788 research outputs found
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
What has finite element analysis taught us about diabetic foot disease and its management?:a systematic review
Over the past two decades finite element (FE) analysis has become a popular tool for researchers seeking to simulate the biomechanics of the healthy and diabetic foot. The primary aims of these simulations have been to improve our understanding of the foot's complicated mechanical loading in health and disease and to inform interventions designed to prevent plantar ulceration, a major complication of diabetes. This article provides a systematic review and summary of the findings from FE analysis-based computational simulations of the diabetic foot.A systematic literature search was carried out and 31 relevant articles were identified covering three primary themes: methodological aspects relevant to modelling the diabetic foot; investigations of the pathomechanics of the diabetic foot; and simulation-based design of interventions to reduce ulceration risk.Methodological studies illustrated appropriate use of FE analysis for simulation of foot mechanics, incorporating nonlinear tissue mechanics, contact and rigid body movements. FE studies of pathomechanics have provided estimates of internal soft tissue stresses, and suggest that such stresses may often be considerably larger than those measured at the plantar surface and are proportionally greater in the diabetic foot compared to controls. FE analysis allowed evaluation of insole performance and development of new insole designs, footwear and corrective surgery to effectively provide intervention strategies. The technique also presents the opportunity to simulate the effect of changes associated with the diabetic foot on non-mechanical factors such as blood supply to local tissues.While significant advancement in diabetic foot research has been made possible by the use of FE analysis, translational utility of this powerful tool for routine clinical care at the patient level requires adoption of cost-effective (both in terms of labour and computation) and reliable approaches with clear clinical validity for decision making
Definition and evaluation of a finite element model of the human heel for diabetic foot ulcer prevention under shearing loads
Diabetic foot ulcers are triggered by mechanical loadings applied to the
surface of the plantar skin. Strain is considered to play a crucial role in
relation to ulcer etiology and can be assessed by Finite Element (FE)
modelling. A difficulty in the generation of these models is the choice of the
soft tissue material properties. In the literature, many studies attempt to
model the behavior of the heel soft tissues by implementing constitutive laws
that can differ significantly in terms of mechanical response. Moreover,
current FE models lack of proper evaluation techniques that could estimate
their ability to simulate realistic strains. In this article, we propose and
evaluate a FE model of the human heel for diabetic foot ulcer prevention. Soft
tissue constitutive laws are defined through the fitting of experimental
stretch-stress curves published in the literature. The model is then evaluated
through Digital Volume Correlation (DVC) based on non-rigid 3D Magnetic
Resonance Image Registration. The results from FE analysis and DVC show similar
strain locations in the fat pad and strain intensities according to the type of
applied loads. For additional comparisons, different sets of constitutive
models published in the literature are applied into the proposed FE mesh and
simulated with the same boundary conditions. In this case, the results in terms
of strains show great diversity in locations and intensities, suggesting that
more research should be developed to gain insight into the mechanical
properties of these tissues
Dynamic biomechanical modelling for foot ulcer prevention.
International audienceThis paper introduces a 3D Dynamic Finite Element biomechanical model of the human foot used for diabetic foot pressure ulcer prevention. The model estimates the internal strains and send an alert to the user in case of high strains values
Influence of the calcaneus shape on the risk of posterior heel ulcer using 3D patient-specific biomechanical modeling.
International audienceMost posterior heel ulcers are the consequence of inactivity and prolonged time lying down on the back. They appear when pressures applied on the heel create high internal strains and the soft tissues are compressed by the calcaneus. It is therefore important to monitor those strains to prevent heel pressure ulcers. Using a biomechanical lower leg model, we propose to estimate the influence of the patient-specific calcaneus shape on the strains within the foot and to determine if the risk of pressure ulceration is related to the variability of this shape. The biomechanical model is discretized using a 3D Finite Element mesh representing the soft tissues, separated into four domains implementing Neo Hookean materials with different elasticities: skin, fat, Achilles' tendon, and muscles. Bones are modelled as rigid bodies attached to the tissues. Simulations show that the shape of the calcaneus has an influence on the formation of pressure ulcers with a mean variation of the maximum strain over 6.0 percentage points over 18 distinct morphologies. Furthermore, the models confirm the influence of the cushion on which the leg is resting: a softer cushion leading to lower strains, it has less chances of creating a pressure ulcer. The methodology used for patient-specific strain estimation could be used for the prevention of heel ulcer when coupled with a pressure sensor
Biomechanics of pressure ulcer in body tissues interacting with external forces during locomotion
2009-2010 > Academic research: refereed > Publication in refereed journalAuthor’s OriginalPublishe
Clinical foot measurements as a proxy for plantar pressure testing in people with diabetes
Background: High plantar pressures are associated with increased foot ulcer risk in people with diabetes. Identification of high plantar pressures in people with diabetes is clinically challenging due to time and cost constraints of plantar pressure testing. Factors affecting foot biomechanics, including reduced joint range of motion and foot deformity, are implicated in the development of high plantar pressures and may provide a method to clinically identify those at risk of pressure related complications. The aim of this study was to investigate the contribution of joint range of motion and foot deformity measures on plantar pressures in a community dwelling group with diabetes. Methods: Barefoot (Tekscan HR Mat™) and in-shoe (Novel Pedar-X®) plantar pressure variables, weight bearing ankle dorsiflexion, hallux range of motion, lesser toe deformities and hallux abductus (HAV) scale were assessed in 136 adults with diabetes (52.2% male; mean age 68.4 years). Multivariate multiple linear regression was used to assess the effect of the four biomechanical factors plus neuropathy