Laurent Oudre

• PhD
• Professor (Full) at Ecole Normale Supérieure Paris-Saclay

Motif Discovery consists of finding repeated patterns and locating their occurrences in a time series without prior knowledge about their shape or location. Most state-of-the-art algorithms rely on three core parameters: the number of motifs to discover, the length of the motifs, and a similarity threshold between motif occurrences. Setting these p...

Background Onasemnogene abeparvovec gene replacement therapy (GT) has changed the prognosis of patients with spinal muscular atrophy (SMA) with variable outcome regarding motor development in symptomatic patients. This pilot study evaluates acceptability, validity and clinical relevance of Inertial Measurement Units (IMU) to monitor spontaneous mov...

Introduction This study evaluates the gait analysis obtained by Inetial Measurement Units (IMU) before and after surgical management of Spastic Equino Varus Foot (SEVF) in hemiplegic post-stroke patients and to compare it with the functional results obtained in a monocentric prospective cohort. Methods Patients with post-stroke SEVF, who underwent...

Background: Precise monitoring of the Depth of Anesthesia (DoA) is essential to prevent intra-operative awareness (in case of underdosage) or increased post-operative morbi-mortality (in case of overdosage). The recording of a high-frequency multimodal monitoring during general anesthesia (GA) and the capability of classification of dynamic network...

Background Recently, the use of inertial measurement units (IMUs) in quantitative gait analysis has been widely developed in clinical practice. Numerous methods have been developed for the automatic detection of gait events (GEs). While many of them have achieved high levels of efficiency in healthy subjects, detecting GEs in highly degraded gait f...

Exploring and comparing non-stationary multivariate time series is an important problem in many domains and real-world applications. In recent work, we introduced d_symb, a symbolic representation that transforms multivariate time series into interpretable symbolic sequences that come along with a compatible and efficient distance measure to compar...

The increasing use of inertial measurement units (IMU) in biomedical sciences brings new possibilities for clinical research. The aim of this paper is to demonstrate the accuracy of the IMU-based wearable Syde® device, which allows day-long and remote continuous gait recording in comparison to a reference motion capture system. Twelve healthy subje...

This article describes a non-parametric clustering algorithm with an outlier removal step. Our method is based on tools from topological data analysis: we define a new filtration on metric spaces which is a variant of the Vietoris–Rips filtration that adds information about the points' nearest neighbor to the persistence diagram. We prove a stabili...

This article thoroughly describes a data set of 240 multivariate time series collected using 34 Cartesian Optoelectronic Dynamic Anthropometer (CODA) markers placed on the upper limb of 16 healthy subjects each undergoing 15 predefined movements such as raising their arms or combing their hair. Each sensor records its position in the 3D space. In t...

In a recent review, we summarized the characteristics of perceptual-motor style in humans. Style can vary from individual to individual, task to task and pathology to pathology, as sensorimotor transformations demonstrate considerable adaptability and plasticity. Although the behavioral evidence for individual styles is substantial, much remains to...

Background Evaluating executive dysfunction in brain-damaged patients remains a significant challenge in neurology. Current standard neuropsychological tests, although internally valid, often lack ecological validity. The SDS2 study aims to address this limitation and to improve the understanding of executive dysfunction by collecting multi-modal d...

This article provides a comprehensive description of a dataset consisting of 110 multivariate gait signals collected using three inertial measurement units. The data was obtained from a sample of 19 healthy subjects who followed a predefined protocol: standing still, walking 10 meters, turning around, walking back, and stopping. One notable aspect...

Introduction This study evaluates the gait analysis obtained by IMU before and after surgical management of Spastic Equino Varus Foot in hemiplegic post-stroke patients and to compare it with the functional results obtained in a monocentric prospective cohort. Methods Patients with post-stroke equinovarus foot, who underwent surgery in a single hos...

Background Quantifying gait using inertial measurement units has gained increasing interest in recent years. Highly degraded gaits, especially in neurological impaired patients, challenge gait detection algorithms and require specific segmentation and analysis tools. Thus, the outcomes of these devices must be rigorously tested for both robustness...

