Teses / dissertações sobre o tema "Détection des chutes humaines"
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Veja os 38 melhores trabalhos (teses / dissertações) para estudos sobre o assunto "Détection des chutes humaines".
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Mousse, Ange Mikaël. "Reconnaissance d'activités humaines à partir de séquences multi-caméras : application à la détection de chute de personne". Thesis, Littoral, 2016. http://www.theses.fr/2016DUNK0453/document.
Texto completo da fonteArtificial vision is an involving field of research. The new strategies make it possible to have some autonomous networks of cameras. This leads to the development of many automatic surveillance applications using the cameras. The work developed in this thesis concerns the setting up of an intelligent video surveillance system for real-time people fall detection. The first part of our work consists of a robust estimation of the surface area of a person from two (02) cameras with complementary views. This estimation is based on the detection of each camera. In order to have a robust detection, we propose two approaches. The first approach consists in combining a motion detection algorithm based on the background modeling with an edge detection algorithm. A fusion approach has been proposed to make much more efficient the results of the detection. The second approach is based on the homogeneous regions of the image. A first segmentation is performed to find homogeneous regions of the image. And finally we model the background using obtained regions
Dubois, Amandine. "Mesure de la fragilité et détection de chutes pour le maintien à domicile des personnes âgées". Phd thesis, Université de Lorraine, 2014. http://tel.archives-ouvertes.fr/tel-01070972.
Texto completo da fonteZoetgnandé, Yannick. "Fall detection and activity recognition using stereo low-resolution thermal imaging". Thesis, Rennes 1, 2020. http://www.theses.fr/2020REN1S073.
Texto completo da fonteNowadays, it is essential to find solutions to detect and prevent the falls of seniors. We proposed a low-cost device based on a pair of thermal sensors. The counterpart of these low-cost sensors is their low resolution (80x60 pixels), low refresh rate, noise, and halo effects. We proposed some approaches to bypass these drawbacks. First, we proposed a calibration method with a grid adapted to the thermal image and a framework ensuring the robustness of the parameters estimation despite the low resolution. Then, for 3D vision, we proposed a threefold sub-pixel stereo matching framework (called ST for Subpixel Thermal): 1) robust features extraction method based on phase congruency, 2) matching of these features in pixel precision, and 3) refined matching in sub-pixel accuracy based on local phase correlation. We also proposed a super-resolution method called Edge Focused Thermal Super-resolution (EFTS), which includes an edge extraction module enforcing the neural networks to focus on the edge in images. After that, for fall detection, we proposed a new method (called TSFD for Thermal Stereo Fall Detection) based on stereo point matching but without calibration and the classification of matches as on the ground or not on the ground. Finally, we explored many approaches to learn activities from a limited amount of data for seniors activity monitoring
Shaafi, Aymen. "Secured and trusted remote wireless health monitoring systems for assisted living of elderly people". Electronic Thesis or Diss., Université Paris Cité, 2021. http://www.theses.fr/2021UNIP5208.
Texto completo da fonteAging population is one of the key problems for the vast majority of many countries. The number of elderly people who suffer from multiple diseases and need continuous monitoring of their vital signs increases everyday, resulting in additional healthcare costs. Modern healthcare systems in geriatric medicine often require elderly presence at the hospital which conflict with their demand for independence and privacy. Recent developments on remote e-health monitoring, provides a wide range of solutions. However, most of the devices are designed for specific medical sensing and operate independently from each other. There is still a lack of integrated framework with high interoperability and continuous online monitoring support for further correlation analysis. This thesis is a step towards a remote, complete, and continuous data gathering system for elderly people with various types of health problems. Our research spirit is motivated by immediate demand in a secured and trusted remote wireless health monitoring System for assisted living Elderly people, combining various data sources. To create such a complete system we divide it into subsystems, in order to make it feasible and easy to implement, thus allowing us to update each subsystem individually in the future studies without affecting other integrated subsystems. The main focus is on a complete remote e-health monitoring system. The list of main contributions contains (1) propose a new approach for security of monitored devices and propose a solution to prevent MiTM attacks and reduce energy consumption, (2) we propose reliable fall detection,(3) investigating and developing a novel recognition method of daily activities for monitored elderly patient, (4) propose an approach to enhance the reliability of the system and to reduce false alarms and unnecessary interventions, (5) propose and develop a sign language to text converter algorithm using multi-sensor fusion analysis. As a result, we expect to provide a monitoring system with reliable accuracy in the detection of abnormal events, and raise an alarm upon detection of such events to seek help and assistance
Chahid, Omar. "Détection d'actions humaines interdites par fusion de capteurs". Mémoire, Université de Sherbrooke, 2009. http://savoirs.usherbrooke.ca/handle/11143/4844.
Texto completo da fonteSerra, Renan. "Développement et caractérisation d'un système de sol piézoélectrique intelligent : application à la détection des chutes". Thesis, Strasbourg, 2017. http://www.theses.fr/2017STRAD018.
