Archivio della ricerca - Fondazione Bruno Kessler
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Preliminary Validation of an IMU-based Physiotherapy Assessment System for the Lower Extremities
No full textPhysiotherapy assessments traditionally rely on the clinician’s interpretation to evaluate musculoskeletal conditions. However, technology, such as Inertial Measurement Units (IMU), is increasingly used to assist medical professionals. This study evaluates the accuracy and reliability of the Euleria Lab (ELAB) rehabilitation system against an optical motion capture system (OPTO). 7 healthy volunteers were instrumented with 5 IMU and 22 retroreflective markers and performed lower limbs single-plane and multi-plane movements. Joint angles were used to compute Range of Motion (ROM), Root Mean Squared Error (RMSE), Bland-Altman plots and intraclass correlation coefficient (ICC). ROM and RMSE were analysed using two RM ANOVA. In multi-plane tasks, ankle, knee and hip angles were compared using Hotelling’s T2 statistical parametric mapping (SPM) test. No significant differences were found between the two systems for ROM and between tasks in terms of RMSE. However, hip rotation showed large RMSE and poor ICC reliability. Hip flexion and abduction showed good agreement and a systematic bias = 10°. Multi-joint tasks revealed significant differences only in hip flexion during lunges. Therefore, ELAB proved highly accurate and reliable for the assessment of the movements: ankle, knee, and trunk flexion, but demonstrated poor accuracy and agreement during the hip rotation movement. ELAB displayed significant biases but good agreement and minor errors during hip flexion and abduction
Expected tracking performance of the ATLAS Inner Tracker at the High-Luminosity LHC
No full textThe high-luminosity phase of LHC operations (HL-LHC), will feature a large increase in simultaneous proton-proton interactions per bunch crossing up to 200, compared with a typical leveling target of 64 in Run 3. Such an increase will create a very challenging environment in which to perform charged particle trajectory reconstruction, a task crucial for the success of the ATLAS physics program, and will exceed the capabilities of the current ATLAS Inner Detector (ID). A new all-silicon Inner Tracker (ITk) will replace the current ID in time for the start of the HL-LHC. To ensure successful use of the ITk capabilities in Run 4 and beyond, the ATLAS tracking software has been successfully adapted to achieve state-of-the-art track reconstruction in challenging high-luminosity conditions with the ITk detector. This paper presents the expected tracking performance of the ATLAS ITk based on the latest available developments since the ITk technical design reports
A Holistic Digital Health Framework to Support Health Prevention Strategies in the First 1000 Days (Preprint)
Get PDFThe first 1000 days of a child's life, spanning from the time of conception until 2 years of age, are a key period of laying down the foundations of optimum health, growth, and development across the lifespan. Although the role of health prevention programs targeting families and children in the first 1000 days of life is well recognized, investments in this key period are scarce, and the provision of adequate health care services is insufficient. The aim of this viewpoint is to provide a holistic digital health framework cocreated with policy makers, health care professionals, and families to support more effective efforts and health care programs dedicated to the first 1000 days of life as the first line of prevention. The framework provides recommendations for leveraging on behavioral intervention technology and digital therapeutics solutions augmented by artificial intelligence to support the effective deployment of health prevention programs to families. The framework also encourages the adoption of a citizen science approach to co-design and evolve the digital health interventions with all relevant stakeholders in a real-world research perspective
3D Part Segmentation via Geometric Aggregation of 2D Visual Features
No full textSupervised 3D part segmentation models are tailored for a fixed set of objects and parts, limiting their transferability to open-set, real-world scenarios. Recent works have explored vision-language models (VLMs) as a promising alternative, using multi-view rendering and textual prompting to identify object parts. However, naively applying VLMs in this context introduces several drawbacks, such as the need for meticulous prompt engineering, and fails to leverage the 3D geometric structure of objects. To address these limitations, we propose COPS, a COmprehensive model for Parts Segmentation that blends the semantics extracted from visual concepts and 3D geometry to effectively identify object parts. COPS renders a point cloud from multiple viewpoints, extracts 2D features, projects them back to 3D, and uses a novel geometric-aware feature aggregation procedure to ensure spatial and semantic consistency. Finally, it clusters points into parts and labels them. We demonstrate that COPS is efficient, scalable, and achieves zero-shot state-of-the-art performance across five datasets, covering synthetic and real-world data, texture-less and coloured objects, as well as rigid and non-rigid shapes. The code is available at https://3d-cops.github.io
Mixing individual and collective behaviors to predict out-of-routine mobility
No full textPredicting human displacements is crucial for addressing various societal challenges, including urban design, traffic congestion, epidemic management, and migration dynamics. While predictive models like deep learning and Markov models offer insights into individual mobility, they often struggle with out-of-routine behaviors. Our study introduces an approach that dynamically integrates individual and collective mobility behaviors, leveraging collective intelligence to enhance prediction accuracy. Evaluating the model on millions of privacy-preserving trajectories across five US cities, we demonstrate its superior performance in predicting out-of-routine mobility, surpassing even advanced deep learning methods. The spatial analysis highlights the model’s effectiveness near urban areas with a high density of points of interest, where collective behaviors strongly influence mobility. During disruptive events like the COVID-19 pandemic, our model retains predictive capabilities, unlike individual-based models. By bridging the gap between individual and collective behaviors, our approach offers transparent and accurate predictions, which are crucial for addressing contemporary mobility challenges
