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Computers in Cardiology (CinC)

作者： Andrea Pitzus Giulia Baldazzi Marco Orrú Alberto Valdes Rey Graziana Viola Luigi Raffo Petar Djuric Danilo Pani Department of Electrical and Electronic Engineering (DIEE) University of Cagliari Cagliari Italy Department of Informatics Bioengineering Robotics and Systems Engineering (DIBRIS) University of Genova Genova Italy EP STAFF Santissima Annunziata Hospital Sassari Italy Stony Brook University Stony Brook NY USA

Arrhythmogenic sites in post-ischemic ventricular tachycardia $(VT)$ are usually identified by looking for abnormal ventricular potentials $(AVPs)$ in intracardiac electrograms $(EGMs)$ . Unfortunately, the accurate recognition of AVPs is a challenging problem for different reasons, including the intrinsic variability in the A $VP$ waveform. Given the high performance of deep neural networks in several scenarios, in this work, $we$ explored the use of transfer learning $(TL)$ for AVPs detection in intracardiac electrophysiology. A balanced set of 1504 bipolar intracardiac EGMs was collected from nine post-ischemic $VT$ patients. The time-frequency representation was generated for each $EGM$ by computing the synchrosqueezed wavelet transform to be used in the re-training of the convolutional neural network. The proposed approach allows obtaining high recognition results, above 90% for all the investigated performance indexes, demonstrating the effectiveness of deep learning in the recognition of AVPs in post-ischemic $VT$ EGMs and paving the way for its use in supporting clinicians in targeting arrhythmogenic sites. In addition, this study further confirms the efficacy of the $TL$ approach even in case of limited dataset sizes.

关键词： Deep learning Wavelet transforms Time-frequency analysis Target recognition Transfer learning Neural networks Hyperparameter optimization

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FINSTIX: A Cyber-Physical Data Model for Financial Critical Infrastructures 1st

FINSTIX: A Cyber-Physical Data Model for Financial Critical ...

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1st International Workshop on Cyber-Physical Security for Critical Infrastructures Protection, CPS4CIP 2020 in conjunction with the European Symposium on Research in Computer Security, ESORICS 2020

作者： Gazzarata, Giorgia Troiano, Ernesto Verderame, Luca Aiello, Maurizio Vaccari, Ivan Cambiaso, Enrico Merlo, Alessio Department of Informatics Bioengineering Robotics and System Engineering University of Genoa Genoa Italy Consorzio Interuniversitario Nazionale per l’Informatica Catania Italy GFT Italia S.r.l. Genoa Italy Genoa Italy

ISBN: (纸本)9783030697808

Cyber-physical security of financial institutions is a critical and sensitive topic. In this context, the FINSEC project aims to design and build a reference architecture for the integrated physical and cyber security of financial institutions. To make feasible, the interactions among the different services of the FINSEC platform, a proper data model defining the exchanged information semantic is fundamental. One of the objectives of the FINSEC project is to integrate cyber and physical security measures in the financial services industry. To do so, the data model must consider both cyber and physical systems. In this paper, the authors present FINSTIX, namely the data model adopted in the FINSEC platform. In particular, they extended the Structured Threat Information eXpression (STIX) standard creating custom objects to describe the financial organization’s infrastructure and then to integrate cyber and physical security measures. The paper also reports an example of the use of FINSTIX in a relevant use case scenario. © 2021, Springer Nature Switzerland AG.

关键词： Semantics

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Finite Element Analysis of Patient-Specific Heart Model with Simulated Aortic Stenosis 23

Finite Element Analysis of Patient-Specific Heart Model with...

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23rd IEEE International Conference on Bioinformatics and bioengineering, BIBE 2023

作者： Tomasevic, Smiljana Saveljic, Igor Velicki, Lazar Exarchos, Themis Filipovic, Nenad Faculty of Engineering University of Kragujevac Kragujevac Serbia Bioengineering Research and Development Center - BioIRC Kragujevac Serbia Institute for Information Technologies Kragujevac Serbia Institute of Cardiovascular Diseases Sremska Kamenica Serbia Faculty of Medicine University of Nov Sad Novi Sad Serbia Department of Informatics Ionian University Corfu Greece Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina Greece

