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See detailThe LNQ25 and ELN PVT Metrics Exhibit a Good Sensitivity to Sleep Deprivation and are Independent from the Subject
Latour, Philippe ULiege; Van Droogenbroeck, Marc ULiege

Poster (2017, October 09)

Introduction Performance of people undergoing critical tasks (like driving) may be impaired completely by the lowering of their vigilance level, due to sleep deprivation for instance. This reduction of ... [more ▼]

Introduction Performance of people undergoing critical tasks (like driving) may be impaired completely by the lowering of their vigilance level, due to sleep deprivation for instance. This reduction of performance may be measured by metrics computed from the reaction times (RT) recorded during a 10min Psychomotor Vigilance Test (PVT). Here, we analyze and compare the sensitivity to sleep deprivation and the subject dependent variability of the PVT metrics performance, with a special emphasis on the time interval sizes. Materials and Methods Individuals (22 volunteers; 11 males, 11 females, mean 22.2y., range 19-34 years) follow an uninterrupted 28h sleep deprivation standard PVT protocol during which they achieved two groups of three PVT sessions (in different conditions). The first PVT of each group is in Non-SDP condition (9h30 and 10h30 Day 1) and the second and third PVT of each group are in SDP condition (2h30, 3h30, 10h30 and 11h30 day 2). The subjects fill a sleep journal during the week before the experiment. We checked that they had a normal sleep-wake cycle with no sleep deprivation, jet-lag or shift work and no medication. During the PVT of the first group, the subjects were wearing the glasses of the Phasya’s Drowsimeter. We compute the usual PVT metrics; meanRT, meanRS (Reaction Speed) and LN500 (500ms lapses number). We also compute LNQ25 (adaptive lapses number computed with a subject dependent threshold) and ELN (Expected Lapse Number, computed from a subject-dependent estimation of the lapse probability). Results We use the “Effect Size” (ES, ratio of the mean by the standard deviation of the difference of metrics in the SDP and Non-SDP conditions) to assess the sensitivity to sleep deprivation. For the 10min (resp. 1min, 3min) interval, the ES of LNQ25 and ELN are respectively 1.38 (resp. 0.95, 1.22) and 1.35 (resp. 0.85, 1.14), the ES of meanRS, meanRT and LN500 are 1.23 (resp. 0.91, 1.09), 0.81 (resp. 0.54, 0.68) and 0.85 (resp. 0.63, 0.77). We classify the intervals on which metrics are computed as SDP or non-SDP. We use a fixed threshold for the metrics, independent of the subject. In the ROC curves, the TPR (for a FPR of 10%) assesses the quality of the classification, and then also the subject independence. For the 10min (resp. 1min, 3min) interval, the TPR of LNQ25 and ELN are respectively 0.86 (resp. 0.56, 0.75) and 0.83 (resp. 0.58, 0.75), the TPR of meanRS, meanRT and LN500 are 0.42 (resp. 0.38, 0.41), 0.40 (resp. 0.39, 0.40) and 0.42 (resp. 0.24, 0.30). Conclusions We demonstrate that LNQ25 and ELN enable a quite good classification of the SDP condition for time intervals greater than or equal to 3min, independently of the subject. On the other hand, these metrics provide also a good sensitivity to sleep deprivation. They outperform the usual metrics for both criteria. For time intervals below 3min, the performances degrade first progressively and then much more quickly below 1min. [less ▲]

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See detailIs a Memoryless Motion Detection Truly Relevant for Background Generation with LaBGen?
Laugraud, Benjamin ULiege; Van Droogenbroeck, Marc ULiege

in Advanced Concepts for Intelligent Vision Systems (2017, September)

The stationary background generation problem consists in generating a unique image representing the stationary background of a given video sequence. The LaBGen background generation method combines a ... [more ▼]

The stationary background generation problem consists in generating a unique image representing the stationary background of a given video sequence. The LaBGen background generation method combines a pixel-wise median filter and a patch selection mechanism based on a motion detection performed by a background subtraction algorithm. In our previous works related to LaBGen, we have shown that, surprisingly, the frame difference algorithm provides the most effective motion detection on average. Compared to other background subtraction algorithms, it detects motion between two frames without relying on additional past frames, and is therefore memoryless. In this paper, we experimentally check whether the memoryless property is truly relevant for LaBGen, and whether the effective motion detection provided by the frame difference is not an isolated case. For this purpose, we introduce LaBGen-OF, a variant of LaBGen leverages memoryless dense optical flow algorithms for motion detection. Our experiments show that using a memoryless motion detector is an adequate choice for our background generation framework, and that LaBGen-OF outperforms LaBGen on the SBMnet dataset. We further provide an open-source C++ implementation of both methods at http://www.telecom.ulg.ac.be/labgen. [less ▲]