and body mass index on plantar pressure variables. Non-parametric bootstrapping was employed to determine the difference in plantar pressure variables for participants with two or more foot biomechanical pathologies compared to those with less than two pathologies. Results: Almost one third (32%) of the cohort had two or more foot biomechanical pathologies. Participants with two or more foot biomechanical pathologies displayed significant increases in all barefoot plantar pressure regions (except forefoot), compared to those with less than two pathologies. No significant changes were found for the in-shoe plantar pressure variables. The regression model explains between 9.9% (95%CI: 8.4 to 11.4%) and 29.6% (95% CI: 28.2 to 31%), and between 2.5% (1.0 to 4.0%) and 43.8% (95% CI: 42.5–44.9%), of the variance in the barefoot and in-shoe plantar pressure variables respectively. Conclusions: Participants presenting with two or more factors affecting foot biomechanics displayed higher peak pressures and pressure time integrals in all foot regions compared to those with less than two factors. The tests used in this study could help clinicians detect elevated plantar pressures in people with diabetes and present an opportunity for early preventative interventions
Plantar Overload Diagnostic Support System
Diabetes Mellitus (DM) is a chronic disease that impacts the quality of life of individuals of various age groups, being listed among the 10 leading causes of death in adults. Associated with this disease are diabetic foot ulcers, which cause a reduction in the patient's mobility, quality of life and even amputation of the affected limb. In order to prevent this situation, the study in question aims to develop a mobile application to monitor the patient's gait. The gait data will be collected from a sensorised insole with pressure, temperature, and humidity sensors, with its subsequent analysis and real-time provision of warnings if situations conducive to the formation of a foot ulcer are found. As this insole has not yet been developed, a second mobile application was created to send data replicating several phases of the human gait. In addition, a web application was developed for healthcare professionals, where they can access the patient's personal data as well as various types of statistics associated with their gait, helping the professional to make decisions regarding the improvements that can be made regarding the way the patient performs the gait. All applications were properly tested and proved to be responsive on different devices, environments, and operating system versions. Throughout the development process, it was possible to observe that they will help the healthcare professional to detect more easily patterns in the patient's gait and will alert the patient to the need to change the way he supports the foot, with the provision of information in real time. In order to continue this study, it is hoped in the future to link this system with a clinical record repository, to create a learning algorithm that can use other parameters besides the reading records to create alerts, and finally, it would be useful to develop the application for the IOS operating system.A Diabetes Mellitus (DM) é uma doença crónica que tem impacto na qualidade de vida de indivíduos de vários grupos etários, estando listada entre as 10 principais causas de morte em adultos. Associadas a esta doença, estão as úlceras do pé diabético, que causam uma redução da mobilidade do paciente, da qualidade de vida e até mesmo a amputação do membro afetado. Com o objetivo de prevenir esta situação, o estudo em questão visa desenvolver uma aplicação móvel para monitorizar a marcha do paciente. Os dados da marcha serão recolhidos a partir de uma palmilha sensorizada com sensores de pressão, temperatura e humidade, com a sua posterior análise, e fornecimento, em tempo real, de alertas no caso de serem encontradas situações propícias para a formação de uma úlcera no pé. Como esta palmilha ainda não foi desenvolvida, foi criada uma segunda aplicação móvel para enviar dados que replicam várias fases da marcha humana. Além disso, foi desenvolvida uma aplicação Web para profissionais de saúde, onde podem ter acesso aos dados pessoais do paciente, bem como vários tipos de estatísticas associadas à sua marcha, ajudando o profissional a tomar decisões relativamente às melhorias que podem ser feitas em relação à forma de como o paciente executa a marcha. Todas as aplicações foram devidamente testadas e mostraram-se responsivas em diferentes dispositivos, ambientes e versões de sistema operativo. Ao longo do processo de desenvolvimento, foi possível observar que estas ajudarão o profissional de saúde a detetar mais facilmente padrões na marcha do paciente, e alertarão o mesmo para a necessidade de mudar a forma como apoia o pé, com o fornecimento de informação em tempo real. De forma a dar continuidade a este estudo, espera-se no futuro interligar este sistema com um repositório de registos clínicos, criar um algoritmo de aprendizagem que possa utilizar outros parâmetros para além dos registos de leituras para criar alertas, e, finalmente, seria útil desenvolver a aplicação para o sistema operativo IOS
Classification of forefoot plantar pressure distribution in persons with diabetes : a novel perspective for the mechanical management of diabetic foot?
Background: The aim of this study was to identify groups of subjects with similar patterns of forefoot loading and verify if specific groups of patients with diabetes could be isolated from non-diabetics.
Methodology/Principal Findings: Ninety-seven patients with diabetes and 33 control participants between 45 and 70 years were prospectively recruited in two Belgian Diabetic Foot Clinics. Barefoot plantar pressure measurements were recorded and subsequently analysed using a semi-automatic total mapping technique. Kmeans cluster analysis was applied on relative regional impulses of six forefoot segments in order to pursue a classification for the control group separately, the diabetic group separately and both groups together. Cluster analysis led to identification of three distinct groups when considering only the control group. For the diabetic group, and the computation considering both groups together, four distinct groups were isolated. Compared to the cluster analysis of the control group an additional forefoot loading pattern was identified. This group comprised diabetic feet only. The relevance of the reported clusters was supported by ANOVA statistics indicating significant differences between different regions of interest and different clusters.
Conclusion/s Significance: There seems to emerge a new era in diabetic foot medicine which embraces the classification of diabetic patients according to their biomechanical profile. Classification of the plantar pressure distribution has the potential to provide a means to determine mechanical interventions for the prevention and/or treatment of the diabetic foot
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