New Detection Thresholds and Stop Rules for CUSUM Online Detection.

International audienceWe address the problem of online detection of a change point via the online version of the CUSUM method. Change-point detection is based on the choice of a statistics and the threshold it must reach to report a change. CUSUM statistics is based on a sequential test of the likelihood ratio, which can be replaced by a score function in the non-parametric case and the classical method for selecting the detection threshold is based on Wald inequalities [Wald, A., D. J. (1945)].In our work, we propose an empirical method for the selection of the detection threshold. We also suggest replacing the constant threshold with an instantaneous time-dependent threshold. In order to control the instantaneous false alarm rate (IFAR), the mean time between false alarms (MTBFA) and the average detection delay (ADD), we propose new procedures by correcting the stop rule usually used in the CUSUM approach.In order to evaluate and compare new different methods for selecting detection threshold and the new stop rules, we perform simulations to evaluate detection parameters in each case

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Performance study of change‐point detection thresholds for cumulative sum statistic in a sequential context

International audienceSequential detection is based on a recursive statistic and a threshold it must reach to report a change. In this paper, we consider the score-based CUSUM statistic and propose to evaluate the detection performance of some thresholds on simulated data. Three thresholds come from the literature: the Wald's constant, the empirical constant and the conditional empirical instantaneous (the latter two are built by a simulation-based procedure). Two new thresholds are built by a simulation-based procedure: the first one is instantaneous, the second is a dynamical version of the previous one. The thresholds' performance measured by an estimation of the Mean Time Between False Alarm (MTBFA) and the Average Detection Delay (ADD), are evaluated on independent and autocorrelated data for several scenarii, according to the detection objective and the real change in the data. The simulations allow us to compare the difference between the thresholds' results and to see that their performances prove to be robust when a parameter of the pre-change regime is misestimated or when the data independence assumption is violated. We found also that the conditional empirical threshold is the best at minimizing the detection delay while maintaining the given false alarm rate. However, on real data, we suggest to use the dynamic instantaneous threshold because it's the easiest to build for practical implementation

Détection statistique de rupture dans le cadre online

International audienceWe introduce the online version of the CUSUM statistics based on a sequential test of the likelihood ratio, which we replace with a score function in the non-parametric case. Change-point detection is based on a stopping rule and the selection of a detection threshold. In our work, we propose an instantaneous detection threshold dependent on time and new stopping rules in order to control the detection parameters given by the instantaneous false alarm rate (IFAR), the mean time between false alarms (MTBFA) and the average detection delay (ADD). Finally, we present simulation results by estimating detection parameters.Nous introduisons la version online de la statistique de CUSUM basée sur un test séquentiel du rapport de vraisemblance, que nous remplaçons par une fonction de score dans le cas non-paramétrique. La détection de rupture est basée sur une règle d'arrêt et la sélection d'un seuil de détection. Dans notre travail, nous proposons un seuil de détection instantané, et des nouvelles règles d'arrêt dans le but de contrôler les paramètres de détection donnés par le taux de fausse alarme instantané (IFAR), le temps moyen entre fausses alarmes (MTBFA) ainsi que le délai moyen de détection (ADD). Finalement, nous présentons des résultats de simulation par l'estimation des paramètres de détection

Détection de ruptures dans les signaux EMG de l'activité musculaire du trapèze supérieur

International audienceWe are interested in studying the development of myalgia of the trapezius muscle in the workplace. The data collected are EMG (electromyographic) signals of upper trapezius muscle activity from 30 healthy participants without chronic neck pain, performing different computer activities on an experimental day. For the purpose of breaking detection, we place ourselves within the framework of the sequential detection where we admit that the EMG signal arrives point by point, in real time. Next, we consider the score-based CUSUM statistic to detect diet changes in muscle activity. Our detection methodology supports the estimation of the parameters (mean and variance of the prechange regime) in an online way on the EMG signal. The detection results then made it possible to characterize the different types of activities.Nous nous intéressons à l'étude du développement de la myalgie du muscle trapèze en milieu de travail. Les données recueillies sont des signaux EMG (électromyographique) de l'activité musculaire du trapèze supérieur de 30 participants en bonne santé, sans cervicalgie chronique, effectuant différentes activités informatiques lors d'une journée expérimentale. Dans le but de la détection de rupture, nous nous plaçons dans le cadre de la détection séquentielle où l'on admet que le signal EMG arrive point par point, en temps réel. Ensuite, nous considérons la statistique CUSUM basée sur le score pour détecter des changements de régime dans l'activité musculaire. Notre méthodologie de détection prend en charge l'estimation des paramètres (moyenne et variance du régime pré-changement) d'une manière online sur le signal EMG. Les résultats de détection ont permis ensuite de caractériser les différents types d'activités