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See detailSemantic Background Subtraction
Braham, Marc ULiege; Pierard, Sébastien ULiege; Van Droogenbroeck, Marc ULiege

in IEEE International Conference on Image Processing (ICIP), Beijing 17-20 September 2017 (2017, September)

We introduce the notion of semantic background subtraction, a novel framework for motion detection in video sequences. The key innovation consists to leverage object-level semantics to address the variety ... [more ▼]

We introduce the notion of semantic background subtraction, a novel framework for motion detection in video sequences. The key innovation consists to leverage object-level semantics to address the variety of challenging scenarios for background subtraction. Our framework combines the information of a semantic segmentation algorithm, expressed by a probability for each pixel, with the output of any background subtraction algorithm to reduce false positive detections produced by illumination changes, dynamic backgrounds, strong shadows, and ghosts. In addition, it maintains a fully semantic background model to improve the detection of camouflaged foreground objects. Experiments led on the CDNet dataset show that we managed to improve, significantly, almost all background subtraction algorithms of the CDNet leaderboard, and reduce the mean overall error rate of all the 34 algorithms (resp. of the best 5 algorithms) by roughly 50% (resp. 20%). Note that a C++ implementation of the framework is available at http://www.telecom.ulg.ac.be/semantic. [less ▲]

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See detailA two-step methodology for human pose estimation increasing the accuracy and reducing the amount of learning samples dramatically
Azrour, Samir ULiege; Pierard, Sébastien ULiege; Geurts, Pierre ULiege et al

in Advanced Concepts for Intelligent Vision Systems (2017, September)

In this paper, we present a two-step methodology to improve existing human pose estimation methods from a single depth image. Instead of learning the direct mapping from the depth image to the 3D pose, we ... [more ▼]

In this paper, we present a two-step methodology to improve existing human pose estimation methods from a single depth image. Instead of learning the direct mapping from the depth image to the 3D pose, we first estimate the orientation of the standing person seen by the camera and then use this information to dynamically select a pose estimation model suited for this particular orientation. We evaluated our method on a public dataset of realistic depth images with precise ground truth joints location. Our experiments show that our method decreases the error of a state-of-the-art pose estimation method by 30%, or reduces the size of the needed learning set by a factor larger than 10. [less ▲]

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See detailNew PVT Metrics with an Improved Sensitivity to Sleep Deprivation: Analysis from Short to Long Time Intervals
Latour, Philippe ULiege; Van Droogenbroeck, Marc ULiege

in Managing Fatigue 2017 - Online Proceedings - http://fatigueconference2017.com/presentations.html (2017, March 20)

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See detailProbabilistic Framework for the Characterization of Surfaces and Edges in Range Images, with Application to Edge Detection
Lejeune, Antoine ULiege; Verly, Jacques ULiege; Van Droogenbroeck, Marc ULiege

in IEEE Transactions on Pattern Analysis & Machine Intelligence (2017)

We develop a powerful probabilistic framework for the local characterization of surfaces and edges in range images, which is useful in many applications of computer vision, such as filtering, edge ... [more ▼]

We develop a powerful probabilistic framework for the local characterization of surfaces and edges in range images, which is useful in many applications of computer vision, such as filtering, edge detection, feature extraction, and classification. We use the geometrical nature of the data to derive an analytic expression for the joint probability density function (pdf) for the random variables used to model the ranges of a set of pixels in a local neighborhood of an image. We decompose this joint pdf by considering independently the cases where two real world points corresponding to two neighboring pixels are locally on the same real world surface or not. In particular, we show that this joint pdf is linked to the Voigt pdf and not to the Gaussian pdf as it is assumed in some applications. We apply our framework to edge detection and develop a locally adaptive algorithm that is based on a probabilistic decision rule. We show in an objective evaluation that this new edge detector performs better than prior art edge detectors. This proves the benefits of the probabilistic characterization of the local neighborhood as a tool to improve applications that involve range images. [less ▲]

