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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Riccardo Bezzini Carlo Alberto Avizzano Francesco Porcini Alessandro Filippeschi The Department of Excellence in Robotics and AI Institute of Mechanical Intelligence Scuola Superiore Sant’Anna Pisa Italy

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Lower Limb Exoskeletons (LLEs) are wearable robotic systems that provide mechanical power to the user. Human-exoskeleton (HE) connections must guarantee the subsistence of the user’s natural behavior during the interaction, avoiding the exertion of undesired forces, i.e., the robot must be transparent. Since transparency is an essential feature of exoskeletons’ design, numerous works focus on its maximization, e.g., employing passive joints at the HE interfaces. Given the inherent complications of repeatedly prototyping and experimentally testing a device, modeling the exoskeleton and its physical interaction with the user emerges as an extremely valuable approach for assessing the design effects. This paper proposes a novel method to compare different exoskeleton configurations with a flexible simulation tool. This approach contemplates simulating the dynamics of the device, including its interaction with the wearer, to evaluate multiple connection mechanism designs along with the kinematics and actuation of the LLE. This evaluation is based on the minimization of the interaction wrenches through an optimization process that includes the impedance parameters at the interfaces as optimization variables and the similarity of the LLE’s joint variables trajectories with the motion of the wearer’s articulations. Exploratory tests are conducted using the Wearable Walker LLE in different configurations and measuring the interaction forces. Experimental data are then compared to the optimization outcomes, proving that the proposed method provides contact wrench estimations consistent with the collected measurements and previous outcomes from the literature.

关键词： Limbs Exoskeletons Mechanism design Kinematics Motors Minimization Robustness Trajectory Optimization Testing

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Integrating Microfluidics and Deep Learning to Investigate Entomopathogenic Nematode Responses to Host Cues

Integrating Microfluidics and Deep Learning to Investigate E...

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

作者： Gianluca Manduca Valeria Zeni Anita Casadei Giovanni Benelli Cesare Stefanini Donato Romano The BioRobotics Institute Sant’Anna School of Advanced Studies Pisa Italy Department of Excellence in Robotics and AI Sant’Anna School of Advanced Studies Pisa Italy Department of Agriculture Food and Environment University of Pisa Pisa Italy

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Entomopathogenic nematodes (EPNs) are effective biocontrol agents, reducing pesticide impact on health and the environment. Understanding their physiology and ethology is crucial for optimizing their application. This study offers innovative insights about Steinernema carpocapsae EPN behavior, contributing to the interdisciplinary field of engineering, biology, and entomology. The proposed hybrid approach combines microfluidics, deep learning, and optical flow. A Convolutional Neural Network (CNN) model discerned EPNs in the presence of stimuli within a specially designed microfluidic arena, highlighting motor behavior differences. At the video level, the CNN model accurately discriminated a context characterized by host-borne cues, achieving an overall accuracy of 0.938, precision of 1, and f1-score of 0.933. Integrating optical flow analysis unveiled a significant difference in motor activity, adding novel information on their dynamic responses. EPNs showed an increased activity in stimulus presence. This comprehensive approach advances our capability to detect and comprehend the responses of EPN to host stimuli for more precise and targeted biocontrol strategies.

关键词： Deep learning Biological system modeling Entomology Pesticides Motors Physiology Convolutional neural networks Biological control systems Microfluidics Optical flow

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Underactuated Robotic Fish Control: Maneuverability and Adaptability Through Proprioceptive Feedback 12th

Underactuated Robotic Fish Control: Maneuverability and Ada...

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Proceedings of the 12th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2023

作者： Manduca, Gianluca Santaera, Gaspare Dario, Paolo Stefanini, Cesare Romano, Donato The BioRobotics Institute Scuola Superiore Sant’Anna Viale R. Piaggio 34 PI Pontedera56025 Italy Department of Excellence in Robotics & A.I. Scuola Superiore Sant’Anna Piazza Martiri della Libertà 33 Pisa56127 Italy

