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

作者： C. Zinno F. Agnesi F. Bernini K. Gabisonia D. Terlizzi F. A. Recchia V. Lionetti S. Micera Department of Excellence in Robotics & AI The BioRobotics Institute Scuola Superiore Sant’Anna Pisa Italy BioMedLab Scuola Superiore Sant’Anna Pisa Italy Fondazione Toscana G. Monasterio Pisa Italy Scuola Superiore Sant'Anna Pisa Italy National Research Council Pisa Italy Cardiovascular Research Center Lewis Katz School of Medicine at Temple University Philadelphia PA United States of America Unit of Translational Critical Care Medicine Laboratory of Basic and Applied Medical Sciences Interdisciplinary Research Center "Health Science" and BioMedLab Scuola Superiore Sant'Anna Pisa Italy Bertarelli Foundation Chair in Translational NeuroEngineering Centre for Neuroprosthetics and Institute of Bioengineering École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

Vagus nerve stimulation (VNS) is an FDA-approved technique for the neuromodulation of the autonomic nervous system. There are many therapeutic applications where VNS could be used as a therapy, such as cardiovascular diseases, epilepsy, depression, and inflammatory conditions. Cardiovascular applications are particularly relevant, since cardiovascular diseases are the top causes of death worldwide. VNS clinical trials have been performed in the last 15 years for the treatment of heart failure (HF), achieving controversial results. Typically VNS is applied with a cuff electrode placed around the nerve, in an open-loop or cardiac synchronized design. The effectiveness of this approach is hindered by the multifunctional nature of the VN, which is involved in a variety of homeostatic controls. When a high current is applied, adverse effects arise from the stimulation of undesired fibers. An alternative strategy is represented by intraneural stimulation, which can guarantee higher selectivity. Moreover, closed-loop modalities allow the delivery of electrical current inside the nerves only if needed, with a reduced risk of untargeted nerve activation and lower energy consumption. Here we propose a closed-loop intraneural stimulation of the right cervical VN in a clinically relevant animal model. The intraneural was designed according to the internal structure of the VN. A threshold-based closed-loop algorithm was developed using HR as a control variable to produce a chronotropic *** Relevance—This work analyzes the closed-loop intraneural VNS for the treatment of cardiovascular disorders, and supports the possibility of developing fully implantable devices with a high degree of selectivity in stimulation and prolonged lifespan.

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Brain Stimulation 2025年第1期18卷 273-273页

作者： Falciglia, Salvatore Caffi, Laura Habib, Rita Hanafi, Ibrahem Pozzi, Nicolò Marceglia, Sara Arlotti, Mattia Rossi, Lorenzo Mazzoni, Alberto Isaias, Ioannis Palmisano, Chiara The BioRobotics Institute Sant’Anna School of Advanced Studies Pisa Italy Parkinson Institute of Milan ASST G.Pini-CTO Milano Italy Department of Neurology University Hospital of Würzburg and Julius Maximilian University of Würzburg Würzburg Germany Department of Engineering and Architecture University of Trieste Trieste Italy Newronika S.p.A. Milano Italy Department of Excellence in Robotics and AI Sant’Anna School of Advanced Studies Pisa Italy

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A store-and-forward cloud-based telemonitoring system for automatic assessing dysarthria evolution in neurological diseases from video-recording analysis

arXiv

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arXiv 2023年

作者： Migliorelli, Lucia Berardini, Daniele Cela, Kevin Coccia, Michela Villani, Laura Frontoni, Emanuele Moccia, Sara Department of Information Engineering Univeristà Politecnica Delle Marche Via Brecce Bianche 12 Ancona60121 Italy AIDAPT S.r.l Via Brecce Bianche 12 Ancona60121 Italy Fondazione Serena Onlus Via Conca 71 Torrette Ancona60126 Italy Department of Neuroscience Neurorehabilitation Clinic Azienda Ospedaliero-Universitaria delle Marche Via Conca 71 Torrette Ancona60126 Italy Department of Political Sciences Communication and International Relations Università Degli Studi di Macerata Via Giovanni Mario Crescimbeni 30 Macerata62100 Italy The BioRobotics Institute Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Piazza Martiri della Libertà 33 Pisa56127 Italy NeMO Lab Piazza dell’Ospedale Maggiore Milano20162 Italy