ISBN: (纸本)9798350393118

The main aim of this study was to evaluate the impact of simulated aortic stenosis on velocity and shear stress distribution within the patient-specific heart model by using computational Finite Element (FE) method. The three dimensional (3D) patient-specific model of heart, including surrounding arterial and vein structures, was reconstructed based on Computed Tomography (CT) scan images in order to obtain the 3D FE mesh. Computational Fluid Dynamics (CFD) analysis was performed, with applied equivalent material characteristics and boundary conditions. Using one patient-specific heart model with clinically confirmed hypertrophic cardiomyopathy, three different cases were simulated: (i) without aortic stenosis, (ii) with 30% of aortic stenosis (mild aortic stenosis), and (iii) with 70% of aortic stenosis (severe aortic stenosis. The initial results of the study (velocity and shear stress distribution) were quantified concerning anatomical patient's structures and simulating different degrees of aortic stenosis to analyse the blood flow patterns, as well as the correlation between shear stress and aortic and left ventricular remodelling. It was found that gradient of shear stress distribution increases with stenosis degree, especially in the ascending aorta which can lead to different aortopathies and endothelial diseases. Due to the difficulties in obtaining such characteristics in vitro or in vivo, the performed computational analysis gave better insight into the biomechanics of the heart and aortic stenosis that is needed to achieve improvements in surgical repair techniques and presurgical planning. © 2023 IEEE.

关键词： Finite element method

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Semantics Management for a Regional Health Information System in Italy by CTS2 and FHIR

Semantics Management for a Regional Health Information Syste...

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2021 European Federation for Medical informatics (EFMI) Special Topic Conference, STC 2021

作者： Gazzarata, Roberta Maggi, Norbert Magnoni, Luca Douglas Monteverde, Maria Eugenia Ruggiero, Carmelina Giacomini, Mauro Healthropy S.r.l. Savona Italy Department of Informatics Bioengineering Robotics and Information Systems University of Genoa via all'Opera Pia 13 Genoa16145 Italy Laboratory of Human Genetics IRCCS Giannina Gaslini Genova Italy

ISBN: (纸本)9781643682365

An infrastructure for the management of semantics is being developed to support the regional health information exchange in Veneto - an Italian region which has about 5 million inhabitants. Terminology plays a key role in the management of the information fluxes of the Veneto region, in which the management of electronic health record is given great attention. An architecture for the management of the semantics of laboratory reports has been set up, adopting standards by HL7. The system has been initially developed according to the common terminology service release 2 (CTS2) standard and, in order to overcome complexities of CTS2 is being revised according to the Fast Healthcare Interoperability Resources (FHIR) standard, which has been subsequently introduced. Aspects of CST2 and of FHIR have been considered in order to retain most suitable aspects of both. This integration can be regarded as most worthwhile. © 2021 The European Federation for Medical informatics (EFMI) and IOS Press. All rights reserved.

关键词： Terminology

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Effective Somatosensory and Cross-Modal Evaluation in Children with Hemiparesis and Neurotypically developing Children using MSI Caterpillar*

Effective Somatosensory and Cross-Modal Evaluation in Childr...

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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Maria Casado-Palacios Kristina Müller Volker Hömberg Giorgia Bertonati Claudio Campus Marco Crcpaldi Antonio Maviglia Monica Gori Unit for Visually impaired People Center for Human Technologies Istituto Italiano di Tecnologia Genova Italy Neuropediatrics St. Mauritius Therapieklinik Meerbusch Dusseldorf Germany Word Federation for Neurorehabitation European Federation of Neurorehabilitation societies Department of Informatics Bioengineering Robotics and Systems Engineering UniGe Genova Italy Electronic Design Laboratory Istituto Italiano di Tecnologia Genova Italy

ISBN: (数字)9798350307993

ISBN: (纸本)9798350308006

Motor function and tactile perception are deeply interconnected. Individuals with paresis serve as an example of this intricate interplay between motor and tactile systems, by showing that motor recovery depends on improvement in the somatosensory function. In the clinical practice, somatosensory assessment tends to be neglected, or, when conducted, faces challenges due to a lack of consistency in methodology, which might also impact the development of effective rehabilitation strategies. Somatosensory and cross-modal perception in children with hemiparesis is particularly underexplored. With this work, using a new version of the MSI Caterpillar, our goal was (1) to contribute to the understanding of somatosensory perception in children with hemiparesis, (2) investigate how cross-modal inter-actions can influence their perceptions, and (3) bridge the gap between theoretical research and practical application, offering new pathways for technological integration in clinical settings. By measuring the reaction times (RTs) in the detection of a tactile signal and the localization of tactile, audio-tactile and visual-tactile stimuli, we effectively detect somatosensory impairments in the more affected arm of children with hemiparesis compared to the non-dominant one of typically developing peers, suggest the presence of cross-modal interactions, and highlight the dominant role of vision in space location. In addition, our data revealed that attraction towards the wrist in the localization of tactile stimuli is a developmental milestone impaired in hemiparesis.