Texto completo da fonteThis thesis is part of the field of design and elaboration of smart systems combined with a flooring sensor technology. The main objective deal with the design of an automated and smart tool to detect falls of elderly people in hospitals or nursing homes, in order to provide additional information to healthcare workers. First, various sensor technologies applied to floor covering have been studied. Among the technologies identified, piezoelectric planar polymer sensors have been chosen for the development of the smart system. Then, the characterization of the validated technical solution allows to define conditions and limits of use of the sensor. The robustness and durability were evaluated using methods that were specifically developed to address these aspects. Finally, detection algorithms have been developed to detect falls, footsteps and presence of people on our sensors. Classification strategies based on Pearson’s correlation, machine learning algorithms or threshold based algorithm have been used
Cavalcante, Aguilar Paulo Armando. "Réseaux Évidentiels pour la fusion de données multimodales hétérogènes : application à la détection de chutes". Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00789773.
Texto completo da fonteFilali, Wassim. "Détection temps réel de postures humaines par fusion d'images 3D". Toulouse 3, 2014. http://thesesups.ups-tlse.fr/3088/.
Texto completo da fonteThis thesis is based on a computer vision research project. It is a project that allows smart cameras to understand the posture of a person. It allows to know if the person is alright or if it is in a critical situation or in danger. The cameras should not be connected to a computer but embed all the intelligence in the camera itself. This work is based on the recent technologies like the Kinect sensor of the game console. This sensor is a depth sensor, which means that the camera can estimate the distance to every point in the scene. Our contribution consists on combining multiple of these cameras to have a better posture reconstruction of the person. We have created a dataset of images to teach the program how to recognize postures. We have adjusted the right parameters and compared our program to the one of the Kinect
Vaquette, Geoffrey. "Reconnaissance robuste d'activités humaines par vision". Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS090.
Texto completo da fonteThis thesis focuses on supervised activity segmentation from video streams within application context of smart homes. Three semantic levels are defined, namely gesture, action and activity, this thesis focuses mainly on the latter. Based on the Deeply Optimized Hough Transform paridigm, three fusion levels are introduced in order to benefit from various modalities. A review of existing action based datasets is presented and the lack of activity detection oriented database is noticed. Then, a new dataset is introduced. It is composed of unsegmented long time range daily activities and has been recorded in a realistic environment. Finaly, a hierarchical activity detection method is proposed aiming to detect high level activities from unsupervised action detection
Khelaifia, Saber. "Détection et culture des archaea associées aux muqueuses intestinale et orale humaines". Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM5029.
Texto completo da fonteArchaea is one of four known domains of life. Unlike what their name suggests, they some species of methanogenic archaea have been associated with oral, vaginal and intestinal mucosa. These methanogenic archaea are obligate anaerobic prokaryotes and their culture conditions are fastidious and very poorly known. Only four methanogenic archaea have been isolated from human samples including the digestive microbiota; Methanobrevibacter smithii detected in 95.7% of individuals Methanosphaera stadtmanae found in approximately one third of individuals and more recently in our laboratory Methanomassilicoccus luminyensis detected on average in 4% of individuals with a prevalence of age-related, and in the oral microbiota Methanobrevibacter oralis isolated from dental plaque
Auvinet, Edouard. "Analyse d'information tridimensionnelle issue de systèmes multi-caméras pour la détection de la chute et l'analyse de la marche". Phd thesis, Université Rennes 2, 2012. http://tel.archives-ouvertes.fr/tel-00946188.
Texto completo da fonteLangeard, Antoine. "Prévention de la chute chez la personne âgée : de la détection du risque à la réhabilitation par électrostimulation". Thesis, Normandie, 2017. http://www.theses.fr/2017NORMC210/document.
Texto completo da fonteThe objective of this work was to improve the prevention of falls in seniors by (i) improving the detection of people at risk, (ii) providing new tools for assessing postural control and (iii) studying the effects of rehabilitation program by electrostimulation on the markers of the risk of falling. In order to meet these three objectives, three parts were developed:The aim of Part I was to provide tools for better detection of persons at risk of falls or fractures through the identification of factors responsible for a decline in postural control. We have been able to establish through three studies that (i) elderly patients who take five or more drugs per day are at higher risk of cognitive and mobility impairments, (ii) subjects who undergo fractures have a stabilization deficit after obstacle crossing and (iii) fractured fallers reduce their walking speed less during dual-task walking.In Part II we evaluated for the first time the braking of the center of mass, a parameter correlated with the quality of the postural control, with a kinematic analysis technique. It has been demonstrated that the technic usually used, the force-plate analysis, presents greater variability and leads to an underestimation of the braking index in comparison with this new method of analysis.In Part III we tested the effectiveness of a training program by electrostimulation of the ankle plantar and dorsiflexors on the parameters related to the fall or its severity. This training increased the strenght, and probably the contraction speed of the ankle muscles. Although the rehabilitation of other muscles seems necessary to improve gait,the training program has rehabilitated dynamic balance
Amoud, Hassan. "Détection d'une évolution du risque de chute chez les personnes âgées". Troyes, 2006. http://www.theses.fr/2006TROY0018.
