Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Detecting an abnormality in a recovery boiler using dynamic multivariate data analysis with parallel coordinate plots

Data visualization techniques are powerful in the handling and analysis of multivariate systems. One such technique known as parallel coordinates was used to support the diagnosis of an event, detected by a neural network-based monitoring system, in a boiler at a Brazilian Kraft pulp mill. Its attractiveness is the possibility of the visualization of several variables simultaneously. The diagnostic procedure was carried out step-by-step going through exploratory, explanatory, confirmatory, and communicative goals. This tool allowed the visualization of the boiler dynamics in an easier way, compared to commonly used univariate trend plots. In addition it facilitated analysis of other aspects, namely relationships among process variables, distinct modes of operation and discrepant data. The whole analysis revealed firstly that the period involving the detected event was associated with a transition between two distinct normal modes of operation, and secondly the presence of unusual changes in process variables at this time.

Use of Demonstrably Effective Therapies in the Treatment of Acute Coronary Syndromes: Comparison between Different Brazilian Regions. Analysis of the Brazilian Registry on Acute Coronary Syndromes (BRACE)

Background: Little is known in our country about regional differences in the treatment of acute coronary disease. Objective: To analyze the behavior regarding the use of demonstrably effective regional therapies in acute coronary disease. Methods: A total of 71 hospitals were randomly selected, respecting the proportionality of the country in relation to geographic location, among other criteria. In the overall population was regionally analyzed the use of aspirin, clopidogrel, ACE inhibitors / AT1 blocker, beta-blockers and statins, separately and grouped by individual score ranging from 0 (no drug used) to 100 (all drugs used). In myocardial infarction with ST elevation (STEMI) regional differences were analyzed regarding the use of therapeutic recanalization (fibrinolytics and primary angioplasty). Results: In the overall population, within the first 24 hours of hospitalization, the mean score in the North-Northeast (70.5 +/- 22.1) was lower (p < 0.05) than in the Southeast (77.7 +/- 29.5), Midwest (82 +/- 22.1) and South (82.4 +/- 21) regions. At hospital discharge, the score of the North-Northeast region (61.4 +/- 32.9) was lower (p < 0.05) than in the Southeast (69.2 +/- 31.6), Midwest (65.3 +/- 33.6) and South (73.7 +/- 28.1) regions; additionally, the score of the Midwest was lower (p < 0.05) than the South region. In STEMI, the use of recanalization therapies was highest in the Southeast (75.4%, p = 0.001 compared to the rest of the country), and lowest in the North-Northeast (52.5%, p < 0.001 compared to the rest of the country). Conclusion: The use of demonstrably effective therapies in the treatment of acute coronary disease is much to be desired in the country, with important regional differences.

Analysis of kinematic, kinetic and electromyographic patterns during root canal preparation with rotary and manual instruments

Objective: This study assessed the muscular activity during root canal preparation through kinematics, kinetics, and electromyography (EMG). Material and Methods: The operators prepared one canal with RaCe rotary instruments and another with Flexofiles. The kinematics of the major joints was reconstructed using an optoelectronic system and electromyographic responses of the flexor carpi radial's, extensor carpi radialis, brachioradialis, biceps brachii, triceps brachii, middle deltoid, and upper trapezius were recorded. The joint torques of the shoulder, elbow and wrist were calculated using inverse dynamics. In the kinematic analysis, angular movements of the wrist and elbow were classified as low risk factors for work-related musculoskeletal disorders. With respect to the shoulder, the classification was medium-risk. Results: There was no significant difference revealed by the kinetic reports. The EMG results showed that for the middle deltoid and upper trapezius the rotary instrumentation elicited higher values. The flexor carpi radialis and extensor carpi radialis, as well as the brachioradialis showed a higher value with the manual method. Conclusion: The muscular recruitment for accomplishment of articular movements for root canal preparation with either the rotary or manual techniques is distinct. Nevertheless, the rotary instrument presented less difficulty in the generation of the joint torque in each articulation, thus, presenting a greater uniformity of joint torques.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

Functional coupling of sensorimotor and associative areas during a catching ball task: a qEEG coherence study

Abstract Background Catching an object is a complex movement that involves not only programming but also effective motor coordination. Such behavior is related to the activation and recruitment of cortical regions that participates in the sensorimotor integration process. This study aimed to elucidate the cortical mechanisms involved in anticipatory actions when performing a task of catching an object in free fall. Methods Quantitative electroencephalography (qEEG) was recorded using a 20-channel EEG system in 20 healthy right-handed participants performed the catching ball task. We used the EEG coherence analysis to investigate subdivisions of alpha (8-12 Hz) and beta (12-30 Hz) bands, which are related to cognitive processing and sensory-motor integration. Results Notwithstanding, we found the main effects for the factor block; for alpha-1, coherence decreased from the first to sixth block, and the opposite effect occurred for alpha-2 and beta-2, with coherence increasing along the blocks. Conclusion It was concluded that to perform successfully our task, which involved anticipatory processes (i.e. feedback mechanisms), subjects exhibited a great involvement of sensory-motor and associative areas, possibly due to organization of information to process visuospatial parameters and further catch the falling object.