关键词： Somatosensory Wrist Location awareness Visualization Pediatrics Tactile sensors Motors

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Compact early vision signal analyzers in neuromorphic technology 15

Compact early vision signal analyzers in neuromorphic techno...

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15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020

作者： Baruzzi, Valentina Indiveri, Giacomo Sabatini, Silvio P. Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Institute of Neuroinformatics University of Zürich ETH Zürich Zürich Switzerland

ISBN: (纸本)9789897584022

Reproducing the dynamics of biological neural systems using mixed signal analog/digital neuromorphic circuits makes these systems ideal platforms to implement low-power bio-inspired devices for a wide range of application domains. Despite these principled assets, neuromorphic system design has to cope with the limited resources presently available on hardware. Here, different spiking networks were designed, tested in simulation, and implemented on the neuromorphic processor DYNAP-SE, to obtain silicon neurons that are tuned to visual stimuli oriented at specific angles and with specific spatial frequencies, provided by the event camera DVS. Recurrent clustered inhibition was successfully tested on spiking neural networks, both in simulation and on the DYNAP-SE board, to obtain neurons with highly structured Gabor-like receptive fields (RFs);these neurons are characterized by tuning curves that are sharper or at least comparable to the ones obtained using equivalent feed-forward schemes, but require a significantly lower number of synapses. The resulting harmonic signal description provided by the proposed neuromorphic circuit could be potentially used for a complete characterization of the 2D local structure of the visual signal in terms of phase relationships from all the available oriented channels. Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

关键词： Neurons

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Vibrational Stabilization of Complex Network systems

Vibrational Stabilization of Complex Network Systems

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American Control Conference (ACC)

作者： Alberto Maria Nobili Yuzhen Qin Carlo Alberto Avizzano Danielle S. Bassett Fabio Pasqualetti Department of Mechanical Engineering University of California Riverside Department of Excellence in Robotics and A.I. Scuola Superiore Sant’Anna Perceptual Robotics Laboratory at the IIM Institute Pisa Italy Department of Bioengineering the Department of Electrical & Systems Engineering the Department of Physics & Astronomy the Department of Psychiatry and the Department of Neurology University of Pennsylvania and the Santa Fe Institute Collaborative Research Network Aligning Science Across Parkinson’s (ASAP) Chevy Chase MD

Many natural and man-made network systems need to maintain certain patterns, such as working at equilibria or limit cycles, to function properly. Thus, the ability to stabilize such patterns is crucial. Most of the existing studies on stabilization assume that network systems’ states can be measured online so that feedback control strategies can be used. However, in many real-world scenarios, systems’ states, e.g., neuronal activity in the brain, are often difficult to measure. In this paper, we take this situation into account and study the stabilization problem of linear network systems with an open-loop control strategy—vibrational control. We derive a graph-theoretic sufficient condition for structural vibrational stabilizability, under which network systems can always be stabilized. We further provide an approach to select the locations in the network for control placement and design corresponding vibrational inputs to stabilize systems that satisfy this condition. Finally, we provide some numerical results that demonstrate the validity of our theoretical findings.

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Design of an experimental setup for delivering intracortical microstimulation in vivo via Spiking Neural Network

Design of an experimental setup for delivering intracortical...