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See detailLaBGen: A method based on motion detection for generating the background of a scene
Laugraud, Benjamin ULiege; Pierard, Sébastien ULiege; Van Droogenbroeck, Marc ULiege

in Pattern Recognition Letters (2017), 96

Given a video sequence acquired with a fixed camera, the generation of the stationary background of the scene is a challenging problem which aims at computing a reference image for a motionless background ... [more ▼]

Given a video sequence acquired with a fixed camera, the generation of the stationary background of the scene is a challenging problem which aims at computing a reference image for a motionless background. For that purpose, we developed our method named LaBGen, which emerged as the best one during the Scene Background Modeling and Initialization (SBMI) workshop organized in 2015, and the IEEE Scene Background Modeling Contest (SBMC) organized in 2016. LaBGen combines a pixel-wise temporal median filter and a patch selection mechanism based on motion detection. To detect motion, a background subtraction algorithm decides, for each frame, which pixels belong to the background. In this paper, we describe the LaBGen method extensively, evaluate it on the SBI 2016 dataset and compare its performance with other background generation methods. We also study its computational complexity, the performance sensitivity with respect to its parameters, and the stability of the predicted background image over time with respect to the chosen background subtraction algorithm. We provide an open source C++ implementation at http://www.telecom.ulg.ac.be/labgen. [less ▲]

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See detailVIP: Vortex Image Processing package for high-contrast direct imaging
Gómez González, Carlos ULiege; Wertz, Olivier; Absil, Olivier ULiege et al

in Astronomical Journal (The) (2017)

We present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to ... [more ▼]

We present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular di↵erential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompass- ing pre- and post-processing algorithms, potential sources position and flux estimation, and sensitivity curves generation. Among the reference point-spread function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithm capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization (NMF), which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP we investigated the presence of additional companions around HR8799 and did not find any significant additional point source beyond the four known planets. VIP is available at http://github.com/vortex-exoplanet/VIP and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library. [less ▲]

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See detailLaBGen-P: A Pixel-Level Stationary Background Generation Method Based on LaBGen
Laugraud, Benjamin ULiege; Pierard, Sébastien ULiege; Van Droogenbroeck, Marc ULiege

in 2016 International Conference on Pattern Recognition Contest Proceedings (2016, December)

Estimating the stationary background of a video sequence is useful in many applications like surveillance, segmentation, compression, inpainting, privacy protection, and computational photography. To ... [more ▼]

Estimating the stationary background of a video sequence is useful in many applications like surveillance, segmentation, compression, inpainting, privacy protection, and computational photography. To perform this task, we introduce the LaBGen-P method based on the principles of LaBGen and the conclusions drawn in the corresponding paper. It combines a pixel-wise median filter and a pixel selection mechanism based on a motion detection performed by the frame difference algorithm. By working with pixels instead of patches, as originally done in LaBGen, it avoids some discontinuities between different spatial areas and generates better visual results. In this paper, we describe the LaBGen-P method, study its performance on the sequences of the SBMnet dataset, and compare it to that of LaBGen and other methods on the same dataset. Both algorithms emerged as the best ones during the IEEE Scene Background Modeling Contest (SBMC) organized in 2016. However, as there is not yet a good understanding of the recommended metrics, and due to the small amount of video sequences provided with the corresponding ground truth, we have performed a subjective evaluation. More precisely, 35 human experts were asked to compare background images estimated by LaBGen-P and LaBGen, and select the best one. From these experiments, it turns out that the results of LaBGen-P are preferred for about two thirds of the video sequences. Note that we provide an open-source C++ implementation at http://www.telecom.ulg.ac.be/labgen. [less ▲]

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See detailWhat are the optimal walking tests to assess disability progression?
Pierard, Sébastien ULiege; Van Droogenbroeck, Marc ULiege

in Multiple Sclerosis Journal (2016, September 16), 22(S3), 452-453

Background. Therapy success is assumed when there is no evidence of disease activity. Clues to show it include an MRI, the relapses history, questionnaires, and clinical measures to assess the disability ... [more ▼]