ISBN: (纸本)9783031388569

Bioinspired robotics is a promising technology for minimizing environmental disruption during underwater inspection, exploration, and monitoring. In this research, we propose a control strategy for an underactuated robotic fish that mimics the oscillatory movement of a real fish’s tail using only one DC motor. Our control strategy is bioinspired to Central Pattern Generators (CPGs) and integrates proprioceptive sensory feedback. Specifically, we introduced the angular position of the tail as an input control variable to integrate a feedback into CPG circuits. This makes the controller adaptive to changes in the tail structure, weight, or the environment in which the robotic fish swims, allowing it to change its swimming speed and steering performance. Our robotic fish can swim at a speed between 0.18 and 0.26 body lengths per second (BL/s), with a tail beating frequency between 1.7 and 2.3 Hz. It can also vary its steering angular speed in the range of 0.08 rad/s, with a relative change in the curvature radius of 0.25 m. With modifications to the modular design, we can further improve the speed and steering performance while maintaining the developed control strategy. This research highlights the potential of bioinspired robotics to address pressing environmental challenges while improving solutions efficiency, reliability and reducing development costs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Feedback

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Sensorimotor Control Strategies for Tactile robotics

arXiv

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arXiv 2025年

作者： Donato, Enrico Preti, Matteo Lo Beccai, Lucia Falotico, Egidio The BioRobotics Institute Sant’Anna School of Advanced Studies Pontedera56025 Italy Department of Excellence in Robotics and AI Sant’Anna School of Advanced Studies Pisa56125 Italy Advanced Robotics Centre National University of Singapore Singapore117575 Singapore Italian Institute of Technology Genova16163 Italy

How are robots becoming smarter at interacting with their surroundings? Recent advances have reshaped how robots use tactile sensing to perceive and engage with the world. Tactile sensing is a game-changer, allowing robots to embed sensorimotor control strategies to interact with complex environments and skillfully handle heterogeneous objects. Such control frameworks plan contact-driven motions while staying responsive to sudden changes. We review the latest methods for building perception and control systems in tactile robotics while offering practical guidelines for their design and implementation. We also address key challenges to shape the future of intelligent robots. © 2025, CC BY-NC-SA.

关键词： Intelligent robots

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Transparency evaluation for the Kinematic Design of the Harnesses through Human-Exoskeleton Interaction Modeling

arXiv

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arXiv 2024年

作者： Bezzini, Riccardo Avizzano, Carlo Alberto Porcini, Francesco Filippeschi, Alessandro The Institute of Mechanical Intelligence The Department of Excellence in Robotics and AI Scuola Superiore Sant'Anna Pisa56127 Italy

Lower Limb Exoskeletons (LLEs) are wearable robotic systems that provide mechanical power to the user. Human-exoskeleton (HE) connections must guarantee the subsistence of the user's natural behavior during the interaction, avoiding the exertion of undesired forces, i.e., the robot must be transparent. Since transparency is an essential feature of exoskeletons' design, numerous works focus on its maximization, e.g., employing passive joints at the HE interfaces. Given the inherent complications of repeatedly prototyping and experimentally testing a device, modeling the exoskeleton and its physical interaction with the user emerges as an extremely valuable approach for assessing the design effects. This paper proposes a novel method to compare different exoskeleton configurations with a flexible simulation tool. This approach contemplates simulating the dynamics of the device, including its interaction with the wearer, to evaluate multiple connection mechanism designs along with the kinematics and actuation of the LLE. This evaluation is based on the minimization of the interaction wrenches through an optimization process that includes the impedance parameters at the interfaces as optimization variables and the similarity of the LLE's joint variables trajectories with the motion of the wearer's articulations. Exploratory tests are conducted using the Wearable Walker LLE in different configurations and measuring the interaction forces. Experimental data are then compared to the optimization outcomes, proving that the proposed method provides contact wrench estimations consistent with the collected measurements and previous outcomes from the literature. Copyright © 2024, The Authors. All rights reserved.

关键词： Exoskeleton (robotics)

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A Hand-Wrist Control Strategy Based on Human Upper Limb Kinematics

A Hand-Wrist Control Strategy Based on Human Upper Limb Kine...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： E. Stefanelli M. Lapresa F. Cordella D. D'Accolti C. Cipriani L. Zollo Unit of Advanced Robotics and Human-Centred Technologies Università Campus Bio-Medico di Roma Rome Italy BioRobotics Institute Of the Scuola Superiore Sant'Anna Pisa Italy Department of Excellence in Robotics AI Scuola Superiore Sant'Anna Pisa Italy