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

作者： M. Di Florio M. Carè R. Beaubois V. R. Cota F. Barban T. Levi M. Chiappalone Department of Informatics Bioengineering Robotics System Engineering (DIBRIS) University of Genova Genova Italy Rehab Technologies IIT-INAIL Lab Istituto Italiano di Tecnologia Genova Italy IMS Laboratory CNRS UMR 5218 University of Bordeaux Talence France

Electroceutical approaches for the treatment of neurological disorders, such as stroke, can take advantage of neuromorphic engineering, to develop devices able to achieve a seamless interaction with the neural system. This paper illustrates the development and test of a hardware-based Spiking Neural Network (SNN) to deliver neural-like stimulation patterns in an open-loop fashion. Neurons in the SNN have been designed by following the Hodgkin-Huxley formalism, with parameters taken from neuroscientific literature. We then built the set-up to deliver the SNN-driven stimulation in vivo. We used deeply anesthetized healthy rats to test the potential effect of the SNN-driven stimulation. We analyzed the neuronal firing activity pre- and post-stimulation in both the primary somatosensory and the rostral forelimb area. Our results showed that the SNN-based neurostimulation was able increase the spontaneous level of neuronal firing at both monitored locations, as found in the literature only for closed-loop stimulation. This study represents the first step towards translating the use of neuromorphic-based devices into clinical *** Relevance— Stroke represents one of the leading causes of long-term disability and death worldwide. Intracortical microstimulation is an effective approach for restoring lost sensory motor integration by promoting plasticity among the affected brain areas. Stimulation delivered via neuromorphic-based open-loop systems (i.e. neuromorphic prostheses) can pave the way to novel electroceutical strategies for brain repair.

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In Vitro High-Throughput Toxicological Evaluation of Nanoplastics

SSRN

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SSRN 2022年

作者： Gioria, Sabrina Tolardo, Valentina Magrì, Davide Fumagalli, Francesco Cassano, Domenico Athanassiou, Athanassia Fragouli, Despina Smart Materials Istituto Italiano di Tecnologia Via Morego 30 Genova16163 Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Via All'Opera Pia 13 Genova16145 Italy Ispra Italy

Synthetic plastics were first introduced into the consumer markets in the 1950’s. Since then 8.3 billion tons have been produced, of which 6.3 billion tons are estimated to have been lost to the environment. One of the major concerns is that this plastic debris can degrade into small micro (MPs) and nano (NPs) sized fragments which may have negative consequences for humans if taken up into the body. To date, an adequate toxicological evaluation of the effect of NPs’ on humans is still lacking. In this work, we investigated in vitro the impact of three different types of NPs on two different cell models. Two types of laser-ablated NPs (polycarbonate (PC) and polyethylene terephthalate (PET1)) were studied in comparison with PET NPs (PET2) made by nanoprecipitation. All the NPs were characterized in terms of size, surface chemical composition and stability. In comparison to the particles made by nanoprecipitation, the Laser-ablated NPs were generally smaller, had broader size distributions and had a higher degree of oxidation on their surface. A toxicological evaluation was performed on HePG2 and Caco-2 cells by high throughput screening techniques. PC NPs were found to be more toxic than PET1 NPs, whereas the PET2 NPs showed no toxicity. Interestingly, on a model of the intestinal barrier none of the NPs induced any measurable toxicity. © 2022, The Authors. All rights reserved.

关键词： Polycarbonates

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Are you (Google) home? Detecting users’ presence through traffic analysis of smart speakers 4

Are you (Google) home? Detecting users’ presence through tr...

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4th Italian Conference on Cyber Security, ITASEC 2020

作者： Caputo, D. Verderame, L. Merlo, A. Ranieri, A. Caviglione, L. Computer Security Lab Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Italy Institute for Applied Mathematics and Information Technologies National Research Council of Italy Italy

Smart speakers and voice-based virtual assistants are core building blocks of modern smart homes. For instance, they are used to retrieve information, interact with other devices, and command a variety of Internet of Things (IoT) nodes. To this aim, smart speakers and voice-based assistants typically take advantage of cloud architectures: vocal commands of the user are sampled, sent through the Internet to be processed and transmitted back for local execution, e.g., to perform an automation task or activate an IoT device. Even if privacy and security is enforced by means of encryption, features of the traffic, such as the throughput, the size of protocol data units or the IP addresses, can leak important information about the habits of the users as well as the number and the type of IoT nodes deployed. In this perspective, the paper showcases risks of machine learning techniques to develop black-box models to automatically classify traffic and implement privacy leaking attacks. We prove that such traffic analysis allows to detect the presence of a person in a house equipped with a Google Home device, even if the same person does not interact with the smart device. Experimental results collected in a realistic scenario are presented and possible countermeasures are discussed. Copyright © 2020 for this paper by its authors.

关键词： Internet of things

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