Portail des publications scientifiques IMT Mines Alès
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Specifications and functional impact of a self-triggered grasp neuroprosthesis developed to restore prehension in hemiparetic post-stroke subjects
No full textThe online version contains supplementary material available at https:// doi. org/ 10. 1186/ s12938‑ 024‑ 01323‑yInternational audienceBackground: Stroke is the leading cause of acquired motor deficiencies in adults. Restoring prehension abilities is challenging for individuals who have not recovered active hand opening capacities after their rehabilitation. Self-triggered functional electrical stimulation applied to finger extensor muscles to restore grasping abilities in daily life is called grasp neuroprosthesis (GNP) and remains poorly accessible to the poststroke population. Thus, we developed a GNP prototype with self-triggering control modalities adapted to the characteristics of the post-stroke population and assessed its impact on abilities.Methods:Through two clinical research protocols, 22 stroke participants used the GNP and its control modalities (EMG activity of a pre-defined muscle, IMU motion detection, foot switches and voice commands) for 3 to 5 sessions over a week. The NeuroPrehens software interpreted user commands through input signals from electromyographic, inertial, foot switches or microphone sensors to trigger an external electrical stimulator using two bipolar channels with surface electrodes. Users tested a panel of 9 control modalities, subjectively evaluated in ease-of-use and reliability with scores out of 10 and selected a preferred one before training with the GNP to perform functional unimanual standardized prehension tasks in a seated position. The responsiveness and functional impact of the GNP were assessed through a posteriori analysis of video recordings of these tasks across the two blinded evaluation multi-crossover N-of-1 randomized controlled trials.Results: Non-paretic foot triggering, whether from EMG or IMU, received the highest scores in both ease-of-use (median scores out of 10: EMG 10, IMU 9) and reliability (EMG 9, IMU 9) and were found viable and appreciated by users, like voice control and head lateral inclination modalities. The assessment of the system's general responsiveness combined with the control modalities latencies revealed median (95% confidence interval) durations between user intent and FES triggering of 333 ms (211 to 561), 217 ms (167 to 355) and 467 ms (147 to 728) for the IMU, EMG and voice control types of modalities, respectively. The functional improvement with the use of the GNP was significant in the two prehension tasks evaluated, with a median (95% confidence interval) improvement of 3 (−1 to 5) points out of 5.Conclusions: The GNP prototype and its control modalities were well suited to the post-stroke population in terms of self-triggering, responsiveness and restoration of functional grasping abilities. A wearable version of this device is being developed to improve prehension abilities at home.Trial Registration: Both studies are registered on clinicaltrials.gov: NCT03946488, registered May 10, 2019 and NCT04804384, registered March 18, 2021.</p
ORCGT: Ollivier-Ricci Curvature-Based Graph Model for Lung STAS Prediction
No full textDonnées associées : https://github.com/zhengwang9/ORCGTInternational audienceTumor Spread Through Air Spaces (STAS), identified as a mechanism of invasion, has been substantiated by multiple studies to be associated with lower survival rates, underscoring its significant prognostic implications. In clinical practice, pathological diagnosis is regarded as the gold standard for STAS examination. Nonetheless, manual STAS diagnosis is characterized by labor-intensive and time-consuming processes, which are susceptible to misdiagnosis. In this paper, we attempt for the first time to identify the underlying features from histopathological images for the automatic prediction of STAS. Existing deep learning-based methods usually produce undesirable predictive performance with poor interpretability for this task, as they fail to identify small tumor cells spread around the main tumor and their complex correlations. To address these issues, we propose a novel Ollivier-Ricci Curvature-based Graph model for STAS prediction (ORCGT), which utilizes the information from the major tumor margin to improve both the accuracy and interpretability. The model first extracts the major tumor margin by a tumor density map with minimal and coarse annotations, which enhances the visibility of small tumor regions to the model. Then, we develop a Pool-Refined Ollivier-Ricci Curvature-based module to enable complex interactions between patches regardless of long distances and reduce the negative impact of the over-squashing phenomenon among patches linked by negative curvature edges. Extensive experiments conducted on our collected dataset demonstrate the effectiveness and interpretability of the proposed approach for predicting lung STAS. Our code is available at https://github.com/zhengwang9/ORCGT
A Framework for Modular Treatment of Industrial Effluent and Modular Environmental Life Cycle Assessment of the Treatment Scenarios