Texto completo da fontePrevious research has identified over 60 parameters that can be used to characterise static balance, within which three groups exist: spatiotemporal, spectral and stochastic. This last group was analyzed to study its capacity to identify postural differences between two groups of elderly and control subject, its robustness and the minimal duration needed for its calculation. An analysis by nonlinear methods is carried out by using several methods to estimate entropy, such as Approximate Entropy (ApEn), Sample Entropy (SampEn) and Multi-Scale Entropy (MSE). However, these methods suffer from the presence of low-frequency components in the signals. To resolve this problem, a new method called Intrinsic Mode Entropy (IMEn) has been developed based on the Empirical Mode Decomposition (EMD) to eliminate low frequency components (IMFs). The results obtained show that this method is able to characterize postural balance and identify postural differences between groups. Finally, a simulation of the degradation of balance was carried out to make it possible to select those parameters that are able to identify a degradation of balance. Parameter selection was carried out by change-detection methods and supervised feature-selection methods. This study showed that it is possible to find several combinations of these parameters to detect a degradation of balance
Haffner, Julien. "Conception d'un sol instrumenté pour la détection de chutes de personnes à l'aide de capteurs capacitifs et de techniques de l'apprentissage statistique". Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066117.
Texto completo da fonteAlmost 9000 people aged over 65 die each year in France, as consequences of a fall. Falls represent over 80% of all domestic accidents in this part of the population. This number should substantially increase, as the average age of the population is expected to constantly grow up in the next decades. The longest the fallen person stay on the floor without being rescued, the worst are the consequences of the fall. In order to decrease negative effects of falls in older people, it is decisive to develop a technological way to keep isolated people in contact with outside world. In this thesis two fall detection systems are presented, made up with capacitive sensors integrated into the floor. Sensors are totally hidden to the view of people living in the room, in a way that their privacy is most respected. In the first system, parallel sensors are laid out in one direction of the room. One sensor is composed of four electrodes, whose relative spaces have been chosen to favor the detection of a person laying down on the floor. The second system consists of two perpendicular layers of capacitive sensors. Several rooms have been equipped with such sensors. Installing sensors in a new environment has an influence on the measured capacitive signal, due to the own floor configuration in each room. Methods of data preprocessing are proposed, in order to give equivalent detection performances in each environment
Haffner, Julien. "Conception d'un sol instrumenté pour la détection de chutes de personnes à l'aide de capteurs capacitifs et de techniques de l'apprentissage statistique". Electronic Thesis or Diss., Paris 6, 2016. http://www.theses.fr/2016PA066117.
Texto completo da fonteAlmost 9000 people aged over 65 die each year in France, as consequences of a fall. Falls represent over 80% of all domestic accidents in this part of the population. This number should substantially increase, as the average age of the population is expected to constantly grow up in the next decades. The longest the fallen person stay on the floor without being rescued, the worst are the consequences of the fall. In order to decrease negative effects of falls in older people, it is decisive to develop a technological way to keep isolated people in contact with outside world. In this thesis two fall detection systems are presented, made up with capacitive sensors integrated into the floor. Sensors are totally hidden to the view of people living in the room, in a way that their privacy is most respected. In the first system, parallel sensors are laid out in one direction of the room. One sensor is composed of four electrodes, whose relative spaces have been chosen to favor the detection of a person laying down on the floor. The second system consists of two perpendicular layers of capacitive sensors. Several rooms have been equipped with such sensors. Installing sensors in a new environment has an influence on the measured capacitive signal, due to the own floor configuration in each room. Methods of data preprocessing are proposed, in order to give equivalent detection performances in each environment
Charfi, Imen. "Détection automatique de chutes de personnes basée sur des descripteurs spatio-temporels : définition de la méthode, évaluation des performances et implantation temps-réel". Phd thesis, Université de Bourgogne, 2013. http://tel.archives-ouvertes.fr/tel-00959850.
Texto completo da fonteDaher, Mohamad. "Fusion multi-capteurs tolérante aux fautes pour un niveau d'intégrité élevé du suivi de la personne". Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10136/document.
Texto completo da fonteAbout one third of home-dwelling older people suffer a fall each year. The most painful falls occur when the person is alone and unable to get up, resulting in huge number of elders which are associated with institutionalization and high morbidity-mortality rate. The PAL (Personally Assisted Living) system appears to be one of the solutions of this problem. This ambient intelligence system allows elderly people to live in an intelligent and pro-active environment. This thesis describes the ongoing work of in-home elder tracking, activities daily living recognition, and automatic fall detection system using a set of non-intrusive sensors that grants privacy and comfort to the elders. In addition, a fault-tolerant fusion method is proposed using a purely informational formalism: information filter on the one hand, and information theory tools on the other hand. Residues based on the Kullback-Leibler divergence are used. Using an appropriate thresholding, these residues lead to the detection and the exclusion of sensors faults. The proposed algorithms were validated with many different scenarios containing the different activities: walking, sitting, standing, lying down, and falling. The performances of the developed methods showed a sensitivity of more than 94% for the fall detection of persons and more than 92% for the discrimination between the different ADLs (Activities of the daily life)
Mroué, Ali. "Etude et évaluation d'un système multi-radars monostatiques ultra large bande : application à la détection et à l'identification de chutes sur les voies ferroviaires". Valenciennes, 2010. http://ged.univ-valenciennes.fr/nuxeo/site/esupversions/f81c9e2d-8748-4721-9c7c-12dcf60ce0fc.
