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261 results on '"Meriaudeau, F."'

7. Active Disturbance Rejection Control Based Sinusoidal Trajectory Tracking for an Upper Limb Robotic Rehabilitation Exoskeleton

Author

Aole, S, Elamvazuthi, I, Waghmare, L, Patre, B, Bhaskarwar, T, Meriaudeau, F, Su, S, Aole, S, Elamvazuthi, I, Waghmare, L, Patre, B, Bhaskarwar, T, Meriaudeau, F, and Su, S

Abstract

In this paper, a combined control strategy with extended state observer (ESO) and finite time stable tracking differentiator (FTSTD) has been proposed to perform flexion and extension motion repetitively and accurately in the sagittal plane for shoulder and elbow joints. The proposed controller improves the tracking accuracy, performs state estimation, and actively rejects disturbance. A sinusoidal trajectory as an input has been given to a two-link multiple-input multiple-output (MIMO) upper limb robotic rehabilitation exoskeleton (ULRRE) for a passive rehabilitation purpose. The efficacy of the controller has been tested with the help of performance indices such as integral time square error (ITSE), integral square error (ISE), integral time absolute error (ITAE), and integral of the absolute magnitude of error (IAE). The system model is obtained through the Euler–Lagrangian method, and the controller’s stability is also given. The proposed controller has been simulated for ±20% parameter variation with constant external disturbances to test the disturbance rejection ability and robustness against parametric uncertainties. The proposed controller has been compared with already developed ESO-based methods such as active disturbance rejection control (ADRC), nonlinear active disturbance rejection control (NLADRC), and improved active disturbance rejection control (I-ADRC). It has been found that the proposed method increases tracking performance, as evidenced by the above performance indices.

Published
2022

18. Studying the response of drivers against different collision warning systems: a review

Author

Nagahara, Hajime, Umeda, Kazunori, Yamashita, Atsushi, Muzammel, M., Yusoff, M. Zuki, Malik, A. Saeed, Mohamad Saad, M. Naufal, Meriaudeau, F., Centre Européen de Réalité Virtuelle (CERV), École Nationale d'Ingénieurs de Brest (ENIB), Centre for Intelligent Signal and Imaging Research [Petronas] (CISIR), and Universiti Teknologi PETRONAS (UTP)

Subjects
050210 logistics & transportation, Warning system, Computer science, 05 social sciences, Collision system, Rear-end collision, Computer security, computer.software_genre, World health, 3. Good health, 03 medical and health sciences, [SPI]Engineering Sciences [physics], 0302 clinical medicine, Age groups, 0502 economics and business, computer, 030217 neurology & neurosurgery, ComputingMilieux_MISCELLANEOUS
Abstract

The number of vehicle accidents is rapidly increasing and causing significant economic losses in many countries. According to the World Health Organization, road accidents will become the fifth major cause of death by the year 2030. To minimize these accidents different types of collision warning systems have been proposed for motor vehicle drivers. These systems can early detect and warn the drivers about the potential danger, up to a certain accuracy. Many researchers study the effectiveness of these systems by using different methods, including Electroencephalography (EEG). From the literature review, it has been observed that, these systems increase the drivers' response and can help to minimize the accidents that may occur due to drivers unconsciousness. For these collision warning systems, tactile early warnings are found more effective as compared to the auditory and visual early warnings. This review also highlights the areas, where further research can be performed to fully analyze the collision warning system. For example, some contradictions are found among researchers, about these systems' performance for drivers within different age groups. Similarly, most of the EEG studies focus on the front collision warning systems and only give beep sound to alert the drivers. Therefore, EEG study can be performed for the rear end collision warning systems, against proper auditory warning messages which indicate the types of hazards. This EEG study will help to design more friendly collision warning system and may save many lives.

Published
2017

24. Knudsen forces on microcantilevers.

Author

Passian, A., Wig, A., Meriaudeau, F., Ferrell, T. L., and Thundat, T.

