation. Most described methodologies were not reliable and were plagued by numerous problems that prevented practical application beyond the lab. This work emphasizes the need of external validation in machine olfaction. I describe some statistical and methodological pitfalls of the e-nose practice and I give some best practice recommendations for researchers in the field.

Keywords: Chemical sensor arrays, Pattern recognition, Chemometrics, Electronic noses, Robustness, Signal and data processing