Academic literature on the topic 'Mechanical Ventilation Optimisation'

This study presents a multi-objective optimisation of building thermo-modernisation for multi-family buildings. The applied model has considered alternative solutions for insulation materials, with different thicknesses and different types of windows. The weighted sum method was applied to find a solution considering the minimisation of global cost, primary energy ratio and CO2 emissions. The solutions were compared for a building equipped with natural ventilation, and with mechanical supply—exhaust ventilation. In reference to the two considered types of ventilation, we analysed how the modification of an insulation thickness, its type and the type of installed windows, can be converted into individual evaluation criteria. The weights of the considered criteria were changed; however, this had no influence on the optimal solution. If the aim is to achieve the standards of zero-energy buildings, natural ventilation cannot be applied, despite the high value of thermal insulation of the building envelopes. Alternative solutions exist for buildings with natural ventilation and mechanical ventilation with heat recovery, where the primary energy ratio is the same for both, but the global costs are different. The additional energy and environmental input for the production of materials and elements to be replaced are insignificant in comparison to the savings brought about by thermo-modernisation.

IntroductionThe inhalative administration of drugs is a non-invasive application form that is regularly used in the treatment of ventilated patients in critical care setting. However, assessment of effectiveness or distribution of nebulised drugs is one of the lacking cornerstones of modern intensive care monitoring. Electrical impedance tomography (EIT) may provide a promising new monitoring and guiding tool for an adequate optimisation of mechanical ventilation in critically ill patients. EIT may assist in defining mechanical ventilation settings, assess distribution of tidal volume and evaluate associated pathologies at bedside. This study aims to elucidate the extent to which the effectiveness of inhaled salbutamol can be increased by the additional use of EIT for optimisation of respirator settings.Methods and analysisThis study is a randomised, open-label, superiority trial conducted on an intensive care unit of a German university hospital, comparing two groups of mechanically ventilated patients with an acute or chronic bronchial airway obstruction according to the effectiveness of inhaled salbutamol with (intervention) or without (control) additional use of EIT for optimising ventilator settings. The primary outcome is change in airway resistance 30 min after salbutamol inhalation.Ethics and disseminationThe study has received approval from the Ethics Committee of the Medical Faculty of Ruhr-University Bochum (17-6306). The results will be made available to critical care survivors, their caregivers, the funders, the critical care societies and other researchers by publication in a peer-reviewed journal.Trial registration numberDRKS00014706; Pre-results.

Patient–ventilator dyssynchrony or asynchrony occurs when, for any parameter of respiration, discordance exists between the patient’s spontaneous effort and the ventilator’s provided support. If not recognised, it may promote oversedation, prolong the duration of mechanical ventilation, create risk for lung injury, and generally confuse the clinical picture. Seven forms of dyssynchrony are common: (a) ineffective triggering; (b) autotriggering; (c) inadequate flow; (d) too much flow; (e) premature cycling; (f) delayed cycling; and (g) peak pressure apnoea. ‘Reverse triggering’ also occurs and may mimic premature cycling. Correct diagnosis of these phenomena often permits management by simple ventilator optimisation rather than by less desirable measures.

The wine-ageing process is one of the most important phases of the wine production and it can be considerably affected by the micro-climatic conditions inside the ageing rooms. Underground wine cellars in small-medium wineries are designed with natural ventilation systems, able to maintain optimal indoor condition. However, critical factors emerge, such as mold growth or wine evapo-transpiration, where ventilation proved to be poorly designed, insufficient in the first case or excessive in the second one. The zones around the wooden barrels proved to be the most sensitive and problematic. These areas are the most investigated in terms of temperature and humidity values but surprisingly not in terms of air velocity. In this paper, a ventilation system has been designed and optimised to support the lack of ventilation, by means of computational fluid dynamics modelling. Eight configurations have been performed and analysed, identifying the best two according to the air velocity range. Specific parameters have been defined to appreciate the application limits of each configuration. These parameters can be used as reference for system design in similar studies and applications and can help scholars and professionals to identify the optimal configurations for the implementation and proper placement of the system inside a cellar.

This paper deals with predictive control applied to the management of water storage in a small water distribution network. This online optimisation-based strategy is computed iteratively by solving a set of mathematical equations which describe the operative goals, in a given time horizon, and uses a representative model for the network dynamics as well as a demand forecast. The approach has been tested on a simulator developed for a four-reservoir water network of a commune of Luxembourg. Mathematical optimisation of the water distribution network is defined to account for all the requirements put forward by the authorities (both the commune and the regional drinking water provider as well as the national water agency), without ignoring the operating and physical constraints of the network. Based on realistic consumption scenarios, the starting situation (tanks always completely filled) and different control strategies (proportional integral derivative or PID level regulation or global predictive control) have been compared and the results are discussed. Moreover, the question of whether to integrate natural ventilation has been explored. Global predictive control leads to improved management in comparison to PID and mechanical control. Further work is needed to evaluate performance when goals, such as tank aeration, are to be met.