Subjects
MICROELECTROMECHANICAL systems, ATOMIC force microscopy, VACUUM-gages
Abstract

When two surfaces at two different temperatures are separated by a distance comparable to a mean-free path of the molecules of the ambient medium, the surfaces experience Knudsen force. This mechanical force can be important in microelectromechanical systems and in atomic force microscopy. A theoretical discussion of the magnitude of the forces and the conditions where they can be encountered is discussed. A potential application of the Knudsen force in designing a cantilever-based vacuum gauge is discussed. [ABSTRACT FROM AUTHOR]

Published
2002
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28. Facial geometry and speech analysis for depression detection

Author

Pampouchidou, A., primary, Simantiraki, O., additional, Vazakopoulou, C. - M., additional, Chatzaki, C., additional, Pediaditis, M., additional, Maridaki, A., additional, Marias, K., additional, Simos, P., additional, Yang, F., additional, Meriaudeau, F., additional, and Tsiknakis, M., additional

Published
2017
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32. Classification of SD-OCT Volumes Using Local Binary Patterns: Experimental Validation for DME Detection

Author

Lemaitre, G, Rastgoo, M, Massich, J, Cheung, CY, Wong, TY, Lamoureux, E, Milea, D, Meriaudeau, F, Sidibe, D, Lemaitre, G, Rastgoo, M, Massich, J, Cheung, CY, Wong, TY, Lamoureux, E, Milea, D, Meriaudeau, F, and Sidibe, D

Abstract

This paper addresses the problem of automatic classification of Spectral Domain OCT (SD-OCT) data for automatic identification of patients with DME versus normal subjects. Optical Coherence Tomography (OCT) has been a valuable diagnostic tool for DME, which is among the most common causes of irreversible vision loss in individuals with diabetes. Here, a classification framework with five distinctive steps is proposed and we present an extensive study of each step. Our method considers combination of various preprocessing steps in conjunction with Local Binary Patterns (LBP) features and different mapping strategies. Using linear and nonlinear classifiers, we tested the developed framework on a balanced cohort of 32 patients. Experimental results show that the proposed method outperforms the previous studies by achieving a Sensitivity (SE) and a Specificity (SP) of 81.2% and 93.7%, respectively. Our study concludes that the 3D features and high-level representation of 2D features using patches achieve the best results. However, the effects of preprocessing are inconsistent with different classifiers and feature configurations.

Published
2016

33. Demonstration of surface plasmons in metal island films and the effect of the surrounding medium---An undergraduate experiment

Author

Orfanides, P., Buckner, T. F., Buncick, M. C., Meriaudeau, F., and Ferrell, T. L.

Subjects
Surfaces -- Research, Plasmons (Physics) -- Research, Dielectric films -- Research, Physics
Abstract

We present a demonstration of the surface plasmon phenomenon as it occurs in thin metal island films. The metal films are deposited on glass microscope slides. The effect of the surface plasmon resonance may be observed visually on the slide without further apparatus. Heating the film changes the shape of the islands and therefore the resonant frequency of the surface plasmon and changes the color of the film. Placing the film in a dielectric medium changes the resonance condition for the surface plasmon again and changes the color again. We show this by coating the slides with commercially available liquids with different indices of refraction. We present a theoretical model that assumes the islands are oblate spheroids. There are enough details given so that the equations can be programed and the theoretical optical absorbance can be reproduced. We also present a modification to the theory so that the shift in resonant frequency can be calculated when the spheroids are immersed in the index fluids. We describe our apparatus for making thin films and our optical spectrometer system. We then present optical absorbance measurements of thin films of both Ag and Au in air and in two liquids with different indices of refraction. [C] 2000 American Association of Physics Teachers.

