Développement et validation d'un instrument non-invasifde caractérisation du comportement musculaire respiratoire

Réalisé en cotutelle avec l'Université Joseph Fourier École Doctorale Ingénierie pour la Santé,la Cognition et l'Environnement (France)

Apport d’une évaluation biomécanique 3D du genou dans la prise en charge orthopédique de patients ayant une rupture du ligament croisé antérieur

Parmi les blessures sportives reliées au genou, 20 % impliquent le ligament croisé antérieur (LCA). Le LCA étant le principal stabilisateur du genou, une lésion à cette structure engendre une importante instabilité articulaire influençant considérablement la fonction du genou. L’évaluation clinique actuelle des patients ayant une atteinte au LCA présente malheureusement des limitations importantes à la fois dans l’investigation de l’impact de la blessure et dans le processus diagnostic. Une évaluation biomécanique tridimensionnelle (3D) du genou pourrait s’avérer une avenue innovante afin de pallier à ces limitations. L’objectif général de la thèse est de démontrer la valeur ajoutée du domaine biomécanique dans (1) l’investigation de l’impact de la blessure sur la fonction articulaire du genou et dans (2) l’aide au diagnostic. Pour répondre aux objectifs de recherche un groupe de 29 patients ayant une rupture du LCA (ACLD) et un groupe contrôle de 15 participants sains ont pris part à une évaluation biomécanique 3D du genou lors de tâches de marche sur tapis roulant. L’évaluation des patrons biomécaniques 3D du genou a permis de démontrer que les patients ACLD adoptent un mécanisme compensatoire que nous avons intitulé pivot-shift avoidance gait. Cette adaptation biomécanique a pour objectif d’éviter de positionner le genou dans une condition susceptible de provoquer une instabilité antérolatérale du genou lors de la marche. Par la suite, une méthode de classification a été développée afin d’associer de manière automatique et objective des patrons biomécaniques 3D du genou soit au groupe ACLD ou au groupe contrôle. Pour cela, des paramètres ont été extraits des patrons biomécaniques en utilisant une décomposition en ondelettes et ont ensuite été classifiés par la méthode du plus proche voisin. Notre méthode de classification a obtenu un excellent niveau précision, de sensibilité et de spécificité atteignant respectivement 88%, 90% et 87%. Cette méthode a donc le potentiel de servir d’outil d’aide à la décision clinique. La présente thèse a démontré l’apport considérable d’une évaluation biomécanique 3D du genou dans la prise en charge orthopédique de patients présentant une rupture du LCA; plus spécifiquement dans l’investigation de l’impact de la blessure et dans l’aide au diagnostic.

Elementary steps in aqueous proton transfer reactions : a first principles molecular dynamics study

La nature des acides dans un environnement aqueux est primordiale dans de nombreux aspects de la chimie et de la biologie. La caractéristique principale d'un acide est sa capacité à transférer un proton vers une molécule d'eau ou vers n'importe quelle base, mais ce procédé n'est pas aussi simple qu'il y paraît. Il peut au contraire être extrêmement complexe et dépendre de manière cruciale de la solvatation des différents intermédiaires de réaction impliqués. Cette thèse décrit les études computationnelles basées sur des simulations de dynamique moléculaire ab initio qui ont pour but d'obtenir une description à l'échelle moléculaire des divers procédés de transferts de proton entre acide et bases dans un milieu aqueux. Pour cela, nous avons étudié une serie de système, dont l'acide hydrofluorique aqueux, l'acide trifluoroacétique aqueux, et un système modèle constitué d'un phénol et d'une entité carboxylate reliés entre eux par une molécule d'eau en solution aqueuse. Deux états intermédiaires ont été identifiés pour le transfert d'un proton depuis un acide. Ces intermédiaires apparaissent stabilisés par un motif local de solvatation via des ponts H. Leurs signatures spectroscopiques ont été caractérisées au moyen de la spectroscopie infrarouge, en utilisant le formalisme de la dynamique moléculaire ab initio, qui inclut l'effet quantique nucléaire de manière explicite. Cette étude a aussi identifié trois chemins de réaction élémentaire, qui sont responsable pour le transfert d'un proton d'un acide à une base, ainsi que leurs échelles de temps caractéristiques. Les conclusions tirées de ces études sont discutées dans les détails, au niveau moléculaire, avec une emphase sur les comparaisons entre les résultats théoriques et les mesures expérimentales obtenues dans a littérature ou via des collaborateurs.