Background. Therapy success is assumed when there is no evidence of disease activity. Clues to show it include an MRI, the relapses history, questionnaires, and clinical measures to assess the disability progression. Especially gait analysis plays a major role as gait impairment is considered by patients as the most disabling symptom. Too often only the walking speed is measured. New technologies (eg GAIMS, see ECTRIMS 2012-15) measure many spatiotemporal gait parameters, even during long tests (\eg 6min, 500m), without equipping patients with markers or sensors. Moreover, various tests can be done, depending on the length and type of walk (comfortable pace --C--, as fast as possible --F--, tandem gait --T--). Objective. Determine if there is an advantage to perform various walking tests, and which test or combination of tests brings the higher amount of information about the patient state in a reasonable amount of acquisition time. Methods. The system GAIMS provided 434 recordings of the gait parameters of healthy people and 60 recordings of MS patients with EDSS<= 4. They performed 12 tests (25ft C+F+T each twice, 20m C+F+T, 100m C+F, 500m F). To assess the ability of these clinical outcome measures to detect disability progression, we evaluate the possibility of differentiating the persons below a given EDSS threshold (0.25) from those above it based only on the measured gait parameters. For individual tests, we use the classifier of Azrour (ESANN 2014). All subsets of the tests are also considered, by combining the individual classifiers and determining automatically the optimal relative importance of the tests with the linear support vector machine (SVM) technique. The ability to detect the disability progression is quantified by the performance (area under the ROC curve --AUC-- and the maximum achievable balanced accuracy --MBA--) of the corresponding classifiers. Results. The best test alone is the 500m F (note that the walking speed measured during it is the gait parameter best correlated with the EDSS). Combining several tests leads to a better performance. A performance (MBA=95.7%, AUC=0.983) close to the best achievable one can be obtained with 6 tests only (25ft C twice, 25tf F twice, 20m C, 20m T). Conclusions. The clinical gait analysis can help to detect disability progression. While considering different types of walking tests improves the ability of taking decisions, we showed that performing 6 tests for a total of 70.48m suffices. [less ▲]

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See detailBackground subtraction and background generation
Van Droogenbroeck, Marc ULiege

Conference (2016, August 15)

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See detailEnhancing Cover Song Identification with Hierarchical Rank Aggregation
Osmalsky, Julien ULiege; Van Droogenbroeck, Marc ULiege; Embrechts, Jean-Jacques ULiege

in Proceedings of the 17th International for Music Information Retrieval Conference (2016, August)

Abstract Cover song identification involves calculating pairwise similarities between a query audio track and a database of reference tracks. While most authors make exclusively use of chroma features ... [more ▼]

Abstract Cover song identification involves calculating pairwise similarities between a query audio track and a database of reference tracks. While most authors make exclusively use of chroma features, recent work tends to demonstrate that combining similarity estimators based on multiple audio features increases the performance. We improve this approach by using a hierarchical rank aggregation method for combining estimators based on different features. More precisely, we first aggregate estimators based on global features such as the tempo, the duration, the loudness, the beats, and the average chroma vectors. Then, we aggregate the resulting composite estimator with four popular state-of-the-art methods based on chromas as well as timbre sequences. We further introduce a refinement step for the rank aggregation called “local Kemenization” and quantify its benefit for cover song identification. The performance of our method is evaluated on the Second Hand Song dataset. Our experiments show an significant improvement of the performance, up to an increase of more than 200 % of the number of queries identified in the Top-1, compared to previous results. [less ▲]

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See detailLeveraging orientation knowledge to enhance human pose estimation methods
Azrour, Samir ULiege; Pierard, Sébastien ULiege; Van Droogenbroeck, Marc ULiege

in Articulated Motion and Deformable Objects AMDO 2016 (2016, July)

Predicting accurately and in real-time 3D body joint positions from a depth image is the cornerstone for many safety, biomedical, and entertainment applications. Despite the high quality of the depth ... [more ▼]

Predicting accurately and in real-time 3D body joint positions from a depth image is the cornerstone for many safety, biomedical, and entertainment applications. Despite the high quality of the depth images, the accuracy of existing human pose estimation methods from single depth images remains insufficient for some applications. In order to enhance the accuracy, we suggest to leverage a rough orientation estimation to dynamically select a 3D joint position prediction model specialized for this orientation. This orientation estimation can be obtained in real-time either from the image itself, or from any other clue like tracking. We demonstrate the merits of this general principle on a pose estimation method similar to the one used with Kinect cameras. Our results show that the accuracy is improved by up to 45.1 %, with respect to a method using the same model for all orientations. [less ▲]

