The research team designed THInkPen around a deceptively simple requirement: the pen must behave like any ordinary pen. Children hold it, move it and write with it exactly as they would with a standard ballpoint, producing real ink on real paper. This is a substantial departure from many digital screening tools, most notably tablets, which require children to write on a glass surface with a stylus and can subtly alter the mechanics of handwriting. By preserving the natural writing experience, the researchers argue, THInkPen captures a more authentic picture of a child’s writing process rather than an artifact of the measurement technology itself.

Underneath that familiar exterior, however, sits a sophisticated array of sensors. As the children wrote, the pen continuously sampled signals describing the pressure applied to the paper, the fluency and smoothness of movement, the inclination of the pen, and the frequency of the signals transmitted to the device. From these raw measurements, the team computed a set of digital indicators covering different dimensions of the writing process. Rather than judging only the final written product, as conventional tests do, the device records the entire dynamic journey from the first stroke to the last letter.

To validate the device, the researchers asked study participants to complete two tasks from the BVSCO-3, the Battery for the Clinical Assessment of Writing and Orthographic Skills. This battery is the most widely used clinical test in Italy for assessing writing difficulties, dysgraphia and dysorthography, which makes it a rigorous benchmark against which any new screening technology must prove itself. The digital indicators gathered by the pen were then analyzed in three ways: the team examined their correlation with clinical scores, modeled how they progress across school grades, and tested their usefulness in detecting writing difficulties using artificial intelligence algorithms developed specifically for the task.

The results were striking. The analysis revealed significant and consistent relationships between the digital indicators and the clinical scores, confirming that the sensor-derived measures reliably reflect the performance characteristics that clinicians assess by hand. In other words, the pen’s invisible record of pressure, rhythm and fluency tracks closely with the judgments that trained specialists make when they score a child’s handwriting on paper. This correspondence is precisely what any screening tool must demonstrate before it can be trusted in schools.

Artificial intelligence then took the analysis a step further. Binary classification models trained on the pen data successfully distinguished students with writing difficulties, identified on the basis of their BVSCO-3 results, from the other students. Crucially, the researchers did not stop at a correct-or-incorrect verdict. They applied Explainable Artificial Intelligence, or XAI, techniques to open up the model’s reasoning and identify the reasons underlying below-average performance. Instead of a black-box flag that a child may have a problem, teachers and clinicians could receive an interpretable account of which aspects of the writing process deviate from the norm, paving the way for targeted interventions matched to each child’s specific profile.

The statistical analysis across school grades added another layer of validation. It showed that the digital indicators faithfully reproduced the well-established pattern of improvement in writing that occurs from one grade to the next, demonstrating their sensitivity in capturing the development of graphomotor skills over time. A measurement tool that cannot detect developmental change would be of limited use in a school setting, where the goal is not only to identify current difficulties but to monitor progress as children grow. THInkPen’s ability to mirror this trajectory suggests the device could serve as a longitudinal companion to routine education.

The study stems from the PRIN research project e-School 2.0, coordinated by the Department of Electronics, Information and Bioengineering at Politecnico di Milano in collaboration with the University of Insubria. Simona Ferrante, professor at the department and coordinator of the Politecnico di Milano research team, explains that using THInkPen to analyze not only the final written product but the entire writing process could support the early identification of writing difficulties in schools, thus facilitating the timely and effective activation of clinical services. The distinction matters because timing is often decisive: writing difficulties that are recognized early can be addressed before they compound into broader academic struggles and loss of confidence.

The clinical context gives the work particular urgency. Cristiano Termine, professor of Child Neuropsychiatry at the University of Insubria, notes that the aspect is particularly relevant in light of the growing demand that Child and Adolescent Neuropsychiatry services face on a daily basis, and the resulting long waiting lists. School difficulties are one of the main reasons children are referred for assessment by these services, but not all the difficulties experienced by students necessarily require specialist clinical evaluation. Termine argues that it therefore becomes essential to have reliable observation and screening tools that can help schools better understand the nature of these difficulties and identify at an earlier stage those situations that genuinely require referral to Child and Adolescent Neuropsychiatry services. A tool like THInkPen could act as a filter, easing pressure on overloaded services while ensuring that children who do need specialist attention are not left waiting behind those who do not.

