Economics of dialysis dependence following renal replacement therapy for critically ill acute kidney injury patients.

BACKGROUND: The obective of this study was to perform a cost-effectiveness analysis comparing intermittent with continuous renal replacement therapy (IRRT versus CRRT) as initial therapy for acute kidney injury (AKI) in the intensive care unit (ICU). METHODS: Assuming some patients would potentially be eligible for either modality, we modeled life year gained, the quality-adjusted life years (QALYs) and healthcare costs for a cohort of 1000 IRRT patients and a cohort of 1000 CRRT patients. We used a 1-year, 5-year and a lifetime horizon. A Markov model with two health states for AKI survivors was designed: dialysis dependence and dialysis independence. We applied Weibull regression from published estimates to fit survival curves for CRRT and IRRT patients and to fit the proportion of dialysis dependence among CRRT and IRRT survivors. We then applied a risk ratio reported in a large retrospective cohort study to the fitted CRRT estimates in order to determine the proportion of dialysis dependence for IRRT survivors. We conducted sensitivity analyses based on a range of differences for daily implementation cost between CRRT and IRRT (base case: CRRT day $632 more expensive than IRRT day; range from $200 to $1000) and a range of risk ratios for dialysis dependence for CRRT as compared with IRRT (from 0.65 to 0.95; base case: 0.80). RESULTS: Continuous renal replacement therapy was associated with a marginally greater gain in QALY as compared with IRRT (1.093 versus 1.078). Despite higher upfront costs for CRRT in the ICU ($4046 for CRRT versus $1423 for IRRT in average), the 5-year total cost including the cost of dialysis dependence was lower for CRRT ($37 780 for CRRT versus $39 448 for IRRT on average). The base case incremental cost-effectiveness analysis showed that CRRT dominated IRRT. This dominance was confirmed by extensive sensitivity analysis. CONCLUSIONS: Initial CRRT is cost-effective compared with initial IRRT by reducing the rate of long-term dialysis dependence among critically ill AKI survivors.

High-throughput SELEX SAGE method for quantitative modeling of transcription-factor binding sites.

The ability to determine the location and relative strength of all transcription-factor binding sites in a genome is important both for a comprehensive understanding of gene regulation and for effective promoter engineering in biotechnological applications. Here we present a bioinformatically driven experimental method to accurately define the DNA-binding sequence specificity of transcription factors. A generalized profile was used as a predictive quantitative model for binding sites, and its parameters were estimated from in vitro-selected ligands using standard hidden Markov model training algorithms. Computer simulations showed that several thousand low- to medium-affinity sequences are required to generate a profile of desired accuracy. To produce data on this scale, we applied high-throughput genomics methods to the biochemical problem addressed here. A method combining systematic evolution of ligands by exponential enrichment (SELEX) and serial analysis of gene expression (SAGE) protocols was coupled to an automated quality-controlled sequence extraction procedure based on Phred quality scores. This allowed the sequencing of a database of more than 10,000 potential DNA ligands for the CTF/NFI transcription factor. The resulting binding-site model defines the sequence specificity of this protein with a high degree of accuracy not achieved earlier and thereby makes it possible to identify previously unknown regulatory sequences in genomic DNA. A covariance analysis of the selected sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism.

Evaluation of Iowa's Driver Improvement Program, 2009

This study examines the effectiveness of Iowa’s Driver Improvement Program (DIP), measured as the reduction in the number of driver convictions subsequent to the DIP. The analysis involved a random sample of 9,055 drivers who had been instructed to attend DIP and corresponding data on driver convictions, crashes, and driver education training history that were provided by the Iowa Motor Vehicle Division. The sample was divided into two groups based on DIP outcome: satisfactory or unsatisfactory completion. Two evaluation periods were considered: one year after the DIP date (probation period) and the period from the 13th to 18th month after the DIP date. The evaluation of Iowa’s DIP showed that there is evidence of effectiveness in terms of reducing driver convictions subsequent to attending the DIP. Among the 6,790 (75%) drivers who completed the course satisfactorily, 73% of drivers had no actions and 93% were not involved in a crash during the probation period. Statistical tests confirmed these numbers. However, the positive effect of satisfactory completion of DIP on survival time (that is, the time until the first conviction) was not statistically significant 13 months after the DIP date. Econometric model estimation results showed that, regardless of the DIP outcome, the likelihood of conviction occurrence and frequency of subsequent convictions depends on other factors, such as age, driver history, and DIP location, and interaction effects among these factors. Low-cost, early intervention measures are suggested to enhance the effectiveness of Iowa’s DIP. These measures can include advisory and warning letters (customized based on the driver’s age) sent within the first year after the DIP date and soon after the end of the probation period, as well as a closer examination of DIP instruction across the 17 community colleges that host the program. Given the large number of suspended drivers who continued to drive, consideration should also be given to measures to reduce driving while suspended offenses.