Published
2000

38. Graph Cut Energy Minimization in a Probabilistic Learning Framework for 3D Prostate Segmentation in MRI

Author

Ghose, S., Mitra, J., Oliver, A., Robert Martí, Llado, X., Freixenet, J., Vilanova, J. C., Sidibe, D., Meriaudeau, F., Ghose, Soumya, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Visio per computador i robotica ( VICOROB ), Universitat de Girona ( UdG ), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Visio per computador i robotica (VICOROB), and Universitat de Girona (UdG)

Subjects
[ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging
Abstract

International audience; Variations in inter-patient prostate shape, and size and imaging artifacts in magnetic resonance images (MRI) hinders automatic accurate prostate segmentation. In this paper we propose a graph cut based energy minimization of the posterior probabilities obtained in a supervised learning schema for automatic 3D segmentation of the prostate in MRI. A probabilistic classification of the prostate voxels is achieved with a probabilistic atlas and a random forest based learning framework. The posterior probabilities are combined to obtain the likelihood of a voxel being prostate. Finally, 3D graph cut based energy minimization in the stochastic space provides segmentation of the prostate. The proposed method achieves a mean Dice similarity coefficient (DSC) value of 0.91±0.04 and 95% mean Hausdorff distance (HD) of 4.69±2.62 voxels when validated with 15 prostate volumes of a public dataset in a leave-one-patient-out validation framework. The model achieves statistically significant t-test p-value

Published
2012

44. Elliptical local vessel density: a fast and robust quality metric for retinal images

Author

Luca Giancardo, Abràmoff, M. D., Chaum, E., Karnowski, T. P., Meriaudeau, F., and Tobin Jr, K. W.

Subjects
Geneeskunde, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Abstract

A great effort of the research community is geared towards the creation of an automatic screening system able to promptly detect diabetic retinopathy with the use of fundus cameras. In addition, there are some documented approaches for automatically judging the image quality. We propose a new set of features independent of field of view or resolution to describe the morphology of the patient's vessels. Our initial results suggest that these features can be used to estimate the image quality in a time one order of magnitude shorter than previous techniques.

Published
2008

47. Novel health monitoring method an using RGB camera

Author

Hassan, M. A., Malik, A. S., Fofi, D., Saad, N., and Meriaudeau, F.

Abstract

In this paper we present a novel health monitoring method by estimating the heart rate and respiratory rate using an RGB camera. The heart rate and the respiratory rate are estimated from the photoplethysmography (PPG) and the respiratory motion. The method mainly operates by using the green spectrum of the RGB camera to generate a multivariate PPG signal to perform multivariate de-noising on the video signal to extract the resultant PPG signal. A periodicity based voting scheme (PVS) was used to measure the heart rate and respiratory rate from the estimated PPG signal. We evaluated our proposed method with a state of the art heart rate measuring method for two scenarios using the MAHNOB-HCI database and a self collected naturalistic environment database. The methods were furthermore evaluated for various scenarios at naturalistic environments such as a motion variance session and a skin tone variance session. Our proposed method operated robustly during the experiments and outperformed the state of the art heart rate measuring methods by compensating the effects of the naturalistic environment.

Published
2017

48. Detecting global and local hippocampal shape changes in Alzheimer's disease using statistical shape models.

Author

Shen, K.K., Fripp, J., Meriaudeau, F., Chetelat, G., Salvado, O., Bourgeat, P., Olde Rikkert, M., et al., Shen, K.K., Fripp, J., Meriaudeau, F., Chetelat, G., Salvado, O., Bourgeat, P., Olde Rikkert, M., and et al.

Abstract

Item does not contain fulltext, The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). With the use of structural magnetic resonance (MR) imaging, we can investigate the effect of AD on the morphology of the hippocampus. The hippocampal shape variations among a population can be usually described using statistical shape models (SSMs). Conventional SSMs model the modes of variations among the population via principal component analysis (PCA). Although these modes are representative of variations within the training data, they are not necessarily discriminative on labeled data or relevant to the differences between the subpopulations. We use the shape descriptors from SSM as features to classify AD from normal control (NC) cases. In this study, a Hotelling's T2 test is performed to select a subset of landmarks which are used in PCA. The resulting variation modes are used as predictors of AD from NC. The discrimination ability of these predictors is evaluated in terms of their classification performances with bagged support vector machines (SVMs). Restricting the model to landmarks with better separation between AD and NC increases the discrimination power of SSM. The predictors extracted on the subregions also showed stronger correlation with the memory-related measurements such as Logical Memory, Auditory Verbal Learning Test (AVLT) and the memory subscores of Alzheimer Disease Assessment Scale (ADAS).

Published
2012

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