Texto completo da fonteThis thesis presents the development of an Ultra Wide Band monostatic multi-radar sys- tem developed along a single axis. This system aims to detect and identify targets along its axis. The considered field of application is to detect and identify fall on track objects in order to enhance guided transport passenger safety. The main objective of this work is to study the different radiofrequency and signal processing subsets in order to validate the feasibility of the whole system. Simulation and expe- rimentations are performed. A slotted waveguide operated in its fundamental mode is used. Slots close to resonance are periodically perforated and constitute the monostatic radars. An optimal bandwidth and constant radiation coverage along the railway is then optimized. The singularity expansion method (SEM) is used and the characterization of objects fallen onto the track is performed. Complex natural resonances are computed and measured and then saved into a library for further use in a specific discrimination process. Using both numerical simulations and experimental results, the discrimination process shows that the human body is well discriminated as well as other typical objects (suitcases. . . ). In conclusion, this work has led to significant advances in object detection and identification in the railway field, and could have some fallout in other fields such as detection of liquids in the passenger luggage in the airport or detection and identification of intrusions in complex environments
Yaradou, Diaraf Farba. "Legionella pneumophila : de la détection dans les réseaux d'eau à l'étude de l'invasion des cellules épithéliales pulmonaires humaines". Lyon 1, 2007. http://www.theses.fr/2007LYO10174.
Texto completo da fonteLévesque, Ryan Maude. "Technologies d'information de santé chez les personnes âgées : attitudes, conseils et volonté d'usage". Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39644.
Texto completo da fonteChaccour, Kabalan. "Elaborating the Actimetric Profile of Fall Sensitive Patients for Early Detection of Fall Incidents". Thesis, Bourgogne Franche-Comté, 2017. http://www.theses.fr/2017UBFCA016/document.
Texto completo da fonteGrowth is the normal change of the human body and getting old is inevitable to human race. As a result, elderly people are subject to many forms of diseases and dangers among which falls are considered very serious in terms of quality of life and socio-economic costs. But falls can be manageable. Health practitioners, scientists and researchers currently combine efforts to develop systems capable of detecting and predicting falls. In the context of fall prediction, the goal of this thesis is to elaborate the actimetric profile of fall sensitive patients to alert them from a potential fall. It mainly consists of developing a system capable of monitoring gait and balance parameters during their daily activities with minimum intrusiveness. These are usually assessed in clinical settings using high-cost tools. In our first contribution, we proposed a generic classification of fall-related systems based on their sensors deployment. These are classified as Wearable, Non-Wearable and Fusion Systems. Based on the generic classification, we proposed the WMFL v1.0 platform in our second contribution. WMFL fuses a Foot Wear Force Sensing device with an Ambient system using IR-sensing floor tiles. The platform can be deployed at homes or in clinics. It ensures an indoor-outdoor protection. In a third contribution, we proposed an early fall detection approach to determine the risk of falling by analyzing the displacement of the Center of Pressure projecting the amount of sway of the Center of Mass on the foot plantar surface. The method uses the spatio-temporal sliding window to alert the patient of a potential fall
Klaser, Alexander. "Apprentissage pour la reconnaissance d'actions humaines en vidéo". Phd thesis, Grenoble, 2010. http://tel.archives-ouvertes.fr/tel-00514814.
Texto completo da fonteCette thèse s'intéresse à la reconnaissance des actions humaines dans des données vidéo réalistes, tels que les films. À cette fin, nous développons des algorithmes d'extraction de caractéristiques visuelles pour la classification et la localisation d'actions.
Dans une première partie, nous étudions des approches basées sur les sacs-de-mots pour la classification d'action. Dans le cas de vidéo réalistes, certains travaux récents qui utilisent le modèle sac-de-mots pour la représentation d'actions ont montré des résultats prometteurs. Par conséquent, nous effectuons une comparaison approfondie des méthodes existantes pour la détection et la description des caractéristiques locales. Ensuite, nous proposons deux nouvelles approches pour la descriptions des caractéristiques locales en vidéo. La première méthode étend le concept d'histogrammes sur les orientations de gradient dans le domaine spatio-temporel. La seconde méthode est basée sur des trajectoires de points d'intérêt détectés spatialement. Les deux descripteurs sont évalués avec une représentation par sac-de-mots et montrent une amélioration par rapport à l'état de l'art pour la classification d'actions.
Dans une seconde partie, nous examinons comment la détection de personnes peut contribuer à la reconnaissance d'actions. Tout d'abord, nous développons une approche qui combine la détection de personnes avec une représentation sac-de-mots. La performance est évaluée pour la classification d'actions à plusieurs niveaux d'échelle spatiale. Ensuite, nous explorons la localisation spatio-temporelle des actions humaines dans les films. Nous étendons une approche de suivi de personnes pour des vidéos réalistes. En outre, nous développons une représentation d'actions qui est adaptée aux détections de personnes. Nos expériences suggèrent que la détection de personnes améliore significativement la localisation d'actions. De plus, notre système montre une grande amélioration par rapport à l'état de l'art actuel.
