Analyse de l’activité à bord de dragues aspiratrices : une méthodologie exploratoire combinant données psychologiques et physiologiques

Cette étude a pour objectif d’explorer une méthodologie recoupant deux ordres de données, psychologiques et physiologiques, dans le cadre d’une analyse ergonomique de l’activité. Deux terrains d’étude, situations « naturelles », ont été investis : une drague aspiratrice stationnaire et une drague aspiratrice en marche, où nous nous sommes focalisés sur l’assistant de pont en charge de l’activité de dragage. Au niveau psychologique, notre méthode a consisté à croiser des observations ethnographiques avec des entretiens individuels compréhensifs. Au niveau physiologique, des mesures de la fréquence cardiaque (intervalle R-R) ont été réalisées à travers des enregistrements simultanés à l’activité.Nos résultats découlent alors de la confrontation de ces sources de données « objectives » et « subjectives ». Au poste du dragueur, la charge de travail paraît conséquente avec des actions courtes et nombreuses. Il semble nécessaire de maintenir un niveau de vigilance élevé, en fonction des différents paramètres à prendre en considération et des régulations multiples à fournir lors de la tâche. L’activité se complexifie selon la nature des fonds sous-marins, avec la survenue de nombreuses variations et l’apparition possible de stress lors de dragages sur fond chaotique. Cette prise en compte « intégrée » de l’activité humaine devrait permettre en retour l’amélioration de la sécurité des marins.The purpose of this study is to explore a methodology combining two types of data, psychological and physiological, through an ergonomic analysis of the activity. Two field studies were conducted: the stationary suction dredger situation, and the moving suction dredger situation, where we focused on the bridge assistant, responsible for the dredging activity. Two orders of data are considered: psychological and physiological. From a psychological point of view, our methodology cross-referenced ethnographic observations with non-directive interviews. At the physiological level, heart-rate measurements (R-R interval) were continuously recorded, throughout the activity. Our results proceed from the confrontation of these “objective” and “subjective” data sources. The workload at this work station appears to be considerable, with many short actions. It would seem necessary to maintain a high level of vigilance, due to the various parameters to be taken into account, and to the multiple adjustments which must be made during the task time. The activity can become more complex, depending on the nature of the seabeds: many variations can take place, and there may be occurrences of stress when dredging chaotic seabeds. This “integrated” approach to human activity should lead to improved safety for the sailors

Case study of the real contents delivered in French motorcycle schools

This study is concerned initial motorcycle training delivered in motorcycle schools in France. Novice motorcyclists are a particularly vulnerable group of road users in Europe and in France. However, scientific attempts to achieve a better understanding of their behaviors have been limited. The potential value of studying initial motorcycle training, both for research purposes and with regard to public policy, is readily apparent. The aims of this paper are to describe the real educational content of training in motorcycle schools and analyze to what extent this content is related to riding after licensing. A case study of all the training process of one trainee (38 hours) was carried out in real world. Audiovisual recordings and interview data of the rider and instructors were collected at each session. This study was supplemented by ethnographic observations of the educational content provided in three motorcycle schools throughout the instructors’ working days. The results that merged from both studies show (1) the riding skills that were fostered (i.e. control skills, and especially emergency skills, in stable and restricted environments) and undervalued (i.e. hazard perception skills, everyday skills) during initial training, and (2) the poverty of observed training settings: learners spend almost all their training time riding in the same setting that is used in the test. In addition to being repeated to excess, these settings are quite different from the real traffic. These results are discussed regarding the scientific literature on motorcycle education. The conclusion presents the implications of these results for public policy in order to design a future rider training system. Document type: Articl

After-Fatigue Condition: A Novel Analysis Based on Surface EMG Signals

This study introduces a novel muscle activation analysis based on surface electromyography (sEMG) signals to assess the muscle's after-fatigue condition. Previous studies have mainly focused on the before-fatigue and fatigue conditions. However, a comprehensive analysis of the after-fatigue condition has been overlooked. The proposed method analyzes muscle fatigue indicators at various maximal voluntary contraction (MVC) levels to compare the before-fatigue, fatigue, and after-fatigue conditions using amplitude-based, spectral-based, and muscle fiber conduction velocity (CV) parameters. In addition, the contraction time of each MVC level is also analyzed with the same indicators. The results show that in the after-fatigue condition, the muscle activation changes significantly in the ways such as higher CV, power spectral density shifting to the right, and longer contraction time until exhaustion compared to the before-fatigue and fatigue conditions. The results can provide a comprehensive and objective evaluation of muscle fatigue and recovery, which can be helpful in clinical diagnosis, rehabilitation, and sports performance

Développement d'outils non-stationnaires pour la mesure de délais variables appliqués aux signaux bioélectriques

ORLEANS-BU Sciences (452342104) / SudocSudocFranceF

Impact of PCA Pre-Normalization Methods on Ground Reaction Force Estimation Accuracy

Ground reaction force (GRF) components can be estimated using insole pressure sensors. Principal component analysis in conjunction with machine learning (PCA-ML) methods are widely used for this task. PCA reduces dimensionality and requires pre-normalization. In this paper, we evaluated the impact of twelve pre-normalization methods using three PCA-ML methods on the accuracy of GRF component estimation. Accuracy was assessed using laboratory data from gold-standard force plate measurements. Data were collected from nine subjects during slow- and normal-speed walking activities. We tested the ANN (artificial neural network) and LS (least square) methods while also exploring support vector regression (SVR), a method not previously examined in the literature, to the best of our knowledge. In the context of our work, our results suggest that the same normalization method can produce the worst or the best accuracy results, depending on the ML method. For example, the body weight normalization method yields good results for PCA-ANN but the worst performance for PCA-SVR. For PCA-ANN and PCA-LS, the vector standardization normalization method is recommended. For PCA-SVR, the mean method is recommended. The final message is not to define a normalization method a priori independently of the ML method

Cramer-Rao lower bounds for Estimating the Time Varying Delay of Surface EMG Signals

International audienceThe muscle fiber conduction velocity (CV) is usually used as a muscle fatigue indicator. The CV evaluation can indirectly be performed by estimating the time delay between surface electromyography (sEMG) signals recorded on electrodes aligned with the muscle fiber direction. To take into account the variability of the CV along the fiber and between channel recordings, the recently published methods assume that the time delay between the channels is a function depending on time. In the present paper, we derive the theoretical Cramer-Rao Bound (CRB) appropriate for estimating the time-varying delay of sEMG signals. The new CRB expression is computed for a polynomial model of the time-varying delay and for two channels. We emphasize the relationship between this new CRB expression and the classical CRB calculated for a constant time delay. Monte Carlo simulations are conducted to assess the performance of the maximum likelihood estimator of the time-varying delay. The likelihood maximization is achieved by using a stochastic optimization technique called the simulated annealing. The simulation results show the CRB derived very optimistic

Use of cardiorespiratory coherence to separate spectral bands of the heart rate variability

International audienc

Time-varying delay estimators for measuring muscle fiber conduction velocity from the surface electromyogram

International audienc

On The Statistical Properties Of The Generalized Discrete Teager-Kaiser Energy Operator Applied To Uniformly Distributed Random Signals

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