Dans ce travail, nous tirons parti des principes d'incertitude afin d'introduire une nouvelle méthode d'apprentissage de dictionnaire pour les signaux sur graphe. Notre méthode prend en compte deux classes distinctes d'atomes, les atomes locaux spatialement sur le graphe et les atomes spectralement réguliers introduits avec des fonctions de pénalis...

In this work, we leverage recent graph uncertainty principles to introduce a new dictionary learning method on graphs. Our method considers two distinct classes of atoms, local atoms on the graph, and local atoms spectrally together with well suited penalty functions. Notably, the consideration of the notion of localized atoms on graphs allows to...

Ventilation is a simple physiological function that ensures the vital supply of oxygen and the elimination of CO2. The recording of the airflow through the nostrils of a mouse over time makes it possible to calculate the position of critical points, based on the shape of the signals, to compute the respiratory frequency and the volume of air exchan...

This paper presents a novel approach to creating a graphical summary of a subject’s activity during a protocol in a Semi Free-Living Environment. Thanks to this new visualization, human behavior, in particular locomotion, can now be condensed into an easy-to-read and user-friendly output. As time series collected while monitoring patients in Semi F...

Background: Recently, the use of inertial measurement units (IMUs) in quantitative gait analysis has been widely developed in clinical practice. Numerous methods have been developed for the automatic detection of gait events (GEs). While many of them have achieved high levels of efficiency in healthy subjects, detecting GEs in highly degraded gait...

We introduce ASTRIDE (Adaptive Symbolization for Time seRIes DatabasEs), a novel symbolic representation of time series, along with its accelerated variant FASTRIDE (Fast ASTRIDE). Unlike most symbolization procedures, ASTRIDE is adaptive during both the segmentation step by performing change-point detection and the quantization step by using quant...

Introduction The aim of this study was to realize a systematic review of the different ways, both clinical and instrumental, used to evaluate the effects of the surgical correction of an equinovarus foot (EVF) deformity in post-stroke patients. Methods A systematic search of full-length articles published from 1965 to June 2021 was performed in Pu...

We study the network reconstruction problem for an epidemic reaction–diffusion system. These systems are an extension of deterministic, compartmental models to a graph setting, where the reactions within the nodes are coupled by a diffusion dynamics. We study the influence of the diffusion rate and the network topology, on the reconstruction and pr...

Nowadays, it becomes of paramount societal importance to support many frail-prone groups in our society (elderly, patients with neurodegenerative diseases, etc.) to remain socially and physically active, maintain their quality of life, and avoid their loss of autonomy. Once older people enter the prefrail stage, they are already likely to experienc...

The study of plethysmography time series is crucial to better understand the breathing behavior of mice, in particular the influence of neurotoxins on the respiratory system. Current approaches rely on a few respiratory descriptors computed on individual breathing cycles that fail to account for the variety of breathing habits and their evolution w...

In the past few years, light, affordable wearable inertial measurement units have been providing to clinicians and researchers the possibility to quantitatively study motor degeneracy by comparing gait trials from patients and/or healthy subjects. To do so, standard gait features can be used but they fail to detect subtle changes in several patholo...

Au cours de la dernière décennie, l’intelligence artificielle est devenue non seulement une réalité, mais aussi un sujet de débat dans la société. L’objectif de cet exposé est de déconstruire certaines idées sur l’IA, entre mythes et réalités, en passant en revue l’histoire du domaine et ses principales avancées. La présentation détaillera les prin...

We show we can control an epidemic reaction-diffusion on a directed, and heterogeneous, network by redirecting the flows, thanks to the optimisation of well-designed loss functions, in particular the basic reproduction number of the model. We provide a final size relation linking the basic reproduction number to the epidemic final sizes, for diffus...

In this article, we introduce a novel lower bound on the support size of lowband graph signals. This result allows the deduction of an optimality criterion for the lowband and sparse decomposition of any graph signal, establishing the uniqueness of well behaving solutions. A comparison of the new bound with previously introduced results is performe...

