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PEOPLE@HES-SO – Annuaire et Répertoire des compétences
PEOPLE@HES-SO – Annuaire et Répertoire des compétences

PEOPLE@HES-SO
Annuaire et Répertoire des compétences

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Pirrami Lorenzo

Pirrami Lorenzo

Professeur HES associé

Compétences principales

ASIC / FPGA / SoC

Digital Circuits and Systems

RFID

Wireless power transfer

Bioelectronics

Modeling and simulation

  • Contact

  • Enseignement

  • Recherche

  • Publications

Contrat principal

Professeur HES associé

Téléphone: +41 26 429 69 10

Bureau: HEIA_C20.03

Haute école d'ingénierie et d'architecture de Fribourg
Boulevard de Pérolles 80, 1700 Fribourg, CH
HEIA-FR
Institut
iSIS - Institut des systèmes intelligents et sécurisés
BSc HES-SO en Génie électrique - Haute école d'ingénierie et d'architecture de Fribourg
  • Electronique analogique
  • Modélisation et simulation (Modeling and numerical simulations)
  • Système numériques (FPGA/SoC/ASIC)

En cours

Novel Digital Pixel Design for Fast Spectral X-Ray Detectors in Computed Tomography

Rôle: Co-requérant(s)

Financement: Innosuisse | Innovation cheque

Description du projet :

Design of a new generation ASIC for photon-counting detectors in Computed Tomography (CT) applications.

Equipe de recherche au sein de la HES-SO: Pirrami Lorenzo

Partenaires professionnels: Niklaus Lehmann, Dectris AG

Durée du projet: 01.04.2024 - 30.09.2024

Montant global du projet: 15'000 CHF

Statut: En cours

Exploring RISC-V Core-based Microcontrollers for Implementation in Industrial and Automotive Sensor ASICs

Rôle: Requérant(e) principal(e)

Financement: NPR (Nouvelle Politique Régionale), Contrinex SA, Microdul AG, Sonova Communications SA, Melexis Technologies SA, Johnson Electric International AG

Description du projet :

In today's fast-paced technological landscape, the demand for smart sensors with improved performance and efficiency
is ever-increasing. Application-Specific integrated Circuits (ASICs) are custom-designed chips tailored for specific tasks
and play a crucial role in this transition. An ASIC with an integrated microcontroller provides processing power, control
capabilities and communication interfaces, thereby operating effectively in disparate and complex applications. In this
context, RISC-V has become a standout player, drawing a considerable attention in the last couple of years. RISC-V
distinguishes itself by being an open-source architecture, eliminating costs related to licenses and royalties. This,
coupled with its inherent flexibility, facilitates seamless customization and optimization across a diverse range of
applications. Moreover, RISC-V core-based ASIC design encourages innovation within a dynamic and shared
ecosystem. Today, tech giants such as Google are already designing new generation Central Processing Unit (CPU)
architectures based on the RISC-V. This statement alone captures the extensive scope and immense potential of a
RISC-V architecture.


Despite its prominence in larger-scale and high-performance computing applications, RISC-V is not yet common in
industrial sensors ASICs which require mature technologies driven by a combination of precision requirements, reliability
considerations and cost effectiveness. Today several 0.18 μm high voltage and analog mixed-signal technologies are
matured and have lower prices. This allows considering the design of more complex circuits, including microcontrollers
and application-specific coprocessors. To exploit the full potential of the RISC-V technology, industrial partners have to
face challenges in hardware-related technical aspects as well as maturity- and security-related concerns about software
toolchains.


The goal of this project is to foster a shared understanding among industrial partners about the open-source RISC-V
architecture, both in terms of its hardware and the software toolchain ecosystem. The project will focus on low power
and low footprint ASIC implementations with a close look at safety and software security aspects. This collaborative
knowledge-sharing initiative will enable industrial partners to make informed decisions, promote innovation and drive
the adoption of RISC-V architectures into their industrial sensors.