Performance of Down syndrome subjects during a coincident timing task

Abstract Background The time synchronization is a very important ability for the acquisition and performance of motor skills that generate the need to adapt the actions of body segments to external events of the environment that are changing their position in space. Down Syndrome (DS) individuals may present some deficits to perform tasks with synchronization demand. We aimed to investigate the performance of individuals with DS in a simple Coincident Timing task. Method 32 individuals were divided into 2 groups: the Down syndrome group (DSG) comprised of 16 individuals with average age of 20 (+/− 5 years old), and a control group (CG) comprised of 16 individuals of the same age. All individuals performed the Simple Timing (ST) task and their performance was measured in milliseconds. The study was conducted in a single phase with the execution of 20 consecutive trials for each participant. Results There was a significant difference in the intergroup analysis for the accuracy adjustment - Absolute Error (Z = 3.656, p = 0.001); and for the performance consistence - Variable Error (Z = 2.939, p = 0.003). Conclusion DS individuals have more difficulty in integrating the motor action to an external stimulus and they also present more inconsistence in performance. Both groups presented the same tendency to delay their motor responses.

Frequency and precision of feedback and the adaptive process of learning a dual motor task

This work investigated the effects of frequency and precision of feedback on the learning of a dual-motor task. One hundred and twenty adults were randomly assigned to six groups of different knowledge of results (KR), frequency (100%, 66% or 33%) and precision (specific or general) levels. In the stabilization phase, participants performed the dual task (combination of linear positioning and manual force control) with the provision of KR. Ten non-KR adaptation trials were performed for the same task, but with the introduction of an electromagnetic opposite traction force. The analysis showed a significant main effect for frequency of KR. The participants who received KR in 66% of the stabilization trials showed superior adaptation performance than those who received 100% or 33%. This finding reinforces that there is an optimal level of information, neither too high nor too low, for motor learning to be effective.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

Mesh Generation for Isogeometric Analysis with T-spline

[EN]The application of the Isogeometric Analysis (IA) with T-splines [1] demands a partition of the parametric space, C, in a tiling containing T-junctions denominated T-mesh. The T-splines are used both for the geometric modelization of the physical domain, D, and the basis of the numerical approximation. They have the advantage over the NURBS of allowing local refinement. In this work we propose a procedure to construct T-spline representations of complex domains in order to be applied to the resolution of elliptic PDE with IA. In precedent works [2, 3] we accomplished this task by using a tetrahedral parametrization…

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Genomic and transcriptional analysis of allergen genes in apple (Malus x domestica)