We consider the problem of signal interpolation on graphs, i.e. recovering one or multiple graph signal values from incomplete measurements. We propose a review of the graph signal interpolation methods, which enlightens the restrictive underlying hypothesis of signal smoothness over the graph. We formulate a new interpolation framework based on a...

Measuring the quality of movement is a need and a challenge for clinicians. Jerk, defined as the quantity of acceleration variation, is a kinematic parameter used to assess the smoothness of movement. We aimed to assess and compare jerk metrics in asymptomatic participants for 3 important movement characteristics that are considered by clinicians d...

In this paper, we propose an extension of the standard CDL problem with tensor representation, where each activation is constrained to be ‘'low-rank’' through a Canonical Polyadic decomposition. We show that this important additional constraint increases the robustness of the CDL with respect to strong noise and improve the interpretability of the...

Postural control is often quantified by recording the trajectory of the center of pressure (COP)—also called stabilogram—during human quiet standing. This quantification has many important applications, such as the early detection of balance degradation to prevent falls, a crucial task whose relevance increases with the aging of the population. Due...

This paper presents an innovative method to analyze inertial signals recorded in a semi-controlled environment. It uses an adaptive and supervised change point detection procedure to decompose the signals into homogeneous segments, allowing a refined analysis of the successive phases within a gait protocol. Thanks to a training procedure, the algor...

In this paper, we propose to learn a spatial filter directly from Electroencephalography (EEG) signals using graph signal processing tools. We combine a graph learning algorithm with a high-pass graph filter to remove spatially large signals from the raw data. This approach increases topographical localization, and attenuates volume-conducted featu...

Assessing the depth of anesthesia (DoA) is a daily challenge for anesthesiologists. The best assessment of the depth of anesthesia is commonly thought to be the one made by the doctor in charge of the patient. This evaluation is based on the integration of several parameters including epidemiological, pharmacological and physiological data. By deve...

In this paper, we consider the problem of learning a graph structure from multivariate signals, known as graph signals. Such signals are multivariate observations carrying measurements corresponding to the nodes of an unknown graph, which we desire to infer. They are assumed to enjoy a sparse representation in the graph spectral domain, a feature w...

We study the network reconstruction problem for an epidemic reaction-diffusion. These models are an extension of deterministic, compartmental models to a graph setting, where the reactions within the nodes are coupled by a diffusion. We study the influence of the diffusion rate, and the network topology, on the reconstruction and prediction problem...

Video Stabilization (VS) has been an active area of research in the last two decades. Many approaches have been successfully proposed and it is time to take a step back and offer a glimpse and a critical look to this hot topic. Among the questions that should be answered : ”is VS a solved problem”?. Is there still room for further improvement and a...

The analysis of the Nystagmus waveforms from eye-tracking records is crucial for the clinicial interpretation of this pathological movement. A major issue to automatize this analysis is the presence of natural eye movements and eye blink artefacts that are mixed with the signal of interest. We propose a method based on Convolutional Dictionary Lear...

This article presents an overview of fifty-eight articles dedicated to the evaluation of physical activity in free-living conditions using wearable motion sensors. This review provides a comprehensive summary of the technical aspects linked to sensors (types, number, body positions, and technical characteristics) as well as a deep discussion on the...

Introduction Le traumatisme crânien léger (TCL) est une pathologie fréquente à risque évolutif vers le syndrome post-commotionnel (SPC) comprenant des plaintes somatiques, cognitives, émotionnelles et comportementales. Ce syndrome est souvent difficile à objectiver mais il existe des outils innovants pour quantifier l’examen neurologique. L’objecti...

The increasing number of frail elderly people in our aging society is becoming problematic: about 11% of community‐dwelling older persons are frail and another 42% are pre‐frail. Consequently, a major challenge in the coming years will be to test people over the age of 60 years to detect pre‐frailty at the earliest stage and to return them to robus...

Meta-analysis is a data aggregation method that establishes an overall and objective level of evidence based on the results of several studies. It is necessary to maintain a high level of homogeneity in the aggregation of data collected from a systematic literature review. However, the current tools do not allow a cross-referencing of the experimen...