Equipe de recherche au sein de la HES-SO: Pirrami Lorenzo

Partenaires académiques: Silva Eric, ROSAS

Partenaires professionnels: Genilloud Laurent, Contrinex SA; Muttersbach Jens, Microdul AG; Ostermann Christophe, Sonova Communications SA; Aeby Fabien, Melexis Technologies SA; Oberlin Eric, Johnson Electric International AG

Durée du projet: 01.02.2024 - 31.12.2024

Montant global du projet: 200'769 CHF

Statut: En cours

Smart Proximity Sensors for Harsh 4.0 Industry Applications

Rôle: Requérant(e) principal(e)

Financement: Innosuisse

Description du projet :

The goal of this project is to design an Application-Specific Integrated Circuit (ASIC) for new generation smart proximity sensors used in harsh 4.0 industry applications.

Equipe de recherche au sein de la HES-SO: Pirrami Lorenzo

Partenaires professionnels: Contrinex SA

Durée du projet: 01.01.2024

Montant global du projet: 873'460 CHF

Statut: En cours

Terminés

ASIC design for inductive proximity sensors

Rôle: Requérant(e) principal(e)

Financement: Contrinex SA

Description du projet :

Digital ASIC design from VHDL description to the layout generation and tape out.

Equipe de recherche au sein de la HES-SO: Pirrami Lorenzo , Bourquenoud Mathieu

Partenaires professionnels: Laurent Genilloud, Contrinex SA, Corminboeuf

Durée du projet: 01.07.2022 - 30.06.2024

Montant global du projet: 70'000 CHF

Statut: Terminé

Experimental and numerical study of a new micro-manipulation technique based on liquid plugs

Rôle: Requérant(e) principal(e)

Financement: HEIA-FR

Description du projet :

In spite of the very large interest in the discretization (or digitalization) of liquid carrier fluids for Lab-on-a-Chip
applications, the use of liquid plugs for the manipulation of micro-objects is an unexplored field, yet, with a huge
market potential. In fact, according to BCC Research (a market research reports and forecasts company), in
2015 the global market for the micromanipulation (transport, pick and place and assembly) technology was
$24.9 billion and it is expected to reach $41.4 billion in 2021.


Based on recent results of a research project at iPrint, the aim of this project is the valorisation and capitalisation
of aR&D competences by means of in-depth experimental tests and numerical simulations of a new type of
micro-manipulation technique based on liquid plugs in microchannels.

Equipe de recherche au sein de la HES-SO: Balestra Gioele , Pirrami Lorenzo , Maturo Jonas

Durée du projet: 14.01.2020 - 01.01.2022

Montant global du projet: 79'124 CHF

Statut: Terminé

ASIC design with embedded ARM Cortex M0-based uC for industrial smart sensors

Rôle: Requérant(e) principal(e)

Financement: HES-SO, Contrinex

Description du projet :

ARM Cortex M0-based microcontroller integration into the ASIC of Contrinex's new generation industrial smart sensors.

Equipe de recherche au sein de la HES-SO: Pirrami Lorenzo

Partenaires professionnels: Laurent Genilloud, Contrinex SA, Corminboeuf

Durée du projet: 01.01.2021 - 29.10.2021

Montant global du projet: 60'000 CHF

Statut: Terminé

Innosuisse start-up initial coaching

Rôle: Requérant(e) principal(e)

Financement: Innosuisse

Description du projet :

Towards highly connected civil infrastructures for the long term monitoring

Equipe de recherche au sein de la HES-SO: Pirrami Lorenzo

Durée du projet: 01.03.2021 - 30.09.2021

Montant global du projet: 5'000 CHF

Statut: Terminé

New assembly process for passive and capacitive-coupled RFID tags

Rôle: Requérant(e) principal(e)

Financement: HES-SO

Description du projet :

Radio frequency identification (RFID) is a well-established, widespread and fast-growing technology used to identify people, animals and products. The applications of RFID tags encompass the retail, transportation, logistics, healthcare, etc. According to IDTechEx, the retail sector alone was responsible for the demand of 4.6 billion RFID tags in 2016 and is expected to reach 8.1 billion in 2024. The RFID technology is also playing a leading role for manufacturing applications. As part of the Industry 4.0, RFID tags allow more flexible and efficient manufacturing of customized products even in mass-production environments.