Economic evaluation of the levonorgestrel-releasing intrauterine system for the treatment of dysfunctional uterine bleeding in Spain

To compare the cost and effectiveness of the levonorgestrel-releasing intrauterine system (LNG-IUS) versus combined oral contraception (COC) and progestogens (PROG) in first-line treatment of dysfunctional uterine bleeding (DUB) in Spain. STUDY DESIGN: A cost-effectiveness and cost-utility analysis of LNG-IUS, COC and PROG was carried out using a Markov model based on clinical data from the literature and expert opinion. The population studied were women with a previous diagnosis of idiopathic heavy menstrual bleeding. The analysis was performed from the National Health System perspective, discounting both costs and future effects at 3%. In addition, a sensitivity analysis (univariate and probabilistic) was conducted. RESULTS: The results show that the greater efficacy of LNG-IUS translates into a gain of 1.92 and 3.89 symptom-free months (SFM) after six months of treatment versus COC and PROG, respectively (which represents an increase of 33% and 60% of symptom-free time). Regarding costs, LNG-IUS produces savings of 174.2-309.95 and 230.54-577.61 versus COC and PROG, respectively, after 6 months-5 years. Apart from cost savings and gains in SFM, quality-adjusted life months (QALM) are also favourable to LNG-IUS in all scenarios, with a range of gains between 1 and 2 QALM compared to COC and PROG. CONCLUSIONS: The results indicate that first-line use of the LNG-IUS is the dominant therapeutic option (less costly and more effective) in comparison with first-line use of COC or PROG for the treatment of DUB in Spain. LNG-IUS as first line is also the option that provides greatest health-related quality of life to patients.

Quantitative modelling of transcription factor binding sites

Abstract One of the most important issues in molecular biology is to understand regulatory mechanisms that control gene expression. Gene expression is often regulated by proteins, called transcription factors which bind to short (5 to 20 base pairs),degenerate segments of DNA. Experimental efforts towards understanding the sequence specificity of transcription factors is laborious and expensive, but can be substantially accelerated with the use of computational predictions. This thesis describes the use of algorithms and resources for transcriptionfactor binding site analysis in addressing quantitative modelling, where probabilitic models are built to represent binding properties of a transcription factor and can be used to find new functional binding sites in genomes. Initially, an open-access database(HTPSELEX) was created, holding high quality binding sequences for two eukaryotic families of transcription factors namely CTF/NF1 and LEFT/TCF. The binding sequences were elucidated using a recently described experimental procedure called HTP-SELEX, that allows generation of large number (> 1000) of binding sites using mass sequencing technology. For each HTP-SELEX experiments we also provide accurate primary experimental information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, and assembled clone sequences of binding sequences. The database also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols.The database is available at http://wwwisrec.isb-sib.ch/htpselex/ and and ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex. The Expectation-Maximisation(EM) algorithm is one the frequently used methods to estimate probabilistic models to represent the sequence specificity of transcription factors. We present computer simulations in order to estimate the precision of EM estimated models as a function of data set parameters(like length of initial sequences, number of initial sequences, percentage of nonbinding sequences). We observed a remarkable robustness of the EM algorithm with regard to length of training sequences and the degree of contamination. The HTPSELEX database and the benchmarked results of the EM algorithm formed part of the foundation for the subsequent project, where a statistical framework called hidden Markov model has been developed to represent sequence specificity of the transcription factors CTF/NF1 and LEF1/TCF using the HTP-SELEX experiment data. The hidden Markov model framework is capable of both predicting and classifying CTF/NF1 and LEF1/TCF binding sites. A covariance analysis of the binding sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism. We next tested the LEF1/TCF model by computing binding scores for a set of LEF1/TCF binding sequences for which relative affinities were determined experimentally using non-linear regression. The predicted and experimentally determined binding affinities were in good correlation.

