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Marek Bucki

Publications and source records attributed to Marek Bucki.

14 recordsLinked to original sources
arXiv2026

Phase Separation in Heritage Objects Made of Plasticised PVC: the Case of Joseph Beuys Multiples

This work addresses the advanced degradation of plasticised PVC boards, which constitute Joseph Beuys multiples Phosphorus-Cross Sled, focusing on the mechanisms responsible for the extensive exudation of a viscous liquid. A multi-analytical approach combining chromatographic, spectroscopic, microscopic, and mechanical techniques was employed to characterise both the exuded surface layer and the polymer bulk, and to evaluate the consequences of degradation for long-term mechanical behaviour. The experimental results are supported by density functional theory simulations, which indicate a thermodynamic driving force for plasticiser migration towards the PVC surface and its tendency to self-associate. These molecular-level insights provide a mechanistic explanation for the observed migration and exudation phenomena. Overall, the study outlines a coherent deterioration pathway for exudate-covered plasticised PVC. The application of NMR spectroscopy proved to be an efficient method for studying accelerated migration of the plasticiser in PVC, opening the path to the development of non-destructive, in situ preventive conservation tools, supporting the early identification of PVC artefacts or parts of a collection that are at risk of severe phase separation.

cond-mat.mtrl-sci↗
arXiv2025

Effect of Accelerated Thermal Degradation of Poly(Vinyl Chloride): The Case of Unplasticized PVC

The thermal degradation of unplasticized poly(vinyl chloride), PVC, was comprehensively investigated through the application of spectroscopic techniques, as well as contact angle measurements (CA), dynamic mechanical analysis (DMA), and size-exclusion chromatography (SEC). To study the effect of relative humidity (RH) on the deterioration of unplasticized PVC, two regimes of accelerated degradation experiments were selected: low RH (max. 30% RH) and high RH = 60% levels, which corresponds to usually the highest RH in heritage institutions equipped with an HVAC system. Nuclear magnetic resonance (NMR) and infrared spectroscopy (FTIR) did not reveal any significant changes in the material during its degradation up to 20 weeks at temperatures ranging from 60{\deg}C to 80{\deg}C. Notable changes were observed in the Raman and UV-Vis spectra, indicative of the formation of conjugated carbon-carbon double bonds. The formation of polyenes was responsible for the yellowing of samples. Notwithstanding, the aforementioned changes did not lead to a notable decline in the mechanical properties, as evidenced by DMA and SEC measurements. EPR measurements demonstrated the formation of 2 radicals at 60{\deg}C, and in the sample degraded at 80{\deg}C the presence of radicals was evident. This indicates that a radical degradation mechanism cannot be excluded even at such low temperatures.

cond-mat.mtrl-sci↗
arXiv2024

Enhancing Biomechanical Simulations Based on A Posteriori Error Estimates: The Potential of Dual Weighted Residual-Driven Adaptive Mesh Refinement

The Finite Element Method (FEM) is a well-established procedure for computing approximate solutions to deterministic engineering problems described by partial differential equations. FEM produces discrete approximations of the solution with a discretisation error that can be an be quantified with \emph{a posteriori} error estimates. The practical relevance of error estimates for biomechanics problems, especially for soft tissue where the response is governed by large strains, is rarely addressed. In this contribution, we propose an implementation of \emph{a posteriori} error estimates targeting a user-defined quantity of interest, using the Dual Weighted Residual (DWR) technique tailored to biomechanics. The proposed method considers a general setting that encompasses three-dimensional geometries and model non-linearities, which appear in hyperelastic soft tissues. We take advantage of the automatic differentiation capabilities embedded in modern finite element software, which allows the error estimates to be computed generically for a large class of models and constitutive laws. First we validate our methodology using experimental measurements from silicone samples, and then illustrate its applicability for patient-specific computations of pressure ulcers on a human heel.

math.NA↗
arXiv2020

Biomechanical monitoring and machine learning for the detection of lying postures

Background: Pressure mapping technology has been adapted to monitor over prolonged periods to evaluate pressure ulcer risk in individuals during extended lying postures. However, temporal pressure distribution signals are not currently used to identify posture or mobility. The present study was designed to examine the potential of an automated approach for the detection of a range of static lying postures and corresponding transitions between postures.Methods: Healthy subjects (n = 19) adopted a range of sagittal and lateral lying postures. Parameters reflecting both the interactions at the support surface and body movements were continuously monitored. Subsequently, the derivative of each signal was examined to identify transitions between postures. Three machine learning algorithms, namely Na{ï}ve-Bayes, k-Nearest Neighbors and Support Vector Machine classifiers, were assessed to predict a range of static postures, established with a training model (n = 9) and validated with new input from test data (n = 10).Findings: Results showed that the derivative signals provided a means to detect transitions between postures, with actimetry providing the most distinct signal perturbations. The accuracy in predicting the range of postures from new test data ranged between 82%--100%, 70%--98% and 69%--100% for Na{ï}ve-Bayes, k-Nearest Neighbors and Support Vector Machine classifiers, respectively.Interpretation: The present study demonstrated that detection of both static postures and their corresponding transitions was achieved by combining machine learning algorithms with robust parameters from two monitoring systems. This approach has the potential to provide reliable indicators of posture and mobility, to support personalised pressure ulcer prevention strategies.