Background and objectives: Patients suffering from neurological diseases may develop dysarthria, a motor speech disorder affecting the execution of speech. Close and quantitative monitoring of dysarthria evolution is crucial for enabling clinicians to promptly implement patients’ management strategies and maximizing effectiveness and efficiency of communication functions in term of restoring, compensating or adjusting. In the clinical assessment of orofacial structures and functions, at rest condition or during speech and non-speech movements, a qualitative evaluation is usually performed, throughout visual observation. Methods: To overcome limitations posed by qualitative assessments, this work presents a store-and-forward self-service telemonitoring system that integrates, within its cloud architecture, a convolutional neural network (CNN) for analyzing video recordings acquired by individuals with dysarthria. This architecture – called facial landmark Mask RCNN – aims at locating facial landmarks as a prior for assessing the orofacial functions related to speech and examining dysarthria evolution in neurological diseases. Results: When tested on the Toronto NeuroFace dataset, a publicly available annotated dataset of video recordings from patients with amyotrophic lateral sclerosis (ALS) and stroke, the proposed CNN achieved a normalized mean error equal to 1.79 on localizing the facial landmarks. We also tested our system in a real-life scenario on 11 bulbar-onset ALS subjects, obtaining promising outcomes in terms of facial landmark position estimation. Discussion and conclusions: This preliminary study represents a relevant step towards the use of remote tools to support clinicians in monitoring the evolution of dysarthria. © 2023, CC BY.

关键词： Network architecture

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Automated detection of larval stages of the Black Soldier Fly ( Hermetia illucens Linnaeus) through deep learning augmented with optical flow

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Information Processing in Agriculture 2025年

作者： Gianluca Manduca Lloyd T. Wilson Cesare Stefanini Donato Romano The BioRobotics Institute Sant’Anna School of Advanced Studies Viale R. Piaggio 34 56025 Pontedera Pisa Italy Department of Excellence in Robotics and AI Sant’Anna School of Advanced Studies Piazza Martiri della Libertà 33 56127 Pisa Italy Texas A&M University and Texas A&M AgriLife Research 1509 Aggie Drive Beaumont TX USA

The Black Soldier Fly (BSF) Hermetia illucens has garnered significant attention for its potential in sustainable waste management, nutrient recycling, and the production of valuable resources such as protein-rich animal feed and biofuels. Traditional mass production methods remain labor-intensive and error-prone, necessitating automated solutions. A critical challenge is the precise identification of BSF different life stages which is essential for optimizing feeding strategies, harvesting, and overall system efficiency. This study explores the use of deep learning, combined with optical flow analysis, to identify BSF life stages, particularly larvae, prepupae, and pupae. A Convolutional Neural Network (CNN) model was employed for real-time BSF larval stages detection. Training, validation, and test were performed on a comprehensive custom dataset of 2130 images. Evaluation metrics including precision, recall, and mean Average Precision (mAP) were assessed. Overall, the CNN model demonstrated a precision of 0.96, a recall of 0.95, and a [email protected] of 0.97 on the test set, confirming its generalization capability and effectiveness in real-world scenarios. The integration of optical flow enhanced the model’s performance by leveraging prior knowledge of motor activity, particularly for identifying and correcting false positives in pupae classification. Automated identification of BSF larval stages optimizes resource management, reduces operational costs, and enhances the economic viability of BSF-based systems. The proposed system extends beyond terrestrial concerns, with potential implications for bioregenerative life-support systems, particularly in space technology.