No full textInternational audienceThis paper presents solutions to challenges encountered during an industrial pilot project focused on managing a modular effluent treatment plant and conducting a life-cycle assessment of the treatment scenarios. The plant's modular design allows for bypassing individual treatment units, enabling flexible and dynamic treatment configurations that can be tailored to the specific characteristics of industrial effluents and the desired water quality. The study addresses three key challenges: 1) identifying suitable treatment techniques for various pollutants, 2) determining the optimal arrangement of treatment modules to configure an effective process for specific effluents, and 3) selecting the most sustainable treatment process from several possible configurations based on the effluent composition. The objective of this research is to provide solutions to these challenges and develop an approach for environmental assessment of modular industrial effluent treatment. This is achieved through the following steps: 1) developing a parametric model encompassing a range of conventional, established, and emerging treatment technologies for industrial effluents, 2) creating a decision tree based on Best Available Techniques (BAT) to configure the appropriate treatment chain according to pollutant composition, 3) designing a modular treatment system consisting of three stages: pretreatment, membrane treatment, and finishing treatment, and 4) conducting a comparative environmental life-cycle assessment (LCA) of the treatment modules to reveal differences in their environmental impacts. An integrated approach was developed to configure treatment scenarios based on effluent composition, intended end use, available technologies, and environmental impact assessments. To address the complexity of configuring treatment chains given the diversity of contaminants and technologies, a decision tree was developed based on the Best Available Techniques (BAT) tailored to pollutant types. To facilitate environmental assessments, parametric life-cycle models were developed for treatment modules based on a thorough literature review, ensuring versatility in LCAs for different treatment scenarios and flexibility in sensitivity and uncertainty analyses. Parametric life-cycle inventories were developed for the operational phase of 15 conventional and advanced treatment modules, enabling comparative environmental impact assessments with sensitivity and uncertainty analysis. The comparative life cycle assessment revealed the hotspots and contributions of fifteen treatment modules to the environmental impacts of treating of 1m³ effluent, with nanofiltration, reverse osmosis, and ion-exchange having the highest overall impacts. Sensitivity analysis unveiled high sensitivity of midpoint and endpoint environmental impacts on energy, resin, and chemical consumption. This integrated approach provides a foundational framework for the further development of decision trees as a tool for configuring effluent treatment processes and assessing their sustainability. The modular configuration, along with the decision tree, offers greater flexibility in developing fit-for-purpose treatment scenarios and conducting modular LCAs for more sustainable effluent treatment. This framework can be updated and adapted to incorporate emerging treatment technologies and contaminants, facilitating future LCAs in the effluent treatment industry
Study of Early-Age Phenomena at the Concrete-Marine Biofilm Interface in Seawater for the Construction of Eco-Friendly Fowt’s
No full textInternational audienceFloating Offshore Wind Turbines (FOWTs) are designed to harness the energy produced by wind. Since these structures are in deep waters, the engineering and dynamics of steel and or concrete structural elements (floaters, chains, mooring, etc.) is important to ensure significant performance. The durability of concrete in submerged zones is affected by biological and chemical deterioration mechanisms, with the latter being controlled by transport of aggressive ions. The influence of concrete on biodiversity developing on its surface plays a significant role as it contributes to the overall environmental footprint of the structure. The aim of this experimental research was to identify the surface interactions between cementitious materials such as concrete, biofouling at their surface, and seawater on short-term exposure. CEM III concrete specimens were submerged at a depth of 27m at SOLA station, Banyuls-sur-mer, France. The microstructural and chemical changes in the cementitious material were analysed with scanning electron microscopy coupled to energy dispersive spectroscopy (SEM-EDS) and electron probe micro analysis (EPMA). The results of SEM-EDS analysis showed the formation of three zones, namely, magnesium-rich, sulfur-rich, and chloride-rich zones. Using Environmental DNA analysis, bacterial diversity was identified, revealing high abundances of alphaproteobacteria and gammaproteobacteria, and 18s rRNA sequencing unveiling a diverse eukaryotic community
QAI-Sport project: Indoor air quality in sports facilities - Characterization of exposure to emerging VOCs and SVOCs and to micro-organisms