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

The human wrist has a fundamental role in grasping tasks since it accurately controls the hand posture. The current commercial prosthetic systems lack several functionalities proper of the human wrist which could increase task success, especially for the most complex ones, and could reduce cognitive effort thanks to the detection of slip events. The analysis of the human wrist-hand kinematics and dynamics could be a starting point for reaching such goals. In particular, by studying the correlations between grip forces and wrist rotation speed, an innovative hand-wrist control strategy was developed aimed at improving the performance of the prosthetic system in grasping and manipulation tasks during Activities of Daily Living (ADLs). Preliminary early stages tests in a simulation environment were performed to evaluate the control strategy performance in two different ADL tasks, i.e. object picking and placing and pouring water, in three different conditions: I) stable grasp; ii) slip event; iii) tangential force variation. Two control parameters were considered to compare the simulated system with the real one. The results demonstrated the prosthetic hand-wrist system can reproduce the expected behaviour.

关键词： Wrist Correlation Force Dynamics Thumb Kinematics Grasping Usability Robots Prosthetics

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Development of a 3D Printing Strategy for Completely Polymeric Neural Interfaces Fabrication

Development of a 3D Printing Strategy for Completely Polymer...

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International IEEE/EMBS Conference on Neural Engineering, CNE

作者： Ciro Zinno Ilaria Cedrola Alice Giannotti Eugenio Redolfi Riva Silvestro Micera Department of Excellence in Robotics &AI Scuola Superiore Sant’ Anna The BioRobotics Institute Pisa Italy Ecole Polytechnique Federale de Lausanne Translational Neural Engineering Lab Lausanne Switzerland

The fabrication of neural interfaces (NIs) typically relies nowadays on the implementation of complex, expensive, and time-consuming photolithographic processes. Metals and polymers are the materials currently used to fabricate NIs. Conductive polymers could be an alternative to metals to enhance the biocompatibility of the devices. Additive manufacturing techniques provide an easier and low-cost approach to process and finely tuning the geometrical and morphological features of polymers. Here, we propose a 3D printing strategy for the fabrication of completely polymeric neural interfaces, based on extrusion printing. The materials have been chosen to enhance the biocompatibility of the devices. PDMS has been chosen as insulating substrate, while a PEDOT:PSS-based ink has been selected for the conductive component. Morphological, mechanical, and rheological analyses on the inks have been carried out and a first prototype of a neural interface has been fabricated. The PDMS has a Young Modulus of 600 kPa, in the same order of magnitude as peripheral nerves, with a thickness of 160 μm. The PEDOT:PSS inks fabricated present a shear thinning behavior, ideal for an extrusion printing process This approach could represent a valuable alternative to photolithography and an innovative method for the fabrication of NIs, due to the high degree of customization, ease of implementation, low-cost and flexibility in materials choice.

关键词： Fabrication Young's modulus Prototypes Ink Three-dimensional printing Nickel Polymers

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Comparing Middle-Aged and Seniors’ Preferences Toward Virtual Agents and Android Robots: Is There a Generational Shift in Assistive Technologies’ Preferences? 11th

Comparing Middle-Aged and Seniors’ Preferences Toward Virtu...

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11th Italian Forum on Ambient Assisted Living, ForItAAL 2020

作者： Esposito, Anna Amorese, Terry Cuciniello, Marialucia Cavallo, Filippo Vinciarelli, Alessandro Cordasco, Gennaro Department of Psychology Università degli Studi della Campania "Luigi Vanvitelli" and IIASS Caserta Italy Department of Industrial Engineering BioRobotics Institute SS Sant’Anna and Department of Excellence in Robotics & AI Florence University Firenze Italy School of Computing Science and the Institute of Neuroscience and Psychology University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9783031088377

The present research aims at investigating effects of participants’ age (middle-aged and seniors) and type of assistive device (female virtual agents vs female android robots) on users’ acceptance. The study involved 4 groups of two middle-aged and two seniors (for a total of 181) participants asked to ex- press their potential acceptance to be assisted in their daily routines by two female android robots/virtual agents. Acceptance was assessed in terms of scores assigned by participants to their willingness to interact with the female agents/robots and pragmatic (PQ), hedonic - identity (HQI), hedonic - feeling (HQF) and attractiveness (ATT) qualities. Video clips of the proposed agents or robots were randomly presented, and after each presentation, participants scored the proposed assistive device by filling either the VAAQ (Virtual Agent Acceptance) or the RAQ (Robot Acceptance) questionnaire. Repeated measures ANOVA were utilized to statistically assess participants’ preferences. Seniors were significantly more open to interact with virtual agents rather than robots, while middle-aged participants were showed slightly more open to interact with robots rather than agents. Participants’ gender significantly affected the evaluation of robots rather than agents’ one, and the appearance of the proposed de- vices (younger toward mature agents, or haired toward hairless robots), strongly affected users’ acceptance. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Robots

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Structuring Clinical Notes of Italian ST-elevation Myocardial Infarction Patients 1

Structuring Clinical Notes of Italian ST-elevation Myocardia...