Spatial and Temporal Variability of some Meteorological Parameters over Tropical Indian Ocean

The objective of the present study is to understand the spatial and temporal variability of sea surface temperature(SST), precipitable water, zonal and meridional components of wind stress over the tropical Indian Ocean to understand the different scales of variability of these features of Indian Ocean. Empirical Orthogonal Function (EOF) and wavelet analysis techniques are utilized to understand the standing oscillations and multi scale oscillations respectively. The study has been carried out over Indian Ocean and South Indian Ocean. For the present study, NCEP/NCAR(National Center for Environmental Prediction National Center for Atmospheric Research) reanalyzed daily fields of sea surface temperature, zonal and meridional surface wind components and precipitable water amount during 1960-1998 are used. The principle of EOF analysis and the methodology used for the analysis of spatial and temporal variance modes.

Some Efficient Representations of 3D Information based on Octress

The thesis introduced the octree and addressed the complete nature of problems encountered, while building and imaging system based on octrees. An efficient Bottom-up recursive algorithm and its iterative counterpart for the raster to octree conversion of CAT scan slices, to improve the speed of generating the octree from the slices, the possibility of utilizing the inherent parallesism in the conversion programme is explored in this thesis. The octree node, which stores the volume information in cube often stores the average density information could lead to “patchy”distribution of density during the image reconstruction. In an attempt to alleviate this problem and explored the possibility of using VQ to represent the imformation contained within a cube. Considering the ease of accommodating the process of compressing the information during the generation of octrees from CAT scan slices, proposed use of wavelet transforms to generate the compressed information in a cube. The modified algorithm for generating octrees from the slices is shown to accommodate the eavelet compression easily. Rendering the stored information in the form of octree is a complex task, necessarily because of the requirement to display the volumetric information. The reys traced from each cube in the octree, sum up the density en-route, accounting for the opacities and transparencies produced due to variations in density.

Characteristics of Upper Troposphere and Lower Stratosphere in Relation to Asian Summer Monsoon

The present work is an attempt to understand the characteristics of the upper troposphere and lower stratosphere over the Asian summer monsoon region, more specifically over the Indian subcontinent. Mainly three important parameters are taken such as zonal wind, temperature and ozone over the UT/LS of the Asian summer monsoon region. It made a detailed study of its interannual variability and characteristics of theses parameters during the Indian summer monsoon period. Monthly values of zonal wind and temperature from the NCEP/NCAR reanalysis for the period 1960-2002 are used for the present study. Also the daily overpass total ozone data for the 12 Indian stations (from low latitude to high latitudes) from the TOMS Nimbus 7 satellite for the period 1979 to 1992 were also used to understand the total ozone variation over the Indian region. The study reveals that if QBO phases in the stratosphere is easterly or weak westerly then the respective monsoon is found to be DRY or below Normal . On the other hand, if the phase is westerly or weak easterly the respective Indian summer monsoon is noted as a WET year. This connection of stratospheric QBO phases and Indian summer monsoon gives more insight in to the long-term predictions of Indian summer monsoon rainfall. Wavelet analysis and EOF methods are the two advanced statistical techniques used in the present study to explore more information of the zonal wind that from the smaller scale to higher scale variability over the Asian summer monsoon region. The interannual variability of temperature for different stratospheric and tropospheric levels over the Asian summer monsoon region have been studied. An attempt has been made to understand the total ozone characteristics and its interannual variablilty over 12 Indian stations spread from south latitudes to north latitudes. Finally it found that the upper troposphere and lower stratosphere contribute significantly to monsoon variability and climate changes. It is also observed that there exists a link between the stratospheric QBO and Indian summer monsoon