The logistic S.D.E.

International audienceWe consider the logistic S.D.E which is obtained by addition of a diffusion coefficient of the type β√x to the usual and deterministic Verhust-Volterra differential equation. We show that this S.D.E is the limit of a sequence of birth and death Markov chains. This permits to interpret the solution Vt as the size at time t of a self-controlled tumor which is submitted to a radiotherapy treatment. We mainly focus on the family of stopping times Tε, where Tε is the first hitting of level ε > 0 by (Vt). We calculate their Laplace transforms and also the first moment of Tε. Finally we determine the asymptotic behavior of Tε, as ε → 0

Change-point detection method for the prediction of dreaded events during online monitoring of lung transplant patients

International audienceContext • Survival after lung transplantation is about 80% at 1 year and 50% at 6 years. • The two main complications responsible for deaths in lung transplant patients are infection and/or rejection. Main objective • Test the monitoring of lung transplant patients by connected sensors ; • Propose a methodology for real-time prediction of a serious event (infection and/ or rejection) via the change-point detection in the evolution of the multivariate signals collected by these connected sensors

Distinct roles of Hoxa2 and Krox20 in the development of rhythmic neural networks controlling inspiratory depth, respiratory frequency, and jaw opening

<p>Abstract</p> <p>Background</p> <p>Little is known about the involvement of molecular determinants of segmental patterning of rhombomeres (r) in the development of rhythmic neural networks in the mouse hindbrain. Here, we compare the phenotypes of mice carrying targeted inactivations of <it>Hoxa2</it>, the only <it>Hox </it>gene expressed up to r2, and of <it>Krox20</it>, expressed in r3 and r5. We investigated the impact of such mutations on the neural circuits controlling jaw opening and breathing in newborn mice, compatible with Hoxa2-dependent trigeminal defects and direct regulation of <it>Hoxa2 </it>by Krox20 in r3.</p> <p>Results</p> <p>We found that <it>Hoxa2 </it>mutants displayed an impaired oro-buccal reflex, similarly to <it>Krox20 </it>mutants. In contrast, while <it>Krox20 </it>is required for the development of the rhythm-promoting parafacial respiratory group (pFRG) modulating respiratory frequency,<it> Hoxa2 </it>inactivation did not affect neonatal breathing frequency. Instead, we found that <it>Hoxa2</it>^-/-but not <it>Krox20</it>^-/-mutation leads to the elimination of a transient control of the inspiratory amplitude normally occurring during the first hours following birth. Tracing of r2-specific progenies of <it>Hoxa2 </it>expressing cells indicated that the control of inspiratory activity resides in rostral pontine areas and required an intact r2-derived territory.</p> <p>Conclusion</p> <p>Thus, inspiratory shaping and respiratory frequency are under the control of distinct <it>Hox</it>-dependent segmental cues in the mammalian brain. Moreover, these data point to the importance of rhombomere-specific genetic control in the development of modular neural networks in the mammalian hindbrain.</p

Identification of Pharmacokinetics Models in the presence of Timing Noise

International audienceThe problem addressed in this paper deals with the parameter estimation of in vitro uptake kinetics of drugs into living cells in presence of timing noise. Effects of the timing noise on the bias and variance of the output error are explicitly determined. A bounded-error parameter estimation approach is proposed as a suited solution to handle this problem. Application results are presented which emphasize the effectiveness of the methodology in such an experimental framework

Parameter estimation of pharmacokinetics models in the presence of timing noise

International audienceWe consider a model of pharmacokinetics which takes into account the presence of timing nois