No full textInternational audienceThe quality of indoor air in sports facilities is still poorly known and studied. However, the intense activity associated with sport can lead to an increase in exposure through inhalation, breathing rate acceleration, ingestion of resuspended dust, and transcutaneous migration facilitated by sweat. The configuration, management and maintenance of premises can also contribute to a deterioration in indoor air quality in sport centers. These include, for example, the occupancy rate of rooms, poor ventilation management, the presence of synthetic floor coverings and technical materials that emit pollutants or favor the development and persistence of pathogenic micro-organisms such as coronavirus.The QAI-sport project (2022-2024), funded by ADEME (the French Agency for Ecological Transition), proposes to characterize exposure to volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs) and microbiological contaminants (molds, viruses and bacteria) by studying around ten sports facilities for different activities (martial arts, weight-lifting, motricity in preschools). The project is presented here, along with its methodology and main objectives.Initially, targeted and non-targeted analyses of these agents will be carried out under occupied and unoccupied conditions. Particular attention will be paid to identifying emerging contaminants, substances that are unregulated or unexpected in these environments, and to highlighting the main families of pathogenic micro-organisms.An in-depth study, carried out on a selection of three rooms, will then make it possible to study the sources and distribution of contaminants (VOCs, SVOCs and micro-organisms) between the gaseous and particulate phases of the air, settled dust and materials’ surfaces. In view of the recent pandemic, the project will also include specific research into Sars-CoV-2. Exposure to biocides used against this virus will be assessed as well.For SVOCs, the data obtained will be integrated into a model to predict the behavior of these pollutants in indoor environments.Finally, a study of the migration of VOCs and SVOCs in sweat and synthetic saliva will complete the results for a complete and detailed assessment of the exposure routes to these compounds
Force reserve predicts compensation in reaching movement with induced shoulder strength deficit
No full textInternational audienceOur study reveals key findings on compensatory movements during upper limb reaching tasks under shoulder strength deficits, as observed poststroke. Using heavy dumbbells with healthy volunteers, we demonstrate how forward trunk displacement conserves around 40% of shoulder strength reserve during reaching. We show that an optimal controller employing a cost function combining squared motor torque and a nonlinear penalty for excessive muscle activation outperforms traditional controllers in predicting torques and compensatory movements in these scenarios
Immersive learning of factual knowledge while assessing the influence of cognitive load and spatial abilities
No full textInternational audienceImmersive virtual reality (IVR) is a motivating new learning tool. However, discrepancies in results emerge regarding the type of knowledge, specifically factual knowledge. Moreover, to improve the instructional design, authors claimed to verify the impact of cognitive load and spatial abilities while learning in IVR. Sixty-one undergraduate students were recruited and divided into two groups in pre-post, test study design. Learning consisted of using "Google Earth" with a Head Mounted Display (HMD) or a desktop computer to improve general geographic knowledge. Pre-training and segmentation were included in the learning process, and levels of presence, spatial orientation and cognitive load were measured to evaluate their impact. Results show that the two groups significantly improved their performance between pre and post-test. HMD users felt more present than computer users. Overall cognitive load did not hinder the learning performance. The analysis of cognitive load dimensions reveals significant differences in the mental load and frustration levels between the two groups. Spatial orientation was not correlated to the learning process. The use of HMD is effective for learning geographic general knowledge. When managed overall cognitive load does not influence learning although the use of HMDs elicits high mental load levels. HMD users are experiencing less frustration indicating it may be suitable for longdistance learning. HMD technological features compensate for spatial orientation abilities. Finally, presence does not enhance learning, suggesting it should be combined with interactions eliciting feedback to be more effective
Consequences of partial vessel failure in BLEVE and liquid full fill rupture events
No full textIssu de : CISAP 11 - International Conference On Safety & Environment In Process & Power Industry, Sep 2024, Naples, Italy.International audienceThe Boiling liquid expanding vapor explosion (BLEVE) refers to a catastrophic explosion that occurs when a vessel containing a pressure liquified gas at a temperature well above its atmospheric boiling point experiences total loss of containment. The vessel completely opens and hazards are produced posing risks to nearby populated areas and critical infrastructure. Studying partial failures aids in developing strategies to minimize potential damage from associated hazards such as ground load, projectiles, and near-field overpressure. Understanding the characteristics of partial failure mechanism provides valuable insights for identifying factors influencing vessel opening and increasing the severity of BLEVE incidents. New small-scale propane 2022 BLEVE experiments on 589 cm3 aluminium vessels were conducted at IMT mines Ales, France, for different operating conditions. Through a sensitivity analysis, this study investigates the factors contributing to partial failure, and how the type of opening contributes to a less or more powerful hazards