Comparison Study of Pattern Synthesis Techniques Using Neural Networks

In this paper, a comparison study among three neuralnetwork algorithms for the synthesis of array patterns is presented. The neural networks are used to estimate the array elements' excitations for an arbitrary pattern. The architecture of the neural networks is discussed and simulation results are presented. Two new neural networks, based on radial basis functions (RBFs) and wavelet neural networks (WNNs), are introduced. The proposed networks offer a more efficient synthesis procedure, as compared to other available techniques

An investigation into observational characteristics of rainfall and temperature in Central Northeast India—a historical perspective 1889–2008

Mann–Kendall non-parametric test was employed for observational trend detection of monthly, seasonal and annual precipitation of five meteorological subdivisions of Central Northeast India (CNE India) for different 30-year normal periods (NP) viz. 1889–1918 (NP1), 1919–1948 (NP2), 1949–1978 (NP3) and 1979–2008 (NP4). The trends of maximum and minimum temperatures were also investigated. The slopes of the trend lines were determined using the method of least square linear fitting. An application of Morelet wavelet analysis was done with monthly rainfall during June– September, total rainfall during monsoon season and annual rainfall to know the periodicity and to test the significance of periodicity using the power spectrum method. The inferences figure out from the analyses will be helpful to the policy managers, planners and agricultural scientists to work out irrigation and water management options under various possible climatic eventualities for the region. The long-term (1889–2008) mean annual rainfall of CNE India is 1,195.1 mm with a standard deviation of 134.1 mm and coefficient of variation of 11%. There is a significant decreasing trend of 4.6 mm/year for Jharkhand and 3.2 mm/day for CNE India. Since rice crop is the important kharif crop (May– October) in this region, the decreasing trend of rainfall during themonth of July may delay/affect the transplanting/vegetative phase of the crop, and assured irrigation is very much needed to tackle the drought situation. During themonth of December, all the meteorological subdivisions except Jharkhand show a significant decreasing trend of rainfall during recent normal period NP4. The decrease of rainfall during December may hamper sowing of wheat, which is the important rabi crop (November–March) in most parts of this region. Maximum temperature shows significant rising trend of 0.008°C/year (at 0.01 level) during monsoon season and 0.014°C/year (at 0.01 level) during post-monsoon season during the period 1914– 2003. The annual maximum temperature also shows significant increasing trend of 0.008°C/year (at 0.01 level) during the same period. Minimum temperature shows significant rising trend of 0.012°C/year (at 0.01 level) during postmonsoon season and significant falling trend of 0.002°C/year (at 0.05 level) during monsoon season. A significant 4– 8 years peak periodicity band has been noticed during September over Western UP, and 30–34 years periodicity has been observed during July over Bihar subdivision. However, as far as CNE India is concerned, no significant periodicity has been noticed in any of the time series.

Intraseasonal oscillation of total precipitable water over North Indian Ocean and its application in the diagnostic study of coastal rainfall

TRMM Microwave Imager (TMI) is reported to be a useful sensor to measure the atmospheric and oceanic parameters even in cloudy conditions. Vertically integrated specific humidity, Total Precipitable Water (TPW) retrieved from the water vapour absorption channel (22GHz.) along with 10m wind speed and rain rate derived from TMI is used to investigate the moisture variation over North Indian Ocean. Intraseasonal Oscillations (ISO) of TPW during the summer monsoon seasons 1998, 1999, and 2000 over North Indian Ocean is explored using wavelet analysis. The dominant waves in TPW during the monsoon periods and the differences in ISO over Arabian Sea and Bay of Bengal are investigated. The northward propagation of TPW anomaly and its coherence with the coastal rainfall is also studied. For the diagnostic study of heavy rainfall spells over the west coast, the intrusion of TPW over the North Arabian Sea is seen to be a useful tool.