La politicizzazione dello scetticismo e il declino della fede nella democrazia
No full textOggi non sembrano sussistere le condizioni necessarie per l’esercizio della capacità democratica di problem solving. I cittadini delle società democratiche si sono divisi in comunità epistemiche apparentemente incommensurabili. Questa situazione di antagonismo tra verità e politica è stata anticipata da Hannah Arendt, ma nemmeno lei aveva previsto l’emergere della politica di scetticismo radicale che si sta diffondendo con scarsa resistenza da parte delle istituzioni democratiche. Le discussioni sullo scetticismo radicale sono rimaste a lungo confinate all’interno dell’accademia. Tuttavia, negli ultimi anni una forma di scetticismo epistemologico radicale ha inaspettatamente guadagnato una posizione politica importante e potenzialmente catastrofica all’interno delle società democratiche. La perdita di fiducia nella capacità di soluzione dei problemi della democrazia è pervasiva e crescente, soprattutto a causa di due fenomeni: 1) l’incapacità delle società democratiche di rispondere all’accelerazione della catastrofe climatica e a tutte le sue allarmanti conseguenze sociali, politiche ed ecologiche; 2) l’incapacità di limitare e mitigare gli effetti distruttivi del capitalismo. Quando le democrazie arrivano a questo punto, devono “rompere le forme politiche esistenti” e creare un nuovo “pubblico” (Dewey). Il recupero della nostra fiducia nella democrazia dipende proprio dalla capacità di affrontare le sfide drammatiche cui siamo posti di fronte oggi
Changes in Heart Rate Variability During Immersive Multisensory Forest Bathing Experiences
No full textExposure to nature promotes relaxation and reduces stress, but accessibility concerns have led to increased investigation of virtual reality nature simulations, including “virtual forest bathing.” This study examines the effects of audiovisual (AV) and audio-visual-olfactory (AVO) immersive VR experiences on relaxation, quality of experience (QoE), and heart rate variability (HRV) among nurses in a mental health inpatient unit. Participants experienced 2.5-min sessions of 360° natural scenes with counterbalanced conditions. Both conditions (AV and AVO) showed improvements in relaxation and QoE ratings, while the AVO condition resulted in greater HRV changes towards the end of the experience, as well as greater correlations with subjective relaxation and QoE ratings
High spatial resolution PET detectors based on 10 mm × 10 mm linearly-graded SiPMs and 0.5 mm pitch LYSO arrays
No full textObjective. Position-sensitive silicon photomultipliers (PS-SiPMs) are promising photodetectors for ultra-high spatial resolution small-animal positron emission tomography (PET) scanners. This paper evaluated the performance of the latest generation of linearly-graded SiPMs (LG-SiPMs), a type of PS-SiPM, for ultra-high spatial resolution PET applications using LYSO arrays from two vendors.
Approach. Two dual-ended readout detectors were developed by coupling LG-SiPMs to both ends of the two LYSO arrays. Each LG-SiPM has an active area of 9.8 × 9.8 mm2. Both LYSO arrays consist of 20 × 20 arrays of 0.44 × 0.44 × 20 mm3polished LYSOs with a pitch of 0.5 mm. The performance of the two detectors was compared in terms of flood histogram, energy resolution, timing resolution, and depth-of-interaction (DOI) resolutions.
Main results. Flood histograms showed clear identification of all LYSO elements except for some edge crystals due to the larger size of the LYSO arrays compared to the active area of the LG-SiPMs and the misalignment between LG-SiPMs and LYSO arrays in the assembled detectors. At a bias voltage of 37.0 V, the detectors utilizing the Tianle LYSO array and EBO LYSO array provided energy resolutions of 17.5 ± 2.2 and 18.6 ± 2.0%, timing resolutions of 0.75 ± 0.03 and 0.78 ± 0.03 ns, and DOI resolutions of 2.16 ± 0.15 and 2.31 ± 0.12 mm, respectively.
Significance. The results presented in this paper demonstrate that the new generation LG-SiPMs are promising photodetectors for ultra-high spatial resolution small-animal PET scanner applications
Automatic digitalization of railway interlocking systems engineering drawings based on hybrid machine learning methods
No full textEngineering drawings of the railway interlocking systems come often from a legacy since the railway networks were built several years ago. Most of these drawings remained archived on handwritten sheets and need to be digitalized to continue updating and safety checks. This digitalization task is challenging as it requires major manual labor, and standard machine learning methods may not perform satisfactorily because drawings can be noisy and have poor sharpness. Considering these challenges, this paper proposes to solve this problem with a hybrid method that combines machine learning models, clustering techniques, computer vision, and ruled-based methods. A fine-tuned deep learning model is applied to identify symbols, labels, specifiers, and electrical connections. The lines representing electrical connections are determined using a combination of probabilistic Hough transform and clustering techniques. The identified letters are joined to create the labels by applying rule-based methods, and electrical connections are attached to symbols in a graph structure. A readable output is created for a drawing interface using the edges from the graph structure and the position of the detected objects. The method proposed in this paper can support the digitization of other engineering drawings assisting in solving the challenge of digitizing engineering schemes
Combination of searches for singly and doubly charged Higgs bosons produced via vector-boson fusion in proton–proton collisions at √s = 13 TeV with the ATLAS detector
No full textA combination of searches for singly and doubly charged Higgs bosons,
and
, produced via vector-boson fusion is performed using 140 fb−1 of proton–proton collisions at a centre-of-mass energy of 13 TeV, collected with the ATLAS detector during Run 2 of the Large Hadron Collider. Searches targeting decays to massive vector bosons in leptonic final states (electrons or muons) are considered. New constraints are reported on the production cross-section times branching fraction for charged Higgs boson masses between 200 GeV and 3000 GeV. The results are interpreted in the context of the Georgi-Machacek model for which the most stringent constraints to date are set for the masses considered in the combination