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See detailBoosting shape classifiers accuracy by considering the inverse shape
Pierard, Sébastien ULiege; Lejeune, Antoine ULiege; Van Droogenbroeck, Marc ULiege

in Journal of Pattern Recognition Research (2016), 11(1), 41-54

Many techniques exist for describing shapes. These techniques almost exclusively consider the contour or the inside of the shape; the major problem for describing the outside of a shape, or inverse shape ... [more ▼]

Many techniques exist for describing shapes. These techniques almost exclusively consider the contour or the inside of the shape; the major problem for describing the outside of a shape, or inverse shape, being that it has an infinite extension. In this paper, we show how to adapt two shape descriptors, one region based, the Cover By Rectangles, and one transform based, the Zernike moments, to be applicable to the inverse shape. We analyze their properties, and show how to deal with the infinite extension of the inverse shape. Then, we apply these descriptors to shape classification and compare representations that use the shape, its inverse, or both. Our experiments establish that, for shape classification, a representation integrating the inverse shape often outperforms a representation restricted to the shape. This opens the path for better techniques that could use, as a rule of thumb, both the representations of a shape and its inverse for the purpose of classification. [less ▲]

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See detailImproving pose estimation by building dedicated datasets and using orientation
Azrour, Samir ULiege; Pierard, Sébastien ULiege; Van Droogenbroeck, Marc ULiege

Poster (2016, May 19)

Markerless pose estimation systems are useful for various applications including human- computer interaction, activity recognition, security, gait analysis, and computer-assisted medical interventions ... [more ▼]

Markerless pose estimation systems are useful for various applications including human- computer interaction, activity recognition, security, gait analysis, and computer-assisted medical interventions. They have attracted much interest since the release of low-cost depth cameras such as Microsoft’s Kinect camera. Shotton et al. and Girshick et al. pioneered tractable methods that infer a full-body pose reconstruction in real-time. Despite this technological breakthrough, the accuracy of human pose estimation from single depth images remains insufficient for some applications. Our work aims at building a simulation environment to create images databases suited for any camera position and improving the mainstream machine learning-based pose estimation algorithms. [less ▲]

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See detailDeep Background Subtraction with Scene-Specific Convolutional Neural Networks
Braham, Marc ULiege; Van Droogenbroeck, Marc ULiege

in IEEE International Conference on Systems, Signals and Image Processing (IWSSIP), Bratislava 23-25 May 2016 (2016, May)

Background subtraction is usually based on low-level or hand-crafted features such as raw color components, gradients, or local binary patterns. As an improvement, we present a background subtraction ... [more ▼]

Background subtraction is usually based on low-level or hand-crafted features such as raw color components, gradients, or local binary patterns. As an improvement, we present a background subtraction algorithm based on spatial features learned with convolutional neural networks (ConvNets). Our algorithm uses a background model reduced to a single background image and a scene-specific training dataset to feed ConvNets that prove able to learn how to subtract the background from an input image patch. Experiments led on 2014 ChangeDetection.net dataset show that our ConvNet based algorithm at least reproduces the performance of state-of-the-art methods, and that it even outperforms them significantly when scene-specific knowledge is considered. [less ▲]

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See detailLow-rank plus sparse decomposition for exoplanet detection in direct-imaging ADI sequences. The LLSG algorithm
Gómez González, Carlos ULiege; Absil, Olivier ULiege; Absil, P.-A. et al

in Astronomy and Astrophysics (2016), 589

Context. Data processing constitutes a critical component of high-contrast exoplanet imaging. Its role is almost as important as the choice of a coronagraph or a wavefront control system, and it is ... [more ▼]

