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IEEE Annual Conference on Decision and Control

作者： Carlos Vivas Silvia Siri Antonella Ferrara Simona Sacone Giulia Cavanna Francisco R. Rubio Dept. de Ingenieria de Sistemas y Automatica Escuela Superior de Ingenieros Universidad de Sevilla Spain Dept. of Informatics Bioengineering Robotics and Systems Engineering Univ. of Genova Italy Dept. of Electrical Computer and Biomedical Engineering University of Pavia Italy

ISBN: (纸本)9781479978878

The estimation of traffic densities in portions of road links is an important open problem. This work contributes to the topic proposing a distributed switched observer design method, based on Luenberger-like and consensus ideas. To this aim, a switching mode model (SMM) is employed, representing the freeway system switching among different sets of linear difference equations. The proposed scheme allows every observer to estimate the densities of the overall system, with very limited information exchange requirements between observers. Asymptotic stability of the overall scheme is proved when the system operates under observable modes, together with L_2-gain disturbance rejection capabilities. The solution is provided in terms of a set of LMIs that use the structure of the SMM to alleviate the computational requirements. The effectiveness of the approach is shown with simulation examples.

关键词： Traffic density Freeway design approach Observers Difference equation Distribute

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Effect of interface type in the VR-based acquisition of pedestrian skills in persons with ASD

Effect of interface type in the VR-based acquisition of pede...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Mario Saiano Eleonora Garbarino Simonetta Lumachi Silvano Solari Vittorio Sanguineti the Dept of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Via all'Opera Pia 13 16145 Genoa Italy the Dept. of Primary Care ASL3 Genovese Genoa Italy the Philos Counseling Academy Genoa Italy the Dept. of Education Sciences University of Genoa Corso A. Podestá 2 Genoa Italy

ISBN: (纸本)9781424492695

Possession of 'social' skills is crucial for persons with autism spectrum disorders (ASD) to maintain a certain independence and a better quality of life, and interaction with virtual environments seems an effective learning aid. In a previous study, we reported that in adults with ASD interaction with a virtual environment (a virtual city) is beneficial to the acquisition of pedestrian skills (street crossing and street navigation). Interaction was based on a gesture-based interface (Microsoft Kinect). Here we compare the learning performance when the same virtual environment is operated by a gamepad interface. We used exactly the same training protocol and data analysis than the original study. We found that both interface types are effective in the acquisition of street crossing and city navigation skills. The gamepad interface seems easier to use (thus leading to faster interaction), but gesture-based interfaces are superior in terms of transfer of the learned skills to real road environments (as reported by parents and caregivers).

关键词： ASD learned skills pedestrian skills heart atrium septum defect Skill Learning Virtual environments Persons Health-Related Quality Of Life Pedestrians Street Road Social Skills

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Analysis of upper limb movement in Multiple Sclerosis subjects during common daily actions

Analysis of upper limb movement in Multiple Sclerosis subjec...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： L. Pellegrino G. Stranieri E. Tiragallo A. Tacchino G. Brichetto M. Coscia M. Casadio student at University of Genoa Genoa Italy researcher at Italian Multiple Sclerosis Foundation (FISM) Genoa Italy postdoctoral fellow at the Translational Neural Engineering Laboratory Center for Neuroprosthetics and Institute of Bioengineering School of Engineering Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland assistant professor at the University of Genoa Dept. Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy

ISBN: (纸本)9781424492695

The goal of this study was to investigate the movement and muscle activity of the upper limb during common activities of daily life in people with Multiple Sclerosis (PwMS) with low and mild-moderate level of upper limb impairments. We found significant changes in muscles activity in PwMS compared to healthy subjects when holding and lifting objects used in everyday life. These differences were particularly remarkable in subjects with moderate level of impairment, in which the disease affected also movement smoothness. Remarkably, the smoothness of the movement during the interaction with common objects of daily activities highly correlated with the subjects' ability measured with the Abilhand scale.

关键词： PwMS subjects' ability measured disease affected also

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A Wireless Surface Electromyogram Monitoring System Using Smartphone and Its Application to Maintain Biceps Muscle

A Wireless Surface Electromyogram Monitoring System Using Sm...