The pen itself has a longer history than its current application might suggest. The THInkPen project, patented by Politecnico di Milano together with the University of Milan in collaboration with professor Alberto Borghese, was initially conceived for the screening of neurodegenerative diseases and was subsequently developed for neurodevelopmental assessment. Linda Greta Dui, a researcher at the Department of Electronics, Information and Bioengineering and recipient of the Tecnovisionaria 2025 Award on this topic, also contributed to this development. The latest publication additionally involved Cesare Cornoldi, professor emeritus at the University of Padua and one of the developers of the BVSCO-3, along with ASST Sette Laghi and the Neuroscience Centre of Los Madroños Hospital in Madrid. Taken together, the study points toward a future in which the same device used for a routine classroom writing exercise can double as a sensitive diagnostic instrument, screening hundreds of children non-invasively, at low cost and without disrupting the natural act of writing, while giving clinicians the quantitative evidence they need to prioritize care where it is most needed.

Subject of Research: Early screening of dysgraphia and writing difficulties in schoolchildren using a sensorized ink pen

Article Title: THInkPen, a “smart” pen for early screening of dysgraphia: study by Politecnico di Milano and the University of Insubria published

Article References: THInkPen, a “smart” pen for early screening of dysgraphia: study by Politecnico di Milano and the University of Insubria published. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: dysgraphia, THInkPen, sensorized pen, handwriting, learning disorders, screening, BVSCO-3, artificial intelligence, explainable AI, child neuropsychiatry, graphomotor skills, Politecnico di Milano

At the core of this innovation lies the development of an intricate digital environment designed to simulate and optimize the operation of self-driving tractors within vineyard settings. This virtual ecosystem, often referred to as a “digital twin,” meticulously mirrors the vineyard’s physical characteristics—including slope gradients, soil texture variations, and the precise geometry of row spacing. By creating this highly realistic simulation, researchers can rigorously test autonomous navigation algorithms, refine control strategies, and predict operational outcomes without the inherent risks and costs of real-world trials.

The research team, comprising experts from the Departments of Mechanical Engineering and Electronics, Information and Bioengineering, has engineered a comprehensive methodological framework for scenario generation. This framework encompasses the synthesis of detailed terrain models and the integration of sensor data streams typical of actual agricultural machinery. By employing low-cost Global Navigation Satellite Systems (GNSS) alongside Inertial Measurement Units (IMU), the virtual tractors execute precise movements that replicate true field conditions. These autonomous vehicles demonstrate an ability to navigate between tightly spaced vine rows and perform complex off-field maneuvers with unprecedented accuracy.

Key to this advancement is the synergistic combination of terrain modeling, sensor emulation, and advanced control algorithms, all embedded within a singular simulation environment. This integration ensures that every aspect influencing vineyard operations—from micro-topography to sensor noise—is faithfully represented. Such fidelity accelerates the iterative process of developing autonomous control systems, bridging the gap between theoretical algorithmic strategies and practical field applications. Furthermore, it dramatically curtails the time and resources traditionally allocated to on-site validation, presenting a transformative leap forward for agricultural engineering.

The implications of this digital twin extend beyond mere operational efficiencies. Researchers envision these simulations as vital tools for operator training, facilitating a controlled setting where human supervisors can familiarize themselves with autonomous machinery behaviors and refine intervention protocols without risking crop damage or machinery faults. This educational facet is seen as a crucial catalyst for broader adoption of automation technologies, breaking down barriers related to unfamiliarity and mistrust that commonly hinder innovation in traditional farming communities.

The initiative has been bolstered through a collaborative partnership with Soluzioni Ingegneria s.r.l., an industry leader specializing in dynamic vehicle simulation software. This alliance embeds academic innovation within the practical frameworks demanded by commercial agricultural equipment manufacturers, ensuring that theoretical models translate effectively into market-ready technologies. It is this blend of scholarly research and industrial application that positions the project at the nexus of agricultural automation and sustainable farming.

From a sustainability perspective, the precise control afforded by autonomous tractors promises substantial environmental benefits. More exact navigation reduces soil compaction and disturbance, while the ability to execute carefully modulated maneuvers minimizes resource wastage. Additionally, optimizing field operations through predictive algorithms aligns with broader ecological goals to reduce carbon footprints and conserve soil health, thereby contributing to resilient agricultural ecosystems in the face of climate change.

This research arrives at a pivotal moment for global agriculture, where the dual pressures of increasing food demand and environmental stewardship mandate innovative technological responses. By embedding advanced robotics and sensor technologies within the unique context of vineyards, the Politecnico di Milano project addresses a sector ripe for disruption. Traditional viticulture, often labor-intensive and tailored to delicate crop requirements, is now poised to embrace automation without compromising the intricate balance of terroir and grape quality.