Recently, there has been growing interest in the analysis of spectrograms of ElectroEncephaloGram (EEG), particularly to study the neural correlates of (un)-consciousness during General Anesthesia (GA). Indeed, it has been shown that order three tensors (channels x frequencies x times) are a natural and useful representation of these signals. Howev...

The analysis of the Nystagmus waveforms from eye-tracking records is crucial for the clinical interpretation of this pathological movement. A major issue to automatize this analysis is the presence of natural eye movements and eye blink artefacts that are mixed with the signal of interest. We propose a method based on Convolutional Dictionary Learn...

Humans exhibit various motor styles that reflect their intra and inter-individual variability when implementing sensorimotor transformations. This opens important questions; such as, at what point should they be readjusted to maintain optimal motor control? Do changes in motor style reveal the onset of a pathological process and can these changes h...

Background: Objective gait assessment is key for the follow-up of patients with progressive multiple sclerosis (pMS). Inertial measurement units (IMUs) provide reliable and yet easy quantitative gait assessment in routine clinical settings. However, to the best of our knowledge, no automated step-detection algorithm performs well in detecting sever...

The automatic detection of gait events (i.e., Initial Contact (IC) and Final Contact (FC)) is crucial for the characterisation of gait from Inertial Measurements Units. In this article, we present a method for detecting steps (i.e., IC and FC) from signals of gait sequences of individuals recorded with a gyrometer. The proposed approach combines th...

Congrès Fragilité du Sujet Agé. Le Vieillissement en Santé. Prévention de la Perte d'Autonomie, Toulouse, FRA, 09-/03/2020 - 10/03/2020

We consider the problem of detecting abrupt changes in the underlying stochastic structure of multivariate signals. A novel non-parametric and model-free off-line change-point detection method based on a kernel mapping is presented. This approach is sequential and alternates between two steps: a greedy detection to estimate a new breakpoint and a p...

Objective: In this paper, we present an original decision support algorithm to assist the anesthesiologists delivery of drugs to maintain the optimal Depth of Anesthesia (DoA). Methods: Derived from a Transform Predictive State Representation algorithm (TPSR), our model learned by observing anesthesiologists in practice. This framework, known as...

In this paper, we consider the problem of learning a graph structure from multivariate signals, known as graph signals. Such signals are multivariate observations carrying measurements corresponding to the nodes of an unknown graph, which we desire to infer. They are assumed to enjoy a sparse representation in the graph spectral domain, a feature w...

This article presents a selective survey of algorithms for the offline detection of multiple change points in multivariate time series. A general yet structuring methodological strategy is adopted to organize this vast body of work. More precisely, detection algorithms considered in this review are characterized by three elements: a cost function,...

This article presents a new approach for processing and subsampling multivariate time-vertex graph signals. The main idea is to model the relationships within each dimension (time, space, feature space) with different graphs and to merge these structures. A new technique based on tensor formalism is provided, which aims to identify the frequency su...

This paper introduces a new multivariate convolutional sparse coding based on tensor algebra with a general model enforcing both element-wise sparsity and low-rankness of the activations tensors. By using the CP decomposition, this model achieves a significantly more efficient encoding of the multivariate signal-particularly in the high order/ dime...

Gait assessment and quantification have received an increased interest in recent years. Embedded technologies and low-cost sensors can be used for the longitudinal follow-up of various populations (neurological diseases, elderly, etc.). However, the comparison of two gait trials remains a tricky question as standard gait features may prove to be in...

In this paper, we present a method for learning an underlying graph topology using observed graph signals as training data. The novelty of our method lies on the combination of two assumptions that are imposed as constraints to the graph learning process: i) the standard assumption used in the literature that signals are smooth with respect to grap...

Introduction Le demi-tour est évalué en routine par le nombre de pas extérieurs et sa durée, ce qui ne rend pas compte de sa cinématique complexe. Nous proposons ici une méthode quantitative d’étude et de représentation du demi-tour (le rotagramme), mesuré avec des capteurs inertiels (IMU). Méthode Trente-sept patients droitiers hémiparétiques apr...

This article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. The algorithm is tested on a database of 1020 record...