We report the case of a 70-year-old diabetic woman who presented to the emergency department with multiple seizure episodes and coma, prompting the need for sedation and mechanical ventilation. She was transferred to our institution for neurosurgical evaluation as the initial CT scan identified hyperdense lesions in the left basal ganglia, interpreted as acute intracranial haemorrhage. On admission, laboratory tests were mostly normal except for blood glucose of 413 mg/dL. Medical records revealed a history of poorly controlled diabetes mellitus and non-adherence to therapy. After seizure control and lifting sedation, right-sided ataxia/involuntary movements were observed. Considering the patient’s history and these findings, the CT scan was reviewed and the striatal region hyperdensities interpreted as lesions typical of non-ketotic hemichorea-hemiballismus. MRI was latter performed and confirmed the diagnosis, even though the unusual presentation. Levetiracetam initiation and glycaemic control optimisation led to great neurological improvement without seizure recurrence.

The use of topical negative pressure (TNP) dressings for sternal wound dehiscence or mediastinitis in the neonatal population is rare. The majority of case reports have focused on wound healing as an endpoint and have not discussed the physiological advantage that TNP dressings may impart with regard to sternal stabilisation, improved respiratory function and early weaning from mechanical ventilation. We present a case of the use of TNP in neonatal post-sternotomy wound dehiscence and mediastinitis, from a UK perspective, with an emphasis on wound healing and physiological optimisation. As well as an improvement in sternal wound healing due to the local effects of the TNP system, serial arterial blood gas analysis revealed a significant improvement in systemic physiological parameters, including a reduction in pCO2 in the period (days 20–31) after application of TNP (p<0.0001) compared to the period before where simple occlusive dressings were applied. Hydrogen ion concentration also significantly reduced in this period (p=0.0058). The use of the TNP system in association with systemic antibiotics successfully treated the mediastinitis. A sealed, controlled wound environment also allowed ease of nursing and an expedited return to care by the parents. We would recommend the consideration of TNP dressings in similar cases of neonatal and paediatric sternal wound dehiscence. Not only do we observe the local effects of improved wound healing, the systemic effects of improved lung function are also valuable in the early management of such complex cases.

AimThis study’s objective was to assess the risk of severe in-hospital complications of patients admitted for COVID-19 and diabetes mellitus (DM).DesignThis was a cross-sectional study.SettingsWe used pseudonymised medical record data provided by six general hospitals from the HM Hospitales group in Spain.Outcome measuresMultiple logistic regression analyses were used to identify variables associated with mortality and the composite of mortality or invasive mechanical ventilation (IMV) in the overall population, and stratified for the presence or absence of DM. Spline analysis was conducted on the entire population to investigate the relationship between glucose levels at admission and outcomes.ResultsOverall, 1621 individuals without DM and 448 with DM were identified in the database. Patients with DM were on average 5.1 years older than those without. The overall in-hospital mortality was 18.6% (N=301), and was higher among patients with DM than those without (26.3% vs 11.3%; p<0.001). DM was independently associated with death, and death or IMV (OR=2.33, 95% CI: 1.7 to 3.1 and OR=2.11, 95% CI: 1.6 to 2.8, respectively; p<0.001). In subjects with DM, the only variables independently associated with both outcomes were age >65 years, male sex and pre-existing chronic kidney disease. We observed a non-linear relationship between blood glucose levels at admission and risk of in-hospital mortality and death or IMV. The highest probability for each outcome (around 50%) was at random glucose of around 550 mg/dL (30.6 mmol/L), and the risks flattened above this value.ConclusionThe results confirm the high burden associated with DM in patients hospitalised with COVID-19 infection, particularly among men, the elderly and those with impaired kidney function. Moreover, hyperglycaemia on admission was strongly associated with poor outcomes, suggesting that personalised optimisation could help to improve outcome during the hospital stay.

Acute Respiratory Distress Syndrome (ARDS) is associated with lung inflammation and fluid filling, resulting in a stiffer lung with reduced intrapulmonary gas volume. ARDS patients are admitted to the Intensive Care Unit (ICU) and require Mechanical Ventilation (MV) for breathing support. Positive End Expiratory Pressure (PEEP) is applied to aid recovery by improving gas exchange and maintaining recruited lung volume. However, high PEEP risks further lung injury due to overstretching of healthy lung units, and low PEEP risks further lung injury due to the repetitive opening and closing of lung units. Thus, selecting PEEP is a balance between avoiding over-stretching and repetitive opening of alveoli. Furthermore, specific protocols to determine optimal PEEP do not currently exist, resulting in variable PEEP selection. Thus, ensuring an optimal PEEP would have significant impact on patient mortality, and the cost and duration of MV therapy. Two important metrics that can be used to aid MV therapy are the elastance of the lungs as a function of PEEP, and the quantity of recruited lung volume as a function of PEEP. This thesis describes several models and model-based methods that can be used to select optimal PEEP in the ICU. Firstly, a single compartment lung model is investigated for its ability to capture the respiratory mechanics of a mechanically ventilated ARDS patient. This model is then expanded upon, leading to a novel method of mapping and visualising dynamic respiratory system elastance. Considering how elastance changes, both within a breath and throughout the course of care, provides a new clinical perspective. Next, a model using only the expiratory portion of the breathing cycle is developed and presented, providing an alternative means to track changes in disease state throughout MV therapy. Finally, four model-based methods are compared based on their capability of estimating the quantity of recruited lung volume due to PEEP. The models and model-based methods described in this thesis enable rapid parameter identification from readily available clinical data, providing a means of tracking lung condition and selecting optimal patient-specific PEEP. Each model is validated using data from clinical ICU patients and/or experimental ARDS animal models.

Mechanical Ventilation (MV) therapy is one of the most common