The published findings, detailed in the latest issue of AgriEngineering, offer a comprehensive analysis of the methodologies employed, simulation parameters, and algorithmic control strategies. The paper elucidates the challenges inherent in replicating complex vineyard environments digitally and discusses the iterative optimization process through which autonomous tractor performance was enhanced. This transparency not only advances academic discourse but also provides a valuable reference point for developers and practitioners aiming to implement similar systems across diverse agricultural contexts.

Beyond the immediate scope of viticulture, the technological principles underpinning this research hold broader applicability. The combination of digital twins with sensor-driven autonomous machinery paves the way for smarter, more resilient farming operations across various crops and terrains. By validating control strategies in virtual environments, stakeholders can anticipate system behaviors under myriad conditions, thereby reducing uncertainty and enhancing decision-making efficacy.

The vision articulated by Professor Federico Cheli, who leads the Mechanical Engineering department and coordinates the project, encapsulates a future where digital simulation is integral to agricultural innovation. His emphasis on integrating realistic sensors, terrain data, and advanced controls reflects a holistic approach that acknowledges the multifaceted challenges of field automation. This mindset exemplifies the evolving role of engineering disciplines in shaping next-generation food systems.

As autonomous technologies gain foothold in agriculture, the nexus of simulation science, robotics, and environmental sustainability will undoubtedly expand. The achievements of the Politecnico di Milano team demonstrate the feasibility and value of a simulation-first approach to developing high-precision vineyard operations. Their work embodies a critical step toward smart agriculture, where data-driven insights and autonomous control converge to cultivate not only grapes but a more sustainable and productive future for farming worldwide.

Subject of Research: Not applicable
Article Title: Scenario Generation and Autonomous Control for High-Precision Vineyard Operations
News Publication Date: 11th November 2025
Web References: http://dx.doi.org/10.3390/agriengineering7020046
References: Ruiz Mayo, C.; Cheli, F.; Arrigoni, S.; Paparazzo, F.; Mentasti, S.; Pezzola, M.E. Scenario Generation and Autonomous Control for High-Precision Vineyard Operations. AgriEngineering 2025, 7(2), 46.
Image Credits: Politecnico di Milano
Keywords: Agricultural engineering, Sustainable agriculture, Robots

The LUMEN project, led by Dr. Emanuele Riva from the Department of Mechanical Engineering, delves into the forefront of neurostimulation technology through the development of advanced acoustic metamaterials. Its core focus lies in optimizing transcranial focused ultrasound (tFUS), a non-invasive modality increasingly harnessed to treat movement disorders like Parkinson’s disease and essential tremor. One of the paramount challenges in current tFUS applications is the unintended dispersion of “leaky-Lamb waves,” acoustic waves scattered irregularly by the complex barrier of the human skull. These waves diminish the precision and efficacy of ultrasound brain stimulation, limiting clinical outcomes.

To confront this obstacle, LUMEN proposes a pioneering approach that engineers acoustic metasurfaces capable of controlling the emission direction of these leaky-Lamb waves at their source. Acoustic metasurfaces, a class of precisely arranged nanostructures, manipulate the propagation of sound waves through subwavelength scale modifications. By integrating biocompatible implants fashioned with these metasurfaces, the project aims to significantly refine the focal targeting of ultrasound energy. The anticipated effect is twofold: enhanced accessibility of the technology, and a remarkable increase in the precision of stimulation, especially in previously hard-to-reach peripheral brain regions. This advancement may revolutionize treatment protocols for millions suffering from debilitating tremors and neuropathic pain, extending therapeutic benefits to diverse patient profiles.

Dr. Riva’s background in structural dynamics and elastic wave mechanics underpins this ambitious enterprise. Having earned his PhD with honors from Politecnico di Milano, his research portfolio is distinguished by expertise in metamaterials and wave propagation, encompassing vibration control and energy harvesting technologies. His engagement with academic publications and patents, along with co-founding a specialized company in vibrational acoustics, demonstrates a rare blend of fundamental research and entrepreneurial innovation essential for bridging theoretical concepts with clinical applications.

Parallel to LUMEN’s endeavor, the ALFRED project, spearheaded by Dr. Claudio Conci from the Department of Chemistry, Materials, and Chemical Engineering “Giulio Natta,” embarks on a radically novel diagnostic frontier. ALFRED stands for Positron Annihilation Lifetime Spectroscopy for Revealing and Quantifying Inflammation and Endothelial Diseases. It exploits the particle physics technique of Positron Annihilation Spectroscopy (PAS) to detect early-stage inflammatory signatures with unparalleled resolution and non-invasiveness. Inflammation’s stealthy onset often eludes conventional diagnostic tools until manifest symptoms appear, delaying timely intervention in conditions ranging from cancer to neurodegenerative and cardiovascular diseases.