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IEEE International Conference on systems, Man and Cybernetics

作者： Edita Rosana Widasari Ryoichi Miyauchi Hiroki Tamura Koichi Tanno Graduate School Dept. of Electrical and Electronic Engineering University of Miyazaki Miyazaki Japan Interdisciplinary Graduate School Dept. of Materials and Informatics University of Miyazaki Miyazaki Japan Associate Professor Dept. of Environmental Robotics University of Miyazaki Miyazaki Japan Professor Dept. of Electrical and Systems Engineering University of Miyazaki Miyazaki Japan

ISBN: (纸本)9781479986989

Recently, there are few monitoring systems using wireless technology for surface electromyogram (sEMG). Muscle fatigue detection is one of the important applications of sEMG monitoring during exercise in maintaining muscle. In this paper, a wireless sEMG system for monitoring and guiding people to maintain biceps muscle based on muscle fatigue is proposed. The android smartphone can record and send the sEMG signal to the Personal Computer (PC) using wireless technology via Hypertext Transfer Protocol (HTTP). Furthermore, a Hypertext Preprocessor (PHP) will invoke Mat Lab as PC's application. The sEMG signal is computed by Mat Lab to calculate and analyze muscle fatigue then send the result back to android smartphone to be displayed. In addition, the system can help to maintain biceps muscle until exercise complete. Detailed information about the design and implementation result is reported in this paper. The testing and implementation results have proven that the system is correct and feasible.

关键词： Muscles Fatigue Androids Humanoid robots MATLAB Monitoring Servers

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A combined geometrical and topological simplification hierarchy for terrain analysis 14

A combined geometrical and topological simplification hierar...

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22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information systems, ACM SIGSPATIAL GIS 2014

作者： Iuricich, Federico De Floriani, Leila Department of Computer Science and UMIACS University of Maryland College ParkMD United States Dept. of Computer Science Bioengineering Robotics and Systems Engineering University of Genova Italy

ISBN: (纸本)9781450331319

We consider the problem of modeling a terrain from both a geo-metric and a morphological point of view for efficient and effective terrain analysis on large data sets. We devise and implement a sim-plification hierarchy for a triangulated terrain, where the terrain is represented as a triangle mesh and its morphology is described by a discrete Morse gradient field defined on the basis on the eleva-tion values given at the vertices of the mesh. The discrete Morse gradient is attached to the triangles, edges and vertices of the mesh. We define a new edge-contraction operator for the edges of the tri-angle mesh, which does not change the behavior of the gradient flow and does not create new critical points, and we apply it to the original full-resolution mesh in combination with a topological sim-plification operator which eliminates critical simplices in pair. We build the simplification hierarchy based on suitably combining such operators and we evaluate it experimentally. © Copyright 2014 ACM.

关键词： Topology

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Testing proprioception in intrinsic and extrinsic coordinate systems: is there a difference?

Testing proprioception in intrinsic and extrinsic coordinate...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Riccardo Iandolo Valentina Squeri Dalia De Santis Psiche Giannoni Pietro Morasso Maura Casadio University of Genoa Italian Institute of Technology Dept. of Robotics ART Education and Rehabilitation Center University of Genoa Dept. Informatics Bioengineering Robotics and Systems Engineering University of Genoa

ISBN: (纸本)9781424479276

An intact position sense is considered important for neuromotor recovery, but the available methods and protocols for its assessment are still limited. In the clinical practice it is generally tested trough a bimanual position matching test, that consists of replicating with one arm the angular positions of the other arm in space (intrinsic coordinates matching). However, the same test could be carried out by matching the hand location in space (extrinsic coordinates matching). Is there any difference between the procedures that may be relevant to the evaluation of position sense deficits? In this study we compared the performance of eight right handed subjects and two stroke survivors with left hemiparesis performing the test in the two conditions. A robotic manipulandum passively moved the left arm of the participants in twenty-four positions in the workspace. Subjects had to match the left arm position with their right arm either in intrinsic or extrinsic coordinates. The results show that all the subjects (impaired and controls) performed better when using the extrinsic paradigm.

关键词： Robot kinematics Protocols Mirrors Robot sensing systems Educational institutions Electronic mail

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Quantifying performance and variability in reward-based motor skill learning

Quantifying performance and variability in reward-based moto...

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5th International Symposium on Measurement, Analysis and Modelling of Human Functions, ISHF 2013

作者： Tamagnone, Irene Casadio, Maura Sanguineti, Vittorio Dept. Informatics Bioengineering Robotics and Systems Engineering University of Genoa Italy

ISBN: (纸本)9781632660251

This study investigates motor skill learning in a specific situation in which the only information provided on performance consists of a reward signal. Subjects performed a point-to-point movement. After the end of the movement we displayed a score based on the distance from a hidden via-point - the maximum score corresponds to the via-point belonging to the trajectory path. The score was the sole information available on task performance and subjects got no additional clues of how to make it high. The task is highly redundant, as infinite trajectories are compatible with the maximum score. We specifically looked at how subjects explore the task space and how they exploit task redundancy to maximize their performance. We also compared the experimental data with the solution predicted by an optimal feedback control model. The main findings were that (i) movement outcomes are largely determined by the subject-specific history of exploration;(ii) during learning, path variability gradually decreased;(iii) for the majority of subjects the point of minimum variability gradually gets closer to the point at minimum distance from the hidden via-point;and (iv) overall, subjects don't converge to the 'optimal control' solution.

关键词： Redundancy

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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