In this project, we demonstrate theoretically and experimentally the feasibility of a new assembly approach in which a capacitive-coupled RFID chip will be delivered inside a dielectric droplet, onto the antenna and no longer placed and oriented precisely as it happens nowadays with pick-and-place and flip chip machines. The dielectric droplet (with the encapsulated chip) will self-aligns with respect to the contact thanks to capillary forces driven by specifically designed wetting conditions on the substrate of the antenna. Finally, with few additional steps, the complete passive RFID tag is created.

Equipe de recherche au sein de la HES-SO: Pirrami Lorenzo

Durée du projet: 03.09.2018 - 30.08.2019

Montant global du projet: 125'000 CHF

Statut: Terminé

2024

Large scale ultrafast manufacturing of wireless soft bioelectronics enabled by autonomous robot arm printing assisted by a computer vision-enabled guidance system for personalized wound healing
Article scientifique ArODES

Jihyun Kim, Seol-Ha Jeong, Brendan Craig Thibault, Javier Alejandro Lozano Soto, Hiroyuki Tetsuka, Surya Varchasvi Devaraj, Estefania Riestra, Yeongseok Jang, Seo Jeong Wook, Rafael Alejandro Cornejo Rodríguez, Lucia L. Huang, Yuhan Lee, Ioana Preda, Sameer Sonkusale, Lance Fiondella, Jungmok Seo, Lorenzo Pirrami, Su Ryon Shin

Advanced Healthcare Materials,  2024, To be published.

Lien vers la publication

Résumé:

A Customized wound patch for Advanced tissue Regeneration with Electric field (CARE), featuring an autonomous robot arm printing system guided by a computer vision-enabled guidance system for fast image recognition is introduced. CARE addresses the growing demand for flexible, stretchable, and wireless adhesive bioelectronics tailored for electrotherapy, which is suitable for rapid adaptation to individual patients and practical implementation in a comfortable design. The visual guidance system integrating a 6-axis robot arm enables scans from multiple angles to provide a 3D map of complex and curved wounds. The size of electrodes and the geometries of power-receiving coil are essential components of the CARE and are determined by a MATLAB simulation, ensuring efficient wireless power transfer. Three heterogeneous inks possessing different rheological behaviors can be extruded and printed sequentially on the flexible substrates, supporting fast manufacturing of large customized bioelectronic patches. CARE can stimulate wounds up to 10 mm in depth with an electric field strength of 88.8 mV mm−1. In vitro studies reveal the ability to accelerate cell migration by a factor of 1.6 and 1.9 for human dermal fibroblasts and human umbilical vein endothelial cells, respectively. This study highlights the potential of CARE as a clinical wound therapy method to accelerate healing.

AI-driven electrical fast transient suppression for enhanced electromagnetic interference immunity in inductive smart proximity sensors
Article scientifique ArODES

Silvia Giangaspero, Gianluca Nicchiotti, Philippe Venier, Laurent Genilloud, Lorenzo Pirrami

Sensors,  2024, 24, 22, 7372

Lien vers la publication

Résumé:

Inductive proximity sensors are relevant in position-sensing applications in many industries but, in order to be used in harsh industrial environments, they need to be immune to electromagnetic interference (EMI). The use of conventional filters to mitigate these perturbations often compromises signal bandwidth, ranging from 100 Hz to 1.6 kHz. We have exploited recent advances in the field of artificial intelligence (AI) to study the ability of neural networks (NNs) to automatically filter out EMI features. This study offers an analysis and comparison of possible NN models (a 1D convolutional NN, a recurrent NN, and a hybrid convolutional and recurrent approach) for denoising EMI-perturbed signals and proposes a final model, which is based on gated recurrent unit (GRU) layers. This network is compressed and optimised to meet memory requirements, so that in future developments it could be implemented in application-specific integrated circuits (ASICs) for inductive sensors. The final RNN manages to reduce noise by 70% (MSEred) while occupying 2 KB of memory.