Economic evaluation of the levonorgestrel-releasing intrauterine system for the treatment of dysfunctional uterine bleeding in Spain

To compare the cost and effectiveness of the levonorgestrel-releasing intrauterine system (LNG-IUS) versus combined oral contraception (COC) and progestogens (PROG) in first-line treatment of dysfunctional uterine bleeding (DUB) in Spain. STUDY DESIGN: A cost-effectiveness and cost-utility analysis of LNG-IUS, COC and PROG was carried out using a Markov model based on clinical data from the literature and expert opinion. The population studied were women with a previous diagnosis of idiopathic heavy menstrual bleeding. The analysis was performed from the National Health System perspective, discounting both costs and future effects at 3%. In addition, a sensitivity analysis (univariate and probabilistic) was conducted. RESULTS: The results show that the greater efficacy of LNG-IUS translates into a gain of 1.92 and 3.89 symptom-free months (SFM) after six months of treatment versus COC and PROG, respectively (which represents an increase of 33% and 60% of symptom-free time). Regarding costs, LNG-IUS produces savings of 174.2-309.95 and 230.54-577.61 versus COC and PROG, respectively, after 6 months-5 years. Apart from cost savings and gains in SFM, quality-adjusted life months (QALM) are also favourable to LNG-IUS in all scenarios, with a range of gains between 1 and 2 QALM compared to COC and PROG. CONCLUSIONS: The results indicate that first-line use of the LNG-IUS is the dominant therapeutic option (less costly and more effective) in comparison with first-line use of COC or PROG for the treatment of DUB in Spain. LNG-IUS as first line is also the option that provides greatest health-related quality of life to patients.

Coev-web: a web platform designed to simulate and evaluate coevolving positions along a phylogenetic tree.

BACKGROUND: Available methods to simulate nucleotide or amino acid data typically use Markov models to simulate each position independently. These approaches are not appropriate to assess the performance of combinatorial and probabilistic methods that look for coevolving positions in nucleotide or amino acid sequences. RESULTS: We have developed a web-based platform that gives a user-friendly access to two phylogenetic-based methods implementing the Coev model: the evaluation of coevolving scores and the simulation of coevolving positions. We have also extended the capabilities of the Coev model to allow for the generalization of the alphabet used in the Markov model, which can now analyse both nucleotide and amino acid data sets. The simulation of coevolving positions is novel and builds upon the developments of the Coev model. It allows user to simulate pairs of dependent nucleotide or amino acid positions. CONCLUSIONS: The main focus of our paper is the new simulation method we present for coevolving positions. The implementation of this method is embedded within the web platform Coev-web that is freely accessible at http://coev.vital-it.ch/, and was tested in most modern web browsers.

Cost-effectiveness analysis of cardiac resynchronization therapy in patients with NYHA I and NYHA II heart failure in Spain

Objectives: The aim of the study was to combine clinical results from the European Cohort of the REVERSE study and costs associated with the addition of cardiac resynchronization therapy (CRT) to optimal medical therapy (OMT) in patients with mild symptomatic (NYHA I-II) or asymptomatic left ventricular dysfunction and markers of cardiac dyssynchrony in Spain. Methods: A Markov model was developed with CRT + OMT (CRT-ON) versus OMT only (CRT-OFF) based on a retrospective cost-effectiveness analysis. Raw data was derived from literature and expert opinion, reflecting clinical and economic consequences of patient"s management in Spain. Time horizon was 10 years. Both costs (euro 2010) and effects were discounted at 3 percent per annum. Results: CRT-ON showed higher total costs than CRT-OFF; however, CRT reduced the length of hospitalization in ICU by 94 percent (0.006 versus 0.091 days) and general ward in by 34 percent (0.705 versus 1.076 days). Surviving CRT-ON patients (88.2 percent versus 77.5 percent) remained in better functional class longer, and they achieved an improvement of 0.9 life years (LYGs) and 0.77 years quality-adjusted life years (QALYs). CRT-ON proved to be cost-effective after 6 years, except for the 7th year due to battery depletion. At 10 years, the results were 18,431 per LYG and 21,500 per QALY gained. Probabilistic sensitivity analysis showed CRT-ON was cost-effective in 75.4 percent of the cases at 10 years. Conclusions: The use of CRT added to OMT represents an efficient use of resources in patients suffering from heart failure in NYHA functional classes I and II.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