Klaser, Alexander. "Apprentissage pour la reconnaissance d'actions humaines en vidéo". Phd thesis, Grenoble, 2010. http://www.theses.fr/2010GRENM039.
Texto completo da fonteThis dissertation targets the recognition of human actions in realistic video data, such as movies. To this end, we develop state-of-the-art feature extraction algorithms that robustly encode video information for both, action classification and action localization. In a first part, we study bag-of-features approaches for action classification. Recent approaches that use bag-of-features as representation have shown excellent results in the case of realistic video data. We, therefore, conduct an extensive comparison of existing methods for local feature detection and description. We, then, propose two new approaches to describe local features in videos. The first method extends the concept of histograms over gradient orientations to the spatio-temporal domain. The second method describes trajectories of local interest points detected spatially. Both descriptors are evaluated in a bag-of-features setup and show an improvement over the state-of-the-art for action classification. In a second part, we investigate how human detection can help action recognition. Firstly, we develop an approach that combines human detection with a bag-of-features model. The performance is evaluated for action classification with varying resolutions of spatial layout information. Next, we explore the spatio-temporal localization of human actions in Hollywood movies. We extend a human tracking approach to work robustly on realistic video data. Furthermore we develop an action representation that is adapted to human tracks. Our experiments suggest that action localization benefits significantly from human detection. In addition, our system shows a large improvement over current state-of-the-art approaches
Cherra, Khalead. "Développement d'un support solide pour les tests immunoenzymatiques en phase hétérogène : Application à la détection de neurotoxines et d'IgG humaines". Compiègne, 1991. http://www.theses.fr/1991COMPD386.
Texto completo da fonteWe have developed a new solid phase made of gelatin coated nitrocellulose membrane. This support offers the possibility of covalent linkage of proteins. We have studied this membrane by the development of immunoenzymatic essays. We have optimized the parameters involved in immobilization efficiency
Nguyen, Thi Khanh Hong. "Conception faible consommation d'un système de détection de chute". Thesis, Nice, 2015. http://www.theses.fr/2015NICE4093/document.
Texto completo da fonteNowadays, fall detection is a major challenge in the public health care domain, especially for the elderly living alone and rehabilitants in hospitals. This thesis presents an exploration for a Fall Detection System based on camera under an algorithmic and architectural point of view. Our system includes four modules: Object Segmentation, Filter, Feature Extraction and Recognition and give an urgent alarm for detecting different kinds of fall. Firstly, different algorithms for the Fall Detection System are proposed and compared the efficiency among Background Subtraction-Neural Network, Background Subtraction-Template Matching (BGS/TM), Background Subtraction-Hidden Markov Model, and Gaussian Mixture Model. Therefore, the selected BGS/TM with 91.67% (Recall), 100% (Precision) and 95.65% (Accuracy) will be implemented on ZYNQ platform. Moreover, a DUT-HBU database which is classified with different actions: fall, non-fall in three camera directions is used to evaluate the efficiency of this system. Secondly, the aim is to explore low cost architectures for this system, new power consumption and execution time models for processor core and FPGA are defined according to the different configurations of architecture and applications. The error rates of the proposed models don’t exceed 3.5%. The models are then extended to hardware/software architectures to explore low cost architecture by defining a suitable Design Space Exploration methodology. Two techniques for parallelization which are based on intra-task and inter-task static scheduling are applied with the aim to enhance the accuracy and the power consumption of this system reaches 98.3% with energy per frame of 29.5mJ/f
Belle, Michèle. "Détection et dosage des des-gamma-carboxyprothrombines plasmatiques humaines : application à l'étude de pathologies associées à un déficit en vitamine K". Lyon 1, 1992. http://www.theses.fr/1992LYO1T158.
Texto completo da fonteLutsch, Charles. "Les antigènes circulants dans les filarioses lymphatiques et les schistosomiases humaines : intérêt diagnostique et pronostique de leur détection par des anticorps monoclonaux". Lille 1, 1989. http://www.theses.fr/1989LIL10061.
Texto completo da fonteNguyen, Quang Vinh. "Contribution à l'étude de la physiologie de la chute du senior, application aux systèmes couplés pied-poignet". Rennes 1, 2012. http://www.theses.fr/2012REN1E006.
Texto completo da fonteRaieli, Salvatore. "TLR2 / 1 Orchestrent la réponse de les cellules dendritiques plasmacytoïdes humaines à les bactéries Gram +". Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS495/document.