physics.med-ph↗
arXiv2018

Personalized modeling for real-time pressure ulcer prevention in sitting posture

, Ischial pressure ulcer is an important risk for every paraplegic person and a major public health issue. Pressure ulcers appear following excessive compression of buttock's soft tissues by bony structures, and particularly in ischial and sacral bones. Current prevention techniques are mainly based on daily skin inspection to spot red patches or injuries. Nevertheless, most pressure ulcers occur internally and are difficult to detect early. Estimating internal strains within soft tissues could help to evaluate the risk of pressure ulcer. A subject-specific biomechanical model could be used to assess internal strains from measured skin surface pressures. However, a realistic 3D non-linear Finite Element buttock model, with different layers of tissue materials for skin, fat and muscles, requires somewhere between minutes and hours to compute, therefore forbidding its use in a real-time daily prevention context. In this article, we propose to optimize these computations by using a reduced order modeling technique (ROM) based on proper orthogonal decompositions of the pressure and strain fields coupled with a machine learning method. ROM allows strains to be evaluated inside the model interactively (i.e. in less than a second) for any pressure field measured below the buttocks. In our case, with only 19 modes of variation of pressure patterns, an error divergence of one percent is observed compared to the full scale simulation for evaluating the strain field. This reduced model could therefore be the first step towards interactive pressure ulcer prevention in a daily setup. Highlights-Buttocks biomechanical modelling,-Reduced order model,-Daily pressure ulcer prevention.

physics.med-ph↗
arXiv2018

Quantifying discretization errors for soft-tissue simulation in computer assisted surgery: a preliminary study

Errors in biomechanics simulations arise from modeling and discretization. Modeling errors are due to the choice of the mathematical model whilst discretization errors measure the impact of the choice of the numerical method on the accuracy of the approximated solution to this specific mathematical model. A major source of discretization errors is mesh generation from medical images, that remains one of the major bottlenecks in the development of reliable, accurate, automatic and efficient personalized, clinically-relevant Finite Element (FE) models in biomechanics. The impact of mesh quality and density on the accuracy of the FE solution can be quantified with \emph{a posteriori} error estimates. Yet, to our knowledge, the relevance of such error estimates for practical biomechanics problems has seldom been addressed, see [25]. In this contribution, we propose an implementation of some a posteriori error estimates to quantify the discretization errors and to optimize the mesh. More precisely, we focus on error estimation for a user-defined quantity of interest with the Dual Weighted Residual (DWR) technique. We test its applicability and relevance in two situations, corresponding to computations for a tongue and an artery, using a simplified setting, i.e., plane linearized elasticity with contractility of the soft-tissue modeled as a pre-stress. Our results demonstrate the feasibility of such methodology to estimate the actual solution errors and to reduce them economically through mesh refinement.

cs.CE↗
arXiv2014

Smart Diabetic Socks: Embedded device for diabetic foot prevention

1) Objectives Most foot ulcers are the consequence of a trauma (repetitive high stress, ill-fitting footwear, or an object inside the shoe) associated to diabetes. They are often followed by amputation and shorten life expectancy. This paper describes the prototype of the Smart Diabetic Socks that has been developed in the context of the French ANR TecSan project. The objective is to prevent pressure foot ulcers for diabetic persons. 2) Material and methods A fully wireless, customizable and washable "smart sock" has been designed. It is made of a textile which fibers are knitted in a way they provide measurements of the pressure exerted under and all around the foot in real-life conditions. This device is coupled with a subject-specific Finite Element foot model that simulates the internal strains within the soft tissues of the foot. 3) Results A number of derived stress indicators can be computed based on that analysis, such as the accumulated stress dose, high internal strains or peak pressures near bony prominences during gait. In case of risks for pressure ulcer, an alert is sent to the person and/or to the clinician. A watch, a smart-phone or a distant laptop can be used for providing such alert.

physics.med-ph↗
arXiv2011

Using a smart phone for information rendering in Computer-Aided Surgery

Computer-aided surgery intensively uses the concept of navigation: after having collected CT data from a patient and transferred them to the operating room coordinate system, the surgical instrument (a puncture needle for instance) is localized and its position is visualized with respect to the patient organs which are not directly visible. This approach is very similar to the GPS paradigm. Traditionally, three orthogonal slices in the patient data are presented on a distant screen. Sometimes a 3D representation is also added. In this study we evaluated the potential of adding a smart phone as a man-machine interaction device. Different experiments involving operators puncturing a phantom are reported in this paper.