Apple consumption is highly recomended for a healthy diet and is the most important fruit produced in temperate climate regions. Unfortunately, it is also one of the fruit that most ofthen provoks allergy in atopic patients and the only treatment available up to date for these apple allergic patients is the avoidance. Apple allergy is due to the presence of four major classes of allergens: Mal d 1 (PR-10/Bet v 1-like proteins), Mal d 2 (Thaumatine-like proteins), Mal d 3 (Lipid transfer protein) and Mal d 4 (profilin). In this work new advances in the characterization of apple allergen gene families have been reached using a multidisciplinary approach. First of all, a genomic approach was used for the characterization of the allergen gene families of Mal d 1 (task of Chapter 1), Mal d 2 and Mal d 4 (task of Chapter 5). In particular, in Chapter 1 the study of two large contiguos blocks of DNA sequences containing the Mal d 1 gene cluster on LG16 allowed to acquire many new findings on number and orientation of genes in the cluster, their physical distances, their regulatory sequences and the presence of other genes or pseudogenes in this genomic region. Three new members were discovered co-localizing with the other Mal d 1 genes of LG16 suggesting that the complexity of the genetic base of allergenicity will increase with new advances. Many retrotranspon elements were also retrieved in this cluster. Due to the developement of molecular markers on the two sequences, the anchoring of the physical and the genetic map of the region has been successfully achieved. Moreover, in Chapter 5 the existence of other loci for the Thaumatine-like protein family in apple (Mal d 2.03 on LG4 and Mal d 2.02 on LG17) respect the one reported up to now was demonstred for the first time. Also one new locus for profilins (Mal d 4.04) was mapped on LG2, close to the Mal d 4.02 locus, suggesting a cluster organization for this gene family, as is well reported for Mal d 1 family. Secondly, a methodological approach was used to set up an highly specific tool to discriminate and quantify the expression of each Mal d 1 allergen gene (task of Chapter 2). In aprticular, a set of 20 Mal d 1 gene specific primer pairs for the quantitative Real time PCR technique was validated and optimized. As a first application, this tool was used on leaves and fruit tissues of the cultivar Florina in order to identify the Mal d 1 allergen genes that are expressed in different tissues. The differential expression retrieved in this study revealed a tissue-specificity for some Mal d 1 genes: 10/20 Mal d 1 genes were expressed in fruits and, indeed, probably more involved in the allergic reactions; while 17/20 Mal d 1 genes were expressed in leaves challenged with the fungus Venturia inaequalis and therefore probably interesting in the study of the plant defense mechanism. In Chapter 3 the specific expression levels of the 10 Mal d 1 isoallergen genes, found to be expressed in fruits, were studied for the first time in skin and flesh of apples of different genotypes. A complex gene expression profile was obtained due to the high gene-, tissue- and genotype-variability. Despite this, Mal d 1.06A and Mal d 1.07 expression patterns resulted particularly associated with the degree of allergenicity of the different cultivars. They were not the most expressed Mal d 1 genes in apple but here it was hypotized a relevant importance in the determination of allergenicity for both qualitative and quantitative aspects of the Mal d 1 gene expression levels. In Chapter 4 a clear modulation for all the 17 PR-10 genes tested in young leaves of Florina after challenging with the fungus V. inaequalis have been reported but with a peculiar expression profile for each gene. Interestingly, all the Mal d 1 genes resulted up-regulated except Mal d 1.10 that was down-regulated after the challenging with the fungus. The differences in direction, timing and magnitude of induction seem to confirm the hypothesis of a subfunctionalization inside the gene family despite an high sequencce and structure similarity. Moreover, a modulation of PR-10 genes was showed both in compatible (Gala-V. inaequalis) and incompatible (Florina-V. inaequalis) interactions contribute to validate the hypothesis of an indirect role for at least some of these proteins in the induced defense responses. Finally, a certain modulation of PR-10 transcripts retrieved also in leaves treated with water confirm their abilty to respond also to abiotic stress. To conclude, the genomic approach used here allowed to create a comprehensive inventory of all the genes of allergen families, especially in the case of extended gene families like Mal d 1. This knowledge can be considered a basal prerequisite for many further studies. On the other hand, the specific transcriptional approach make it possible to evaluate the Mal d 1 genes behavior on different samples and conditions and therefore, to speculate on their involvement on apple allergenicity process. Considering the double nature of Mal d 1 proteins, as apple allergens and as PR-10 proteins, the gene expression analysis upon the attack of the fungus created the base for unravel the Mal d 1 biological functions. In particular, the knowledge acquired in this work about the PR-10 genes putatively more involved in the specific Malus-V. inaequalis interaction will be helpful, in the future, to drive the apple breeding for hypo-allergenicity genotype without compromise the mechanism of response of the plants to stress conditions. For the future, the survey of the differences in allergenicity among cultivars has to be be thorough including other genotypes and allergic patients in the tests. After this, the allelic diversity analysis with the high and low allergenic cultivars on all the allergen genes, in particular on the ones with transcription levels correlated to allergencity, will provide the genetic background of the low ones. This step from genes to alleles will allow the develop of molecular markers for them that might be used to effectively addressed the apple breeding for hypo-allergenicity. Another important step forward for the study of apple allergens will be the use of a specific proteomic approach since apple allergy is a multifactor-determined disease and only an interdisciplinary and integrated approach can be effective for its prevention and treatment.