Context. Data processing constitutes a critical component of high-contrast exoplanet imaging. Its role is almost as important as the choice of a coronagraph or a wavefront control system, and it is intertwined with the chosen observing strategy. Among the data processing techniques for angular differential imaging (ADI), the most recent is the family of principal component analysis (PCA) based algorithms. It is a widely used statistical tool developed during the first half of the past century. PCA serves, in this case, as a subspace projection technique for constructing a reference point spread function (PSF) that can be subtracted from the science data for boosting the detectability of potential companions present in the data. Unfortunately, when building this reference PSF from the science data itself, PCA comes with certain limitations such as the sensitivity of the lower dimensional orthogonal subspace to non-Gaussian noise. <BR /> Aims: Inspired by recent advances in machine learning algorithms such as robust PCA, we aim to propose a localized subspace projection technique that surpasses current PCA-based post-processing algorithms in terms of the detectability of companions at near real-time speed, a quality that will be useful for future direct imaging surveys. <BR /> Methods: We used randomized low-rank approximation methods recently proposed in the machine learning literature, coupled with entry-wise thresholding to decompose an ADI image sequence locally into low-rank, sparse, and Gaussian noise components (LLSG). This local three-term decomposition separates the starlight and the associated speckle noise from the planetary signal, which mostly remains in the sparse term. We tested the performance of our new algorithm on a long ADI sequence obtained on β Pictoris with VLT/NACO. <BR /> Results: Compared to a standard PCA approach, LLSG decomposition reaches a higher signal-to-noise ratio and has an overall better performance in the receiver operating characteristic space. This three-term decomposition brings a detectability boost compared to the full-frame standard PCA approach, especially in the small inner working angle region where complex speckle noise prevents PCA from discerning true companions from noise. [less ▲]

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See detailQuand les ondes électromagnétiques vous informent !
Van Droogenbroeck, Marc ULiege

Conference given outside the academic context (2015)

Introduction aux techniques de télécommunications et transmission par ondes électromagnétiques

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See detailDefining a score based on gait analysis for the longitudinal follow-up of MS patients
Azrour, Samir ULiege; Pierard, Sébastien ULiege; Van Droogenbroeck, Marc ULiege

in Multiple Sclerosis Journal (2015, October 09), 23(S11), 408-409

BACKGROUND. The project GAIMS [ECTRIMS 2013 P800] aims at developing a gait measuring system particularily suited for the clinical routine, and providing a reference database with the gait characteristics ... [more ▼]

BACKGROUND. The project GAIMS [ECTRIMS 2013 P800] aims at developing a gait measuring system particularily suited for the clinical routine, and providing a reference database with the gait characteristics of many MS patients (MSP) and healthy people (HP). As the gait impairments are related to the disease progression, defining an objective and quantitative score based on the gait characteristics would be useful for the longitudinal follow-up. Based on the dataset of GAIMS and machine learning techniques (MLT), a score, well correlated with the EDSS, can be defined [Azrour et al. ESANN 2014]. OBJECTIVE. Burggraaff et al. [ECTRIMS 2014 P033] showed that paired comparisons can help human raters to better judge the state of the patients. In the same spirit, we aim at predicting the difference of EDSS between two persons or between two visits of a same person, based on clinical gait measures. We show that the pairwise comparison strategy leads to a score (Gait-Score) well correlated with the EDSS and sensitive to small modifications of the gait. METHODS. The gait of 162 HP and 72 MSP (44 with EDSS>3) has been recorded and analyzed with GAIMS. The Gait-Score is defined using the MLT of [Geurts et al. 2006]. We can compute the Gait-Score of a person by comparing him to others with known EDSS, and compute the difference of Gait-Score of a same person at two different moments. We measure the merits of the Gait-Score by the correlation between the predicted Gait-Score and the EDSS, as well as the ability to detect subtle gait deteriorations among people with ataxia induced by a low dose of alcohol (data of [Piérard et al. ESANN 2014]). RESULTS. The Gait-Score is well correlated with the EDSS (Pearson’s correlation=0.8743). Moreover, it manages to detect a gait deterioration after a small alcohol intake for 19 persons out of 24 (79% correct) which is much better than what was obtained by visual inspection of neurologists (62% according to [Piérard et al. ESANN 2014]). CONCLUSIONS. Based on the accurate gait measures provided by GAIMS, we are able to derive a Gait-Score, automatically, that is well correlated with the EDSS. Moreover, this score is able to detect subtle deteriorations of the gait caused by a low dose of alcohol. These results reinforce our conviction that the use of an automatic method based on gait analysis is very promising for the longitudinal follow-up of MS patients and the assessment of the impact of new drugs and rehabilitation programs. [less ▲]

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