关键词： Precision techniques Automated systems Computer vision Machine learning Sustainability Insect-based technologies

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Letter to the Editor: The concept of Hepatic Steatosis assessment in Liver Donors

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Journal of Liver Transplantation 2022年 8卷 100104-100104页

作者： Cesaretti, Manuela Moccia, Sara HPB and Liver Transplantation Department. ARNAS Brotzu Cagliari 09122 Italy Istituto Italiano di Tecnologia Genova 16163 Italy The BioRobotics Institute and the Department of Excellence in Robotics and AI. Scuola Superiore Sant'Anna Pisa 56127 Italy

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A deep learning approach to predict myocardial fibrosis in early contrast-enhanced CCT images

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European Heart Journal - Cardiovascular Imaging 2023年第SUPPLEMENT_1期24卷

作者： Penso, M Carerj, M L Moccia, S Babbaro, M Baggiano, A Guglielmo, M Fusini, L Mushtaq, S Andreini, A Pepi, M Caiani, E Pontone, G Centro Cardiologico Monzino IRCSS Department of Perioperative Cardiology and Cardiovascular Imaging Milan Italy Sant'Anna School of Advanced Studies The BioRobotics Institute and Department of Excellence in Robotics and AI Pisa Italy IRCCS Policlinico San Donato Department of Cardiology milano Italy Utrecht University Utrecht University Medical Center Department of Cardiology Division of Heart and Lungs Utrecht Netherlands (The) Istituto Auxologico Italiano IRCCS milano Italy

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Multidimensional evaluation of telepresence robot: results from a field trial*

Multidimensional evaluation of telepresence robot: results f...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： L. Fiorini G. Mancioppi C. Becchimanzi A. Sorrentino M. Pistolesi F. Tosi F. Cavallo BioRobotics Instutute of Scuola Superiore Sant’Anna Pontedera (Pisa) Italy Department of Excellence in Robotics & AI Piazza Martiri della Libertà Pisa Italy Department of Architecture University of Florence Florence Italy Department of Industrial Engineering University of Florence Florence Italy

ISBN: (数字)9781728160757

ISBN: (纸本)9781728160764

The European population is getting older; many elderlies would like to live independently in their homes as long as possible. In this context, a robotic telepresence service could support the frail persons in their homes, empowering their social relationships. In this work, 10 frail elderly were asked to live with a telepresence robot (i.e. Double Robot), through which the formal caregiver could remotely visit and chat with them. A total of 169 days of field-test trial was evaluated before (TO) and after (TF) the tests with a multidimensional framework, including acceptance, usability, and expectation domains. The system was used for 2871 mins, and the results underline good usability- and acceptance- related domains (average score equals to 70.83 at TF) and expectation (average score equal to 67.01 at TF). Results remark that expectation could influence the potential and the real use of the robot. Additionally, a positive trend in the answers was identified between T0 and TF. Indeed, the evaluation of a system should envisage a complex, multidisciplinary and holistic approach, that may influence the success or failure of the robot's purpose, if not properly analysed during the evaluation and design phase.

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Publisher's Note: “Contrast-enhanced ultrasound tracking of helical propellers with acoustic phase analysis and comparison with color Doppler” [APL Bioeng. 6, 036102 (2022)]

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APL Bioengineering 2022年第3期6卷

作者： S. Pane M. Zhang V. Iacovacci L. Zhang A. Menciassi 1The BioRobotics Institute Scuola Superiore Sant'Anna Pisa Italy 2Department of Excellence in Robotics & AI Scuola Superiore Sant'Anna Pisa Italy 3Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong SAR China

This article was originally published online on 2 August 2022 with errors in the reference numbering through the text.

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Unveiling host-seeking behaviour in entomopathogenic nematodes via lab-on-a-chip technology

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Biosystems Engineering 2025年 255卷

作者： Manduca, Gianluca Zeni, Valeria Casadei, Anita Tarasco, Eustachio Lucchi, Andrea Benelli, Giovanni Stefanini, Cesare Romano, Donato The BioRobotics Institute Sant'Anna School of Advanced Studies Viale R. Piaggio 34 Pontedera Pisa56025 Italy Department of Excellence in Robotics and AI Sant'Anna School of Advanced Studies Piazza Martiri della Libertà 33 Pisa56127 Italy Department of Agriculture Food and Environment University of Pisa Via del Borghetto 80 Pisa856124 Italy Department of Soil Plant and Food Sciences University of Bari Aldo Moro Via Amendola 165/A Bari70126 Italy