Texto completo da fonteInfections by Gram+ bacteria are worldwide life-threatening diseases where new studies are highlighting the pathological role of Type I interferon (I IFN). Plasmacytoid dendritic cells (pDCs) are the main source of Type I IFN following viral sensing. Recent evidence suggests that human pDCs might sense bacteria. The receptors mediating bacterial sensing in pDCs are not known. During my thesis, I focused on the characterization of pDCs TLR2/1 receptors expression. These two receptors allow pDCs to sense Gram+ bacterial lipoproteins. My work showed that human primary pDCs express TLR1 and TLR2 at the mRNA and protein level. I show that pDCs respond to the Gram+ bacteria M. tuberculosis, S. aureus and L. monocytogenes through TLR2/1 pathway. In human primary pDC, I found that in response to bacterial lipoproteins up-regulation of costimulatory molecules is TLR1-dependent while IFN-I secretion is TLR2-dependent. TLR2 and TLR1 signalling play a different role in the pDCs priming of naïve CD4+ T-cells, inducing proliferation and differentiation to TH1/TH2/Treg subsets. I further demonstrate that these differences rely on the diverse signaling pathway activated by the two TLRs. This work provides the rationale to explore pDCs activity in human bacterial infection
Attal, Ferhat. "Classification de situations de conduite et détection des événements critiques d'un deux roues motorisé". Thesis, Paris Est, 2015. http://www.theses.fr/2015PEST1003/document.
Texto completo da fonteThis thesis aims to develop framework tools for analyzing and understanding the riding of Powered Two Wheelers (PTW). Experiments are conducted using instrumented PTW in real context including both normal (naturalistic) riding behaviors and critical riding behaviors (near fall and fall). The two objectives of this thesis are the riding patterns classification and critical riding events detection. In the first part of this thesis, a machine-learning framework is used for riding pattern recognition problem. Therefore, this problem is formulated as a classification task to identify the class of riding patterns. The approaches developed in this context have shown the interest to take into account the temporal aspect of the data in PTW riding. Moreover, we have shown the effectiveness of hidden Markov models for such problem. The second part of this thesis focuses on the development of the off-line detection and classification of critical riding events tools and the on-line fall detection. The problem of detection and classification of critical riding events has been performed towards two steps: (1) the segmentation step, where the multidimensional time of data were modeled and segmented by using a mixture model with quadratic logistic proportions; (2) the classification step, which consists in using a pattern recognition algorithm in order to assign each event by its extracted features to one of the three classes namely Fall, near Fall and Naturalistic riding. Regarding the fall detection problem, it is formulated as a sequential anomaly detection problem. The Multivariate CUmulative SUM (MCUSUM) control chart was applied on the data collected from sensors mounted on the motorcycle. The obtained results on a real database have shown the effectiveness of the proposed methodology for both riding pattern recognition and critical riding events detection problems
Poujaud, Julien. "Etude de méthodes de fusion de données multi-capteurs pour le diagnostic et la classification de situations complexes. Application au développement d'un dispositif intégré pour la détection de la chute des personnes âgées". Thesis, Grenoble, 2012. http://www.theses.fr/2012GRENT022.
Texto completo da fonteIn 2050, the elderly population over 65-years-old, will represent about 20% of the world's population. Getting older is an opportunity, but unfortunately it also makes people dependent. This dependence requires help, sometimes permanent, from relatives, health professionals and in the worst case may cause a placement of the elderly in a nursing home. Unfortunately, this kind of help is not, and will not be, sufficient to allow every elderly person to live the rest of their life in the respect of human dignity. A potential technological support can be found with automatic detection systems which help detect critical situations. Of course, this kind of system will not replace human help, but only support them. The goal of this thesis is to develop an integrated systemwhich can meet these expectations. After a review of the critical situations of the elderly living independently at home, a bibliography of the existing systems of detection is done. This analysis will help to design a multi sensor analysis and classification system of critical situations detection. The latter is based on different kinds of non invasive sensors located in the homes of the elderly. Experimental data allows to classifying the activity of the elderly thanks to a data fusion algorithm. In case of a critical situation, the alarmsystem will automatically alert the emergency platform. This system was also tested thanks to functional and laboratory experiments
Fayad, Moustafa. "Health care platform development based on multimedia sensors". Electronic Thesis or Diss., Université Paris Cité, 2021. http://www.theses.fr/2021UNIP5204.
Texto completo da fonteAll countries are facing significant demographic changes on an unprecedented scale. Seniors are the fastest-growing segment of the world's population. It increases dependent and vulnerable older adults marked by loss of autonomy and chronic illness. These complications increase mortality and morbidity rates in our societies. In recent years, the socio-economic consequences on seniors and their families and the high prices in specialized accommodation establishments have drawn attention to home support by using new reliable and inexpensive technologies. However, developing a critical healthcare system for the elderly is a real challenge that can only be met by ensuring reliability and high performance. Within the framework of the future health care system named Family Heroes, we are interested in this thesis in its reliability and safety. Thus, we studied the automatic detection of falls using the Kinect camera. More precisely, we have proposed a methodology combining the CATWOE method and UML notions to analyze and model our system. We have shown the steps to take to consider system requirements and constraints in the development process effectively. Thus, we used the MARTE concepts to face the time constraints in the modeling phase. Then, to ensure the reliability of our system, we proposed a formal verification approach based on the UML / MARTE models presented in the modeling stage. We modeled them with timed automata and deployed the UPPAAL model checker to specify and verify properties. To ensure the security of our system, we have presented a formal approach to deal with cyber-attack issues that may arise in the Family Heroes system. Thus, we adopted a scenario of cyberattacks linked to this context and proposed reconfiguring our system to face cyberattacks. In addition, formal verification has been proposed to ensure the reliability of the proposed solution. The results showed the respect of the properties (No deadlock, accessibility, security, and liveliness) in Family Heroes.For automatic fall detection, we used the multimedia sensor of Kinect technology. We have proposed a new approach based on thresholds that analyzes the variation in height, the angles of the upper body during the cycle of movement, and the person's inactivity on the ground. In addition, we have proposed a new lightweight model based on Deep Learning LSTM using geometric features. This lightweight model is designed to work on limited devices like the Raspberry Pi. The results are very promising
Auvinet, Edouard. "Analyse d’information tridimensionnelle issue de systèmes multi-caméras pour la détection de la chute et l’analyse de la marche". Thèse, Rennes 2, 2012. http://hdl.handle.net/1866/9770.