DYNAMICS AND PREDICTION OF DIAMETRIC STRUCTURE IN TWO ATLANTIC FOREST FRAGMENTS IN NORTHEASTERN BRAZIL

ABSTRACT Monitoring analyses aim to understand the processes that drive changes in forest structure and, along with prediction studies, may assist in the management planning and conservation of forest remnants. The objective of this study was to analyze the forest dynamics in two Atlantic rainforest fragments in Pernambuco, Brazil, and to predict their future forest diameter structure using the Markov chain model. We used continuous forest inventory data from three surveys in two forest fragments of 87 ha (F1) and 388 ha (F2). We calculated the annual rates of mortality and recruitment, the mean annual increment, and the basal area for each of the 3-year periods. Data from the first and second surveys were used to project the third inventory measurements, which were compared to the observed values in the permanent plots using chi-squared tests (a = 0.05). In F1, a decrease in the number of individuals was observed due to mortality rates being higher than recruitment rates; however, there was an increase in the basal area. In this fragment, the fit to the Markov model was adequate. In F2, there was an increase in both the basal area and the number of individuals during the 6-year period due to the recruitment rate exceeding the mortality rate. For this fragment, the fit of the model was unacceptable. Hence, for the studied fragments, the demographic rates influenced the stem density more than the floristic composition. Yet, even with these intense dynamics, both fragments showed active growth.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Évaluation de l'impact clinique et économique du développement d'un traitement pour la schizophrénie

Contexte : Les stratégies pharmacologiques pour traiter la schizophrénie reçoivent une attention croissante due au développement de nouvelles pharmacothérapies plus efficaces, mieux tolérées mais plus coûteuses. La schizophrénie est une maladie chronique présentant différents états spécifiques et définis par leur sévérité. Objectifs : Ce programme de recherche vise à: 1) Évaluer les facteurs associés au risque d'être dans un état spécifique de la schizophrénie, afin de construire les fonctions de risque de la modélisation du cours naturel de la schizophrénie; 2) Développer et valider un modèle de Markov avec microsimulations de Monte-Carlo, afin de simuler l'évolution naturelle des patients qui sont nouvellement diagnostiqués pour la schizophrénie, en fonction du profil individuel des facteurs de risque; 3) Estimer le coût direct de la schizophrénie (pour les soins de santé et autres non reliés aux soins de santé) dans la perspective gouvernementale et simuler l’impact clinique et économique du développement d’un traitement dans une cohorte de patients nouvellement diagnostiqués avec la schizophrénie, suivis pendant les cinq premières années post-diagnostic. Méthode : Pour le premier objectif de ce programme de recherche, un total de 14 320 patients nouvellement diagnostiqués avec la schizophrénie ont été identifiés dans les bases de données de la RAMQ et de Med-Echo. Les six états spécifiques de la schizophrénie ont été définis : le premier épisode (FE), l'état de dépendance faible (LDS), l’état de dépendance élevée (HDS), l’état stable (Stable), l’état de bien-être (Well) et l'état de décès (Death). Pour évaluer les facteurs associés au risque de se trouver dans chacun des états spécifiques de la schizophrénie, nous avons construit 4 fonctions de risque en se basant sur l'analyse de risque proportionnel de Cox pour des risques compétitifs. Pour le deuxième objectif, nous avons élaboré et validé un modèle de Markov avec microsimulations de Monte-Carlo intégrant les six états spécifiques de la schizophrénie. Dans le modèle, chaque sujet avait ses propres probabilités de transition entre les états spécifiques de la schizophrénie. Ces probabilités ont été estimées en utilisant la méthode de la fonction d'incidence cumulée. Pour le troisième objectif, nous avons utilisé le modèle de Markov développé précédemment. Ce modèle inclut les coûts directs de soins de santé, estimés en utilisant les bases de données de la Régie de l'assurance maladie du Québec et Med-Echo, et les coûts directs autres que pour les soins de santé, estimés à partir des enquêtes et publications de Statistique Canada. Résultats : Un total de 14 320 personnes nouvellement diagnostiquées avec la schizophrénie ont été identifiées dans la cohorte à l'étude. Le suivi moyen des sujets était de 4,4 (± 2,6) ans. Parmi les facteurs associés à l’évolution de la schizophrénie, on peut énumérer l’âge, le sexe, le traitement pour la schizophrénie et les comorbidités. Après une période de cinq ans, nos résultats montrent que 41% des patients seront considérés guéris, 13% seront dans un état stable et 3,4% seront décédés. Au cours des 5 premières années après le diagnostic de schizophrénie, le coût direct moyen de soins de santé et autres que les soins de santé a été estimé à 36 701 $ canadiens (CAN) (95% CI: 36 264-37 138). Le coût des soins de santé a représenté 56,2% du coût direct, le coût de l'aide sociale 34,6% et le coût associé à l’institutionnalisation dans les établissements de soins de longue durée 9,2%. Si un nouveau traitement était disponible et offrait une augmentation de 20% de l'efficacité thérapeutique, le coût direct des soins de santé et autres que les soins de santé pourrait être réduit jusqu’à 14,2%. Conclusion : Nous avons identifié des facteurs associés à l’évolution de la schizophrénie. Le modèle de Markov que nous avons développé est le premier modèle canadien intégrant des probabilités de transition ajustées pour le profil individuel des facteurs de risque, en utilisant des données réelles. Le modèle montre une bonne validité interne et externe. Nos résultats indiquent qu’un nouveau traitement pourrait éventuellement réduire les hospitalisations et le coût associé aux établissements de soins de longue durée, augmenter les chances des patients de retourner sur le marché du travail et ainsi contribuer à la réduction du coût de l'aide sociale.