Entomopathogenic nematodes (EPNs) can be employed as biological control agents (BCAs) for many insect pests’ sustainable management. Despite their widespread use, our understanding of EPNs biology, particularly interactions with their hosts, remains limited. Advancing knowledge of EPNs ecology and host interactions is crucial for optimising their efficacy in pest management. This study pioneers an interdisciplinary approach, at the interface of engineering and applied entomology, to investigate the behaviour of the EPN Steinernema carpocapsae. A novel method combining microfluidics, machine learning, and optical flow is presented. A lab-on-a-chip platform was designed to enable accurate investigation of EPN response to stimuli. A convolutional neural network (CNN) identified nematodes and distinguished their responses to host-derived cues achieving 0.94 accuracy and 1.00 precision in detecting stimulus presence at video-level, classifying EPN behaviour within a controlled environment that simulates host conditions. Optical flow analysis revealed differences in motor activity of EPN upon exposure to stimuli, providing new insights into their dynamic responses. Steinernema carpocapsae exhibited more intense activity in presence of host-borne cues (p = 0.0055). Support vector machine (SVM) and multilayer perceptron (MLP) classifiers distinguished stimulus contexts from optical flow features, with an area under the receiver operating characteristic (ROC) curve of 0.71. These results highlight that, although S. carpocapsae is typically considered an ambusher, it may actively engage in host-seeking behaviour, suggesting a shift in our understanding of its search strategies. This methodology significantly enhances the detection and understanding of EPN responses to cues, advancing their potential in precision biocontrol programs for sustainable pest management actions. Science4Impact statement (S4IS): This study develops a novel lab-on-a-chip platform integrating artificia

关键词： Mosquito control

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Enhancing human bodies with extra robotic arms and fingers: The Neural Resource Allocation Problem

arXiv

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arXiv 2021年

作者： Dominijanni, Giulia Shokur, Solaiman Salvietti, Gionata Buehler, Sarah Palmerini, Erica Rossi, Simone de Vignemont, Frederique D’Avella, Andrea Makin, Tamar R. Prattichizzo, Domenico Micera, Silvestro Lausanne Switzerland Institute of BioRobotics Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Pisa Italy Department of Information Engineering and Mathematics University of Siena Siena Italy Department of Advanced Robotics Istituto Italiano di Tecnologia Genoa Italy Institute of Cognitive Neuroscience University College London United Kingdom Dirpolis Institute Scuola Superiore Sant’Anna Pisa Italy Department of Medicine Surgery and Neuroscience Unit of Neurology and Clinical Neurophysiology University of Siena Italy Institut Jean Nicod CNRS-ENS-EHESS PSL University France Department of Biomedical and Dental Sciences and Morphofunctional Imaging University of Messina Italy Laboratory of Neuromotor Physiology IRCCS Fondazione Santa Lucia Rome Italy

The emergence of robot-based body augmentation promises exciting innovations that will inform robotics, human-machine interaction, and wearable electronics. Even though augmentative devices like extra robotic arms and fingers in many ways build on restorative technologies, they introduce unique challenges for bidirectional human-machine collaboration. Can humans adapt and learn to operate a new limb collaboratively with their biological limbs without sacrificing their physical abilities? To successfully achieve robotic body augmentation, we need to ensure that by giving a person an additional (artificial) limb, we are not in fact trading off an existing (biological) one. In this manuscript, we introduce the "Neural Resource Allocation" problem, which distinguishes body augmentation from existing robotics paradigms such as teleoperation and prosthetics. We discuss how to allow the effective and effortless voluntary control of augmentative devices without compromising the voluntary control of the biological body. In reviewing the relevant literature on extra robotic fingers and limbs we critically assess the range of potential solutions available for the "Neural Resource Allocation" problem. For this purpose, we combine multiple perspectives from engineering and neuroscience with considerations from human-machine interaction, sensory-motor integration, ethics and law. Altogether we aim to define common foundations and operating principles for the successful implementation of motor augmentation. © 2021, CC BY.

关键词： Robotic arms

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