cs.HC↗
arXiv2010

A fast and robust patient specific Finite Element mesh registration technique: application to 60 clinical cases

Finite Element mesh generation remains an important issue for patient specific biomechanical modeling. While some techniques make automatic mesh generation possible, in most cases, manual mesh generation is preferred for better control over the sub-domain representation, element type, layout and refinement that it provides. Yet, this option is time consuming and not suited for intraoperative situations where model generation and computation time is critical. To overcome this problem we propose a fast and automatic mesh generation technique based on the elastic registration of a generic mesh to the specific target organ in conjunction with element regularity and quality correction. This Mesh-Match-and-Repair (MMRep) approach combines control over the mesh structure along with fast and robust meshing capabilities, even in situations where only partial organ geometry is available. The technique was successfully tested on a database of 5 pre-operatively acquired complete femora CT scans, 5 femoral heads partially digitized at intraoperative stage, and 50 CT volumes of patients' heads. The MMRep algorithm succeeded in all 60 cases, yielding for each patient a hex-dominant, Atlas based, Finite Element mesh with submillimetric surface representation accuracy, directly exploitable within a commercial FE software.

physics.med-ph↗
arXiv2007

Techniques on mesh generation for the brain shift simulation

Neurosurgery interventions involve complex tracking systems because a tissue deformation takesplace. The neuronavigation system relies only on preoperative images. In order to overcome the soft tissue deformations and guarantee the accuracy of the navigation a biomechanical model can be used during surgery to simulate the deformation of the brain. Therefore, a mesh generation for an optimal real-time Finite Element Model (FEM) becomes crucial. In this work we present different alternatives from a meshgeneration point of view that were evaluated to optimize the process in terms of elements quantity and quality as well as constraints of a intraoperative application and patient specific data.

physics.med-ph↗
arXiv2007

Framework for a low-cost intra-operative image-guided neuronavigator including brain shift compensation

In this paper we present a methodology to address the problem of brain tissue deformation referred to as 'brain-shift'. This deformation occurs throughout a neurosurgery intervention and strongly alters the accuracy of the neuronavigation systems used to date in clinical routine which rely solely on pre-operative patient imaging to locate the surgical target, such as a tumour or a functional area. After a general description of the framework of our intra-operative image-guided system, we describe a procedure to generate patient specific finite element meshes of the brain and propose a biomechanical model which can take into account tissue deformations and surgical procedures that modify the brain structure, like tumour or tissue resection.

physics.med-ph↗
arXiv2007

Bio-Mechanical Model of the Brain for a Per-Operative Image-Guided Neuronavigator Compensating for "Brain-Shift" Deformations

In this paper we present a methodology to address the problem of brain tissue deformation referred to as 'brain-shift'. This deformation occurs throughout a neurosurgery intervention and strongly alters the accuracy of the neuronavigation systems used to date in clinical routine which rely solely on pre-operative patient imaging to locate the surgical target, such as a tumour or a functional area. After a general description of the framework of our intra-operative image-guided system, we describe a procedure to generate patient specific finite element meshes of the brain and propose a biomechanical model which can take into account tissue deformations and surgical procedures that modify the brain structure, like tumour or tissue resection.

physics.med-ph↗
arXiv2006

Framework and Bio-Mechanical Model for a Per-Operative Image-Guided Neuronavigator Including 'Brain-Shift' Compensation

In this paper we present a methodology to adress the problem of brain tissue deformation referred to as "brainshift". This deformation occurs throughout a neurosurgery intervention and strongly alters the accuracy of the neuronavigation systems used to date in clinical routine which rely solely on preoperative patient imaging to locate the surgical target, such as a tumour or a functional area. After a general description of the framework of our intraoperative image-guided system, we propose a biomechanical model of the brain which can take into account interactively such deformations as well as surgical procedures that modify the brain structure, like tumour or tissue resection.

physics.med-ph↗
arXiv2006

Automatic finite elements mesh generation from planar contours of the brain: an image driven 'blobby' approach

In this paper, we address the problem of automatic mesh generation for finite elements modeling of anatomical organs for which a volumetric data set is available. In the first step a set of characteristic outlines of the organ is defined manually or automatically within the volume. The outlines define the "key frames" that will guide the procedure of surface reconstruction. Then, based on this information, and along with organ surface curvature information extracted from the volume data, a 3D scalar field is generated. This field allows a 3D reconstruction of the organ: as an iso-surface model, using a marching cubes algorithm; or as a 3D mesh, using a grid "immersion" technique, the field value being used as the outside/inside test. The final reconstruction respects the various topological changes that occur within the organ, such as holes and branching elements.

physics.med-ph↗