Texto completo da fonteThis thesis is concerned with defining new clinical investigation method to assess the impact of ageing on motricity. In particular, this thesis focuses on two main possible disturbance during ageing : the fall and walk impairment. This two motricity disturbances still remain unclear and their clinical analysis presents real scientist and technological challenges. In this thesis, we propose novel measuring methods usable in everyday life or in the walking clinic, with a minimum of technical constraints. In the first part, we address the problem of fall detection at home, which was widely discussed in previous years. In particular, we propose an approach to exploit the subject’s volume, reconstructed from multiple calibrated cameras. These methods are generally very sensitive to occlusions that inevitably occur in the home and we therefore propose an original approach much more robust to these occultations. The efficiency and real-time operation has been validated on more than two dozen videos of falls and lures, with results approaching 100 % sensitivity and specificity with at least four or more cameras. In the second part, we go a little further in the exploitation of reconstructed volumes of a person at a particular motor task : the treadmill, in a clinical diagnostic. In this section we analyze more specifically the quality of walking. For this we develop the concept of using depth camera for the quantification of the spatial and temporal asymmetry of lower limb movement during walking. After detecting each step in time, this method makes a comparison of surfaces of each leg with its corresponding symmetric leg in the opposite step. The validation performed on a cohort of 20 subjects showed the viability of the approach.
Réalisé en cotutelle avec le laboratoire M2S de Rennes 2
Vossier, Ludivine. "Risque bactérien et transfusion sanguine : vers de nouvelles approches préventives". Thesis, Montpellier 1, 2013. http://www.theses.fr/2013MON13518.
Texto completo da fonteThe prevention of the infectious risk is a major issue for the Etablissement Français du Sang. Currently, bacterial contamination is the most infectious risk in developed countries. The bacterial risk is not limited to blood transfusion safety. The antimicrobial resistance is a major public health problem. Antimicrobial peptides are important arm of the innate immune system which represents an interesting alternative to antibiotics. Human neutrophil peptides 1, 2 and 3 (HNPs 1-3) are found in the azurophilic granules of neutrophils. We have developed an original approach of HNPs 1-3 purification from leucodepletion filters used in blood processing. This process allows the production of a pure cocktail of HNPs 1-3 displaying high antibacterial activity as demonstrated by this work. HNPs 1-3 have also been used as bioreceptor in an innovative approach for bacterial detection. Initially, an electrochemical immunosensor was designed, exploiting magnetic microparticles coated with commercially available antibodies. In a second step, magnetic microparticles have been coated efficently with the HNPs 1-3 purified according our protocol. We have obtained a first proof of concept showing the bacterial capture by this innovative approach. The peptides stability combined with the electrochemical biosensors performances would allow the development of a generic bacteria detection assay in labile blood products
Diop, Cheikh Abdoulahat. "La structure multimodale de la distribution de probabilité de la réflectivité radar des précipitations". Toulouse 3, 2012. http://thesesups.ups-tlse.fr/3089/.
Texto completo da fonteA set of radar data gathered over various sites of the US Nexrad (Next Generation Weather Radar) S band radar network is used to analyse the probability distribution function (pdf) of the radar reflectivity factor (Z) of precipitation, P(Z). Various storm types are studied and a comparison between them is made: 1) hailstorms at the continental site of Little Rock (Arkansas), 2) peninsular and coastal convection at Miami (Florida), 3) coastal convection and land/sea transition at Brownsville (Texas), 4) tropical maritime convection at Hawaii, 5) midlatitude maritime convection at Eureka (California), 6) snowstorms from winter frontal continental systems at New York City (New York), and 7) high latitude maritime snowstorms at Middleton Island (Alaska). Each storm type has a specific P(Z) signature with a complex shape. It is shown that P(Z) is a mixture of Gaussian components, each of them being attribuable to a precipitation type. Using the EM (Expectation Maximisation) algorithm of Dempster et al. 1977, based on the maximum likelihood method, four main components are categorized in hailstorms: 1) cloud and precipitation of very low intensity or drizzle, 2) stratiform precipitation, 3) convective precipitation, and 4) hail. Each component is described by the fraction of area occupied inside P(Z) and by the two Gaussian parameters, mean and variance. The absence of hail component in maritime and coastal storms is highlighted. For snowstorms, P(Z) has a more regular shape. The presence of several components in P(Z) is linked to some differences in the dynamics and microphysics of each precipitation type. The retrieval of the mixed distribution by a linear combination of the Gaussian components gives a very stisfactory P(Z) fitting. An application of the results of the split-up of P(Z) is then presented. Cloud, rain, and hail components have been isolated and each corresponding P(Z) is converted into a probability distribution of rain rate P(R) which parameters are µR and sR2 , respectively mean and variance. It is shown on the graph (µR ,sR2) that each precipitation type occupies a specific area. This suggests that the identified components are distinct. For example, the location of snowstorms representative points indicates that snow is statistically different from rain. The P(R) variation coefficient, CVR = sR/µR is constant for each precipitation type. This result implies that knowing CVR and measuring only one of the P(R) parameters enable to determine the other one and to define the rain rate probability distribution. The influence of the coefficients a and b of the relation Z = aRb on P(R) is also discussed
Mokhtari, Djamila. "Détection des chutes par calcul homographique". Thèse, 2012. http://hdl.handle.net/1866/8869.