Wirelessly steerable bioelectronic neuromuscular robots adapting neurocardiac junctions
Article scientifique ArODES

Hiroyuki Tetsuka, Samuele Gobbi, Takaaki Hatanaka, Lorenzo Pirrami, Su Ryon Shin

Science Robotics,  2024, 9, 94

Lien vers la publication

Résumé:

Biological motions of native muscle tissues rely on the nervous system to interface movement with the surrounding environment. The neural innervation of muscles, crucial for regulating movement, is the fundamental infrastructure for swiftly responding to changes in body tissue requirements. This study introduces a bioelectronic neuromuscular robot integrated with the motor nervous system through electrical synapses to evoke cardiac muscle activities and steer robotic motion. Serving as an artificial brain and wirelessly regulating selective neural activation to initiate robot fin motion, a wireless frequency multiplexing bioelectronic device is used to control the robot. Frequency multiplexing bioelectronics enables the control of the robot locomotion speed and direction by modulating the flapping of the robot fins through the wireless motor innervation of cardiac muscles. The robots demonstrated an average locomotion speed of ~0.52 ± 0.22 millimeters per second, fin-flapping frequency up to 2.0 hertz, and turning locomotion path curvature of ~0.11 ± 0.04 radians per millimeter. These systems will contribute to the expansion of biohybrid machines into the brain-to-motor frontier for developing autonomous biohybrid systems capable of advanced adaptive motor control and learning.

2022

Wirelessly powered 3D printed hierarchical biohybrid robots with multiscale mechanical properties
Article scientifique ArODES

Hiroyuki Tetsuka, Lorenzo Pirrami, Ting Wang, Danilo Demarchi, Su Ryon Shin

Advanced Functional Materials,  2022, 32, 31, 2202674

Lien vers la publication

Résumé:

The integration of flexible and stretchable electronics into biohybrid soft robotics can spur the development of new approaches for fabricating biohybrid soft machines, thus enabling a wide variety of innovative applications. Inspired by flexible and stretchable wireless-based bioelectronic devices, untethered biohybrid soft robots are developed that can execute swimming motions, which are remotely controllable by the wireless transmission of electrical power into a cell simulator. To this end, wirelessly-powered, stretchable, and lightweight cell stimulators are designed to be integrated into muscle bodies without impeding the robots’ underwater swimming abilities. The cell stimulators function by generating controlled monophasic pulses of up to ≈9 V in biological environments. By differentiating induced pluripotent stem cell-derived cardiomyocytes directly on the cell stimulators using an accordion-inspired, three-dimensional (3D) printing construct, the native myofiber architecture are replicated with comparable robustness and enhanced contractibility. Wirelessly modulated electrical frequencies enables the control of speed and direction of the biohybrid soft robots. A maximum locomotion speed of ≈580 µm s−1 is achieved in robots possessing a large body size by adjusting the pacing frequency. This innovative approach will provide a platform for building untethered and biohybrid systems for various biomedical applications.

2018

Electrically driven microengineered bioinspired soft robots
Article scientifique ArODES

Su Ryon Shin, Bianca Migliori, Beatrice Miccoli, Yi-Chen Li, Pooria Mostafalu, Jungmok Seo, Serena Mandla, Alessandro Enrico, Silvia Antona, Ram Sabarish, Ting Zheng, Lorenzo Pirrami, Kaizhen Zhang, Yu Shrike Zhang, Kai-Tak Wan, Danilo Demarchi, Mehmet R. Dokmeci, Ali Khademhosseini

Advanced Materials,  2018, vol. 30, no.10

Lien vers la publication

Résumé:

To create life-like movements, living muscle actuator technologies have borrowed inspiration from biomimetic concepts in developing bioinspired robots. Here, the development of a bioinspired soft robotics system, with integrated self-actuating cardiac muscles on a hierarchically structured scaffold with flexible gold microelectrodes is reported. Inspired by the movement of living organisms, a batoid-fish-shaped substrate is designed and reported, which is composed of two micropatterned hydrogel layers. The first layer is a poly(ethylene glycol) hydrogel substrate, which provides a mechanically stable structure for the robot, followed by a layer of gelatin methacryloyl embedded with carbon nanotubes, which serves as a cell culture substrate, to create the actuation component for the soft body robot. In addition, flexible Au microelectrodes are embedded into the biomimetic scaffold, which not only enhance the mechanical integrity of the device, but also increase its electrical conductivity. After culturing and maturation of cardiomyocytes on the biomimetic scaffold, they show excellent myofiber organization and provide self-actuating motions aligned with the direction of the contractile force of the cells. The Au microelectrodes placed below the cell layer further provide localized electrical stimulation and control of the beating behavior of the bioinspired soft robot.

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