Foetal heart rate recording: analysis and comparison of different methodologies

Monitoring foetal health is a very important task in clinical practice to appropriately plan pregnancy management and delivery. In the third trimester of pregnancy, ultrasound cardiotocography is the most employed diagnostic technique: foetal heart rate and uterine contractions signals are simultaneously recorded and analysed in order to ascertain foetal health. Because ultrasound cardiotocography interpretation still lacks of complete reliability, new parameters and methods of interpretation, or alternative methodologies, are necessary to further support physicians’ decisions. To this aim, in this thesis, foetal phonocardiography and electrocardiography are considered as different techniques. Further, variability of foetal heart rate is thoroughly studied. Frequency components and their modifications can be analysed by applying a time-frequency approach, for a distinct understanding of the spectral components and their change over time related to foetal reactions to internal and external stimuli (such as uterine contractions). Such modifications of the power spectrum can be a sign of autonomic nervous system reactions and therefore represent additional, objective information about foetal reactivity and health. However, some limits of ultrasonic cardiotocography still remain, such as in long-term foetal surveillance, which is often recommendable mainly in risky pregnancies. In these cases, the fully non-invasive acoustic recording, foetal phonocardiography, through maternal abdomen, represents a valuable alternative to the ultrasonic cardiotocography. Unfortunately, the so recorded foetal heart sound signal is heavily loaded by noise, thus the determination of the foetal heart rate raises serious signal processing issues. A new algorithm for foetal heart rate estimation from foetal phonocardiographic recordings is presented in this thesis. Different filtering and enhancement techniques, to enhance the first foetal heart sounds, were applied, so that different signal processing techniques were implemented, evaluated and compared, by identifying the strategy characterized on average by the best results. In particular, phonocardiographic signals were recorded simultaneously to ultrasonic cardiotocographic signals in order to compare the two foetal heart rate series (the one estimated by the developed algorithm and the other provided by cardiotocographic device). The algorithm performances were tested on phonocardiographic signals recorded on pregnant women, showing reliable foetal heart rate signals, very close to the ultrasound cardiotocographic recordings, considered as reference. The algorithm was also tested by using a foetal phonocardiographic recording simulator developed and presented in this research thesis. The target was to provide a software for simulating recordings relative to different foetal conditions and recordings situations and to use it as a test tool for comparing and assessing different foetal heart rate extraction algorithms. Since there are few studies about foetal heart sounds time characteristics and frequency content and the available literature is poor and not rigorous in this area, a data collection pilot study was also conducted with the purpose of specifically characterising both foetal and maternal heart sounds. Finally, in this thesis, the use of foetal phonocardiographic and electrocardiographic methodology and their combination, are presented in order to detect foetal heart rate and other functioning anomalies. The developed methodologies, suitable for longer-term assessment, were able to detect heart beat events correctly, such as first and second heart sounds and QRS waves. The detection of such events provides reliable measures of foetal heart rate, potentially information about measurement of the systolic time intervals and foetus circulatory impedance.

Procedures of quality control and data analysis of multi-site ground-based observations for the absolute flux calibration of Gaia

The Gaia space mission is a major project for the European astronomical community. As challenging as it is, the processing and analysis of the huge data-flow incoming from Gaia is the subject of thorough study and preparatory work by the DPAC (Data Processing and Analysis Consortium), in charge of all aspects of the Gaia data reduction. This PhD Thesis was carried out in the framework of the DPAC, within the team based in Bologna. The task of the Bologna team is to define the calibration model and to build a grid of spectro-photometric standard stars (SPSS) suitable for the absolute flux calibration of the Gaia G-band photometry and the BP/RP spectrophotometry. Such a flux calibration can be performed by repeatedly observing each SPSS during the life-time of the Gaia mission and by comparing the observed Gaia spectra to the spectra obtained by our ground-based observations. Due to both the different observing sites involved and the huge amount of frames expected (≃100000), it is essential to maintain the maximum homogeneity in data quality, acquisition and treatment, and a particular care has to be used to test the capabilities of each telescope/instrument combination (through the “instrument familiarization plan”), to devise methods to keep under control, and eventually to correct for, the typical instrumental effects that can affect the high precision required for the Gaia SPSS grid (a few % with respect to Vega). I contributed to the ground-based survey of Gaia SPSS in many respects: with the observations, the instrument familiarization plan, the data reduction and analysis activities (both photometry and spectroscopy), and to the maintenance of the data archives. However, the field I was personally responsible for was photometry and in particular relative photometry for the production of short-term light curves. In this context I defined and tested a semi-automated pipeline which allows for the pre-reduction of imaging SPSS data and the production of aperture photometry catalogues ready to be used for further analysis. A series of semi-automated quality control criteria are included in the pipeline at various levels, from pre-reduction, to aperture photometry, to light curves production and analysis.

A novel map-matching procedure for low-sampling GPS data with applications to traffic flow analysis

An extensive sample (2%) of private vehicles in Italy are equipped with a GPS device that periodically measures their position and dynamical state for insurance purposes. Having access to this type of data allows to develop theoretical and practical applications of great interest: the real-time reconstruction of traffic state in a certain region, the development of accurate models of vehicle dynamics, the study of the cognitive dynamics of drivers. In order for these applications to be possible, we first need to develop the ability to reconstruct the paths taken by vehicles on the road network from the raw GPS data. In fact, these data are affected by positioning errors and they are often very distanced from each other (~2 Km). For these reasons, the task of path identification is not straightforward. This thesis describes the approach we followed to reliably identify vehicle paths from this kind of low-sampling data. The problem of matching data with roads is solved with a bayesian approach of maximum likelihood. While the identification of the path taken between two consecutive GPS measures is performed with a specifically developed optimal routing algorithm, based on A* algorithm. The procedure was applied on an off-line urban data sample and proved to be robust and accurate. Future developments will extend the procedure to real-time execution and nation-wide coverage.