PSWT Based Linear Predictive Coding and Development of a Parallel Multiple Subsequence Structure for DWT Computation

During 1990's the Wavelet Transform emerged as an important signal processing tool with potential applications in time-frequency analysis and non-stationary signal processing.Wavelets have gained popularity in broad range of disciplines like signal/image compression, medical diagnostics, boundary value problems, geophysical signal processing, statistical signal processing,pattern recognition,underwater acoustics etc.In 1993, G. Evangelista introduced the Pitch- synchronous Wavelet Transform, which is particularly suited for pseudo-periodic signal processing.The work presented in this thesis mainly concentrates on two interrelated topics in signal processing,viz. the Wavelet Transform based signal compression and the computation of Discrete Wavelet Transform. A new compression scheme is described in which the Pitch-Synchronous Wavelet Transform technique is combined with the popular linear Predictive Coding method for pseudo-periodic signal processing. Subsequently,A novel Parallel Multiple Subsequence structure is presented for the efficient computation of Wavelet Transform. Case studies also presented to highlight the potential applications.

Development of Time - Frequency Techniques for Sonar Applications

Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

“Improved Feature Extraction and Classification Techniques for Multispectral Brain Magnetic Resonance Images”

Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.

Characteristics of oscillation in surface layer and above over Cochin

The oscillations in the Atmospheric Boundary Layer (ABL) are important because the transport mechanism from the surface to the upper atmosphere is governed by the ABL characteristics. The study was carried out using wind and temperature data observed at surface, 925 hPa and 850 hPa levels over Cochin and the different frequencies embedded in the boundary layer parameters are identified by employing wavelet technique. Surface boundary layer characteristics over the monsoon region are closely linked to the upper layer monsoon features. In this perception it is important to study the various oscillations in the surface boundary layer and the layer above. It is found that the wind and temperature at different levels show oscillations in Quasi Biweekly Mode (QBM) and Intra Seasonal Oscillation (ISO) bands as observed in a typical monsoon system. Amplitude of the oscillation varies with height. The amplitude of the QBM periodicity is more in the surface levels but in the upper levels the amplitude of the ISO periodicity is more than that of the QBM. From this, it is obvious that the controlling mechanism of QBM band is surface parameters such as surface friction and that for ISO band is associated with the active-break cycles of monsoon system

Characteristic Study of the Boundary Layer Parameters over the Arabian Sea and the Bay of Bengal Using the QuikSCAT Dataset

The marine atmospheric boundary layer (MABL) plays a vital role in the transport of momentum and heat from the surface of the ocean into the atmosphere. A detailed study on the MABL characteristics was carried out using high-resolution surface-wind data as measured by the QuikSCAT (Quick scatterometer) satellite. Spatial variations in the surface wind, frictional velocity, roughness parameter and drag coe±cient for the di®erent seasons were studied. The surface wind was strong during the southwest monsoon season due to the modulation induced by the Low Level Jetstream. The drag coe±cient was larger during this season, due to the strong winds and was lower during the winter months. The spatial variations in the frictional velocity over the seas was small during the post-monsoon season (»0.2 m s¡1). The maximum spatial variation in the frictional velocity was found over the south Arabian Sea (0.3 to 0.5 m s¡1) during the southwest monsoon period, followed by the pre-monsoon over the Bay of Bengal (0.1 to 0.25 m s¡1). The mean wind-stress curl during the winter was positive over the equatorial region, with a maximum value of 1.5£10¡7 N m¡3, but on either side of the equatorial belt, a negative wind-stress curl dominated. The area average of the frictional velocity and drag coe±cient over the Arabian Sea and Bay of Bengal were also studied. The values of frictional velocity shows a variability that is similar to the intraseasonal oscillation (ISO) and this was con¯rmed via wavelet analysis. In the case of the drag coe±cient, the prominent oscillations were ISO and quasi-biweekly mode (QBM). The interrelationship between the drag coe±cient and the frictional velocity with wind speed in both the Arabian Sea and the Bay of Bengal was also studied.

COMBINED FEATURE EXTRACTION TECHNIQUES AND NAIVE BAYES CLASSIFIER FOR SPEECH RECOGNITION

Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.