Modélisation de l'espérance de vie des clients en assurance

Dans ce mémoire, nous proposons une méthodologie statistique permettant d’obtenir un estimateur de l’espérance de vie des clients en assurance. Les prédictions effectuées tiennent compte des caractéristiques individuelles des clients, notamment du fait qu’ils peuvent détenir différents types de produits d’assurance (automobile, résidentielle ou les deux). Trois approches sont comparées. La première approche est le modèle de Markov simple, qui suppose à la fois l’homogénéité et la stationnarité des probabilités de transition. L’autre modèle – qui a été implémenté par deux approches, soit une approche directe et une approche par simulations – tient compte de l’hétérogénéité des probabilités de transition, ce qui permet d’effectuer des prédictions qui évoluent avec les caractéristiques des individus dans le temps. Les probabilités de transition de ce modèle sont estimées par des régressions logistiques multinomiales.

Stratégie de vaccination familiale contre la coqueluche (méthode de cocooning) à la maternité : analyse coût-efficacité d'un programme provincial

Le manuscrit constituant l'annexe 1 a été publié en décembre 2013 sous la référence : Vaccine. 2013 Dec 9;31(51):6087-91.

Video-based analysis of Gait pathologies

L’analyse de la marche a émergé comme l’un des domaines médicaux le plus im- portants récemment. Les systèmes à base de marqueurs sont les méthodes les plus fa- vorisées par l’évaluation du mouvement humain et l’analyse de la marche, cependant, ces systèmes nécessitent des équipements et de l’expertise spécifiques et sont lourds, coûteux et difficiles à utiliser. De nombreuses approches récentes basées sur la vision par ordinateur ont été développées pour réduire le coût des systèmes de capture de mou- vement tout en assurant un résultat de haute précision. Dans cette thèse, nous présentons notre nouveau système d’analyse de la démarche à faible coût, qui est composé de deux caméras vidéo monoculaire placées sur le côté gauche et droit d’un tapis roulant. Chaque modèle 2D de la moitié du squelette humain est reconstruit à partir de chaque vue sur la base de la segmentation dynamique de la couleur, l’analyse de la marche est alors effectuée sur ces deux modèles. La validation avec l’état de l’art basée sur la vision du système de capture de mouvement (en utilisant le Microsoft Kinect) et la réalité du ter- rain (avec des marqueurs) a été faite pour démontrer la robustesse et l’efficacité de notre système. L’erreur moyenne de l’estimation du modèle de squelette humain par rapport à la réalité du terrain entre notre méthode vs Kinect est très prometteur: les joints des angles de cuisses (6,29◦ contre 9,68◦), jambes (7,68◦ contre 11,47◦), pieds (6,14◦ contre 13,63◦), la longueur de la foulée (6.14cm rapport de 13.63cm) sont meilleurs et plus stables que ceux de la Kinect, alors que le système peut maintenir une précision assez proche de la Kinect pour les bras (7,29◦ contre 6,12◦), les bras inférieurs (8,33◦ contre 8,04◦), et le torse (8,69◦contre 6,47◦). Basé sur le modèle de squelette obtenu par chaque méthode, nous avons réalisé une étude de symétrie sur différentes articulations (coude, genou et cheville) en utilisant chaque méthode sur trois sujets différents pour voir quelle méthode permet de distinguer plus efficacement la caractéristique symétrie / asymétrie de la marche. Dans notre test, notre système a un angle de genou au maximum de 8,97◦ et 13,86◦ pour des promenades normale et asymétrique respectivement, tandis que la Kinect a donné 10,58◦et 11,94◦. Par rapport à la réalité de terrain, 7,64◦et 14,34◦, notre système a montré une plus grande précision et pouvoir discriminant entre les deux cas.