Texto completo da fonteThe main objective of video surveillance is to protect persons and property by detecting any abnormal behavior. This is not possible without detecting motion in the image. This process is often based on the concept of subtraction of the scene background. However in video tracking, the cameras are themselves often in motion, causing a significant change of the background. So, background subtraction techniques become problematic. We propose in this work a motion detection approach, with the example application of fall detection. This approach is free of background subtraction for a rotating surveillance camera. The method uses the camera rotation to detect motion by using homographic calculation. Our results on synthetic and real video sequences demonstrate the feasibility of this approach.
Rougier, Caroline. "Vidéosurveillance intelligente pour la détection de chutes chez les personnes âgées". Thèse, 2010. http://hdl.handle.net/1866/4113.
Texto completo da fonteDeveloped countries like Canada have to adapt to a growing population of seniors. A majority of seniors reside in private homes and most of them live alone, which can be dangerous in case of a fall, particularly if the person cannot call for help. Video surveillance is a new and promising solution for healthcare systems to ensure the safety of elderly people at home. Concretely, a camera network would be placed in the apartment of the person in order to automatically detect a fall. When a fall is detected, a message would be sent to the emergency center or to the family through a secure Internet connection. For a low cost system, we must limit the number of cameras to only one per room, which leads us to explore monocular methods for fall detection. We first studied 2D information (images) by analyzing the shape deformation during a fall. Normal activities of an elderly person were used to train a Gaussian Mixture Model (GMM) to detect any abnormal event. Our method was tested with a realistic video data set of simulated falls and normal activities. However, 3D information like the spatial localization of a person in a room can be very useful for action recognition. Although a multi-camera system is usually preferable to acquire 3D information, we have demonstrated that, with only one calibrated camera, it is possible to localize a person in his/her environment using the person’s head. Concretely, the head, modeled by a 3D ellipsoid, was tracked in the video sequence using particle filters. The precision of the 3D head localization was evaluated with a video data set containing the real 3D head localizations obtained with a Motion Capture system. An application example using the 3D head trajectory for fall detection is also proposed. In conclusion, we have confirmed that a video surveillance system for fall detection with only one camera per room is feasible. To reduce the risk of false alarms, a hybrid method combining 2D and 3D information could be considered.
Alla, Jules-Ryane S. "Détection de chute à l'aide d'une caméra de profondeur". Thèse, 2013. http://hdl.handle.net/1866/9992.
Texto completo da fonteElderly falls are a major public health problem. Studies show that about 30% of people aged 65 and older fall each year in Canada, with negative consequences on individuals, their families and our society. Faced with such a situation a video surveillance system is an effective solution to ensure the safety of these people. To this day many systems support services to the elderly. These devices allow the elderly to live at home while ensuring their safety by wearing a sensor. However the sensor must be worn at all times by the subject which is uncomfortable and restrictive. This is why research has recently been interested in the use of cameras instead of wearable sensors. The goal of this project is to demonstrate that the use of a video surveillance system can help to reduce this problem. In this thesis we present an approach for automatic detection of falls based on a method for tracking 3D subject using a depth camera (Kinect from Microsoft) positioned vertically to the ground. This monitoring is done using the silhouette extracted in real time with a robust approach for extracting 3D depth based on the depth variation of the pixels in the scene. This method is based on an initial capture the scene without any body. Once extracted, 10% of the silhouette corresponding to the uppermost region (nearest to the Kinect) will be analyzed in real time depending on the speed and the position of its center of gravity . These criteria will be analysed to detect the fall, then a signal (email or SMS) will be transmitted to an individual or to the authority in charge of the elderly. This method was validated using several videos of a stunt simulating falls. The camera position and depth information reduce so considerably the risk of false alarms. Positioned vertically above the ground, the camera makes it possible to analyze the scene especially for tracking the silhouette without major occlusion, which in some cases lead to false alarms. In addition, the various criteria for fall detection, are reliable characteristics for distinguishing the fall of a person, from squatting or sitting. Nevertheless, the angle of the camera remains a problem because it is not large enough to cover a large surface. A solution to this dilemma would be to fix a lens on the objective of the Kinect for the enlargement of the field of view and monitored area.