PAS uniquely harnesses the behavior of positrons—antiparticles of electrons—that, upon interacting with electrons in biological tissue, annihilate and emit gamma rays. The timing and spatial characteristics of this emission can reveal microscopic changes in tissues at the molecular and cellular levels. By adapting this technique to medical imaging, ALFRED seeks to quantify localized inflammation with sensitivity far exceeding existing modalities. This fusion of bioengineering, nuclear medicine, and particle physics could reshape preventive healthcare by intercepting disease processes before irreversible damage ensues.

Dr. Conci, whose academic genesis blends biomedical and bioengineering disciplines, has honed his expertise through multidisciplinary collaborations with Italy’s leading research institutes. His career focus on ethical imaging solutions and miniaturized medical diagnostic devices lays the foundation for ALFRED’s integrative methodology. The project exemplifies the translation of fundamental physics into tangible, life-saving medical technologies.

Politecnico di Milano’s distinction as Italy’s prime locus for Horizon Europe funding underscores its strategic role in fostering scientific excellence. Housing 362 projects amounting to over 175 million euros and securing 39 ERC projects worth over 41 million euros, the institution exemplifies leadership in advancing frontier research. The selection of LUMEN and ALFRED among 478 ERC-funded projects in 2025 highlights their exceptional potential to redefine medical engineering paradigms.

ERC Starting Grants fuel early-career researchers who have recently obtained their doctorates but stand at a critical juncture to embark on independent scientific trajectories. The grants encourage audacious, foundational research peering beyond existing knowledge frontiers. Both projects resonate with this mandate, as they challenge established constraints within their respective domains and engage interdisciplinary synergies.

The potential impact of LUMEN extends beyond treating motor symptoms; by enhancing the precision of ultrasound wave focusing via metamaterial engineering, it opens avenues for neuromodulation therapies targeting a broad spectrum of neurological disorders. Its emphasis on affordability and accessibility further ensures that such advanced treatments may reach underserved populations worldwide, addressing health equity issues intrinsic to medical innovation.

Conversely, ALFRED’s promise lies in revolutionizing diagnostics by unveiling invisible biological processes that underpin inflammation—a precursor to numerous chronic and acute conditions. With the capacity to detect molecular perturbations non-invasively and at an early stage, this technology could enable clinicians to devise personalized treatments, optimize therapeutic windows, and ultimately improve prognoses.

Taken together, these initiatives exemplify how convergence science—melding material science, applied physics, bioengineering, and clinical medicine—can surmount longstanding limitations in healthcare. Their anticipated breakthroughs signify a future where non-invasive, precise, and rapid interventions become standard components of disease management, elevating patient care to unprecedented levels.

As the LUMEN and ALFRED projects forge ahead under the Politecnico di Milano umbrella, their trajectories illuminate the vital landscape where technological innovation intersects with urgent societal health needs. Supported by the visionary backing of the European Research Council, these projects embody the transformative potential of early-stage scientific ambition nurtured within world-class research environments.

The collaborative fabric woven through both projects, spanning multiple disciplines and institutions, reflects the modern ethos of scientific inquiry. It is this intersectional approach that fuels novel methodologies—from manipulating acoustic metamaterials at the microscale to applying positron physics in biological systems—ushering in a new era of medical diagnostics and therapeutics backed by precise, physics-based technologies.

In an era increasingly defined by personalized medicine and minimally invasive interventions, the LUMEN and ALFRED projects position themselves front and center as beacon initiatives. They are poised not only to deepen understanding of complex physiological phenomena but also to translate this knowledge swiftly and safely into patient-centered solutions. The coming years will be pivotal in witnessing how these ERC-funded endeavors reshape the sonic and imaging landscapes underpinning essential neurological and inflammatory disease care.

Subject of Research: Acoustic Metamaterials for Focused Ultrasound Neuromodulation; Positron Annihilation Spectroscopy for Inflammation Detection

Article Title: Pioneering Neuromodulation and Inflammation Diagnostics: Politecnico di Milano’s ERC-Funded Breakthroughs in Medical Engineering

News Publication Date: 2025

Web References:
https://mediasvc.eurekalert.org/Api/v1/Multimedia/69a8ade3-3d36-4432-9738-a036ceaebfb6/Rendition/low-res/Content/Public

Image Credits: Claudio Conci

Keywords: Acoustic Metamaterials, Focused Ultrasound, Neuromodulation, Positron Annihilation Spectroscopy, Inflammation Detection, Biomedical Engineering, Structural Dynamics, Particle Physics, Neurodegenerative Diseases, Medical Imaging, Non-invasive Diagnostics, European Research Council