This article proposes an implementation and a study of the paper “Adaptive Interpolation of Discrete-Time Signals That Can Be Modeled as Autoregressive Processes” by Janssen et al. The algorithm presented in this paper allows one to reconstruct an audio signal which presents localized degradations by interpolating the missing samples. This method a...

In this work, methods to detect one or several change points in multivariate time series are reviewed. They include retrospective (off-line) procedure such as maximum likelihood estimation, regression, kernel methods, etc. In this large area of research, applications are numerous and diverse; many different models and operational constraints (on pr...

ruptures is a Python library for offline change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models. ruptures focuses on ease of use by providing a well-documented and consistent int...

Introduction Motor and sensitive disabilities deeply modify the gait pattern in progressive multiple sclerosis (MS); head–and thus cephalic sensory system- stabilization during walking is therefore a key issue for maintaining dynamic stability. This study aims at assessing the feasibility of constraining the gaze on a target while walking to limit...

In this paper, we present a method for the creation of a library of inertial signals based on Dynamic Time Warping (DTW) for step characterization, with preliminary results in control subjects and patients with neurological diseases. Subjects performed a protocol including a 10 m straight walking, then turn back and walking for additional 10 m. The...

We consider the problem of building shift-invariant representations for long signals in the context of distributed processing. We propose an asynchronous algorithm based on coordinate descent called DICOD to efficiently solve the $\ell_1$-minimization problems involved in convolutional sparse coding. This algorithm leverages the weak temporal depen...

Objective We analyzed spontaneous 180° turning strategies in poststroke hemiparetic patients by using inertial measurement units (IMUs) and the association of turning strategies with risk of falls. Methods We included right paretic (RP) and left paretic (LP) post-stroke patients, and healthy controls (HCs) from a physical and rehabilitation depart...

Congrès Francophone Fragilité des Personnes Âgées et Prévention de la Perte d'Autonomie, Paris, FRA, -

Introduction Le demi-tour est évalué en routine à l’aide du nombre de pas extérieurs et de sa durée. Ces deux paramètres ne rendent pas compte de toute la cinématique du demi-tour ce que pourraient permettre en routine les capteurs inertiels (IMUs). Nous avons : – comparé les stratégies de demi-tour spontanées des sujets hémiparétiques droits (HD)...

For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC...

Lower limb osteoarthritis severity group, WOMAC score, BMI, age, walking velocity and the 60 parameters for the 12 control subjects and the 48 patients. Each parameter is defined by: a sensor = {head, lower back, ipsilateral foot, contralateral foot}; a frame = {sensor, office}; an axis = {AP,ML,V} if the frame is the sensor-linked frame or an axis...

Objective Fall is a common complication in post-stroke populations and more likely occurs in left paretic (LP) than in right paretic patients (RP). Since kinematic characteristics of post-stroke patients’ turn have not been clearly established, the goal of this study was to analyze with inertial measurement units (IMUs) spontaneous and constraint 1...

This article presents a method for restoring audio signals corrupted by impulsive noise such as clicks, bursts or scratches. The algorithm takes as input a degraded audio signal and automatically detects the locations of the degraded samples and replaces them with more appropriate values. Both steps (detection and interpolation) are based on the as...

Introduction La faible qualité des acquisitions réalisées par la Wii Board Balance est souvent mise en avant comme le principal obstacle à son utilisation comme plate-forme de force pour l’évaluation de l’équilibre. Une nouvelle approche est proposée, utilisant des méthodes de traitement du signal avancée afin d’améliorer la qualité des enregistrem...

Introduction L’extraction automatique des caractéristiques de la marche est utile pour quantifier objectivement les troubles de la locomotion et étudier l’évolution de diverses maladies ORL, neurologiques ou orthopédiques. On utilise pour cela des centrales inertielles sans fil enregistrant les accélérations et les vitesses angulaires. Le but est d...

Introduction Le suivi longitudinal des patients atteints d’arthrose de hanche et de genou necessite des methodes de quantification de la boiterie utilisables en consultation clinique. Le but etait de realiser une etude exploratoire afin de determiner si une mesure de la boiterie a partir de capteurs inertiels et une analyse de bas niveau du signal...