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1st Workshop on Patient-Oriented Language Processing, CL4Health 2024

作者： Torri, Vittorio Mazzucato, Sara Dalmiani, Stefano Paradossi, Umberto Passino, Claudio Moccia, Sara Micera, Silvestro Ieva, Francesca MOX - Modelling and Scientific Computing Lab Department of Mathematics Politecnico di Milano Italy Biorobotics Institute Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Italy Fondazione Toscana Gabriele Monasterio Italy Health Science Interdisciplinary Center Scuola Superiore Sant’Anna Italy Bertarelli Foundation Chair in Translational Neural Engineering Center for Neuroprosthetics Institute of Bioengineering Ecole Polytechnique Federale de Lausanne Switzerland HDS - Health Data Science Centre Human Technopole Italy

ISBN: (纸本)9782493814258

In recent years, it has become common for patients to get full access to their Electronic Health Records (EHRs), thanks to the advancements in the EHRs systems of many healthcare providers. While this access empowers patients and doctors with comprehensive and real-time health information, it also introduces new challenges, in particular due to the unstructured nature of much of the information within EHRs. To address this, we propose a pipeline to structure anamneses, providing patients with a clear and concise overview of their health data and its longitudinal evolution, also allowing clinicians to focus more on patient care during consultations. In this paper, we present preliminary results on extracting structured information from EHRs of patients diagnosed with ST-Elevation Myocardial Infarction from an Italian hospital. Our pipeline exploits text classification models to extract relevant clinical variables, comparing rule-based, recurrent neural network and BERT-based models. While various approaches utilized ontologies or knowledge graphs for Italian data, our work represents the first attempt to develop this type of pipeline. The results for the extraction of most variables are satisfactory (f1-score > 0.80), with the exception of the most rare values of certain variables, for which we propose future research directions to investigate. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Recurrent neural networks

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Characterization of a conductive hydrogel@Carbon fibers electrode as a novel intraneural interface

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Bioelectronic Medicine 2024年第1期10卷 1-14页

作者： Giannotti, Alice Santanché, Ranieri Zinno, Ciro Carpaneto, Jacopo Micera, Silvestro Riva, Eugenio Redolfi The Biorobotic Institute Scuola Superiore Sant’Anna Piazza Martiri Della Libertà 33 Pisa56127 Italy Department of Excellence in Robotics & amp AI Scuola Superiore Sant’Anna Piazza Martiri Della Libertà 33 Pisa56127 Italy Università Di Pisa Largo Lucio Lazzarino 1 Pisa56122 Italy Lausanne1007 Switzerland

Peripheral neural interfaces facilitate bidirectional communication between the nervous system and external devices, enabling precise control for prosthetic limbs, sensory feedback systems, and therapeutic interventions in the field of Bioelectronic Medicine. Intraneural interfaces hold great promise since they ensure high selectivity in communicating only with the desired nerve fascicles. Despite significant advancements, challenges such as chronic immune response, signal degradation over time, and lack of long-term biocompatibility remain critical considerations in the development of such devices. Here we report on the development and benchtop characterization of a novel design of an intraneural interface based on carbon fiber bundles. Carbon fibers possess low impedance, enabling enhanced signal detection and stimulation efficacy compared to traditional metal electrodes. We provided a 3D-stabilizing structure for the carbon fiber bundles made of PEDOT:PSS hydrogel, to enhance the biocompatibility between the carbon fibers and the nervous tissue. We further coated the overall bundles with a thin layer of elastomeric material to provide electrical insulation. Taken together, our results demonstrated that our electrode possesses adequate structural and electrochemical properties to ensure proper stimulation and recording of peripheral nerve fibers and a biocompatible interface with the nervous tissue. © The Author(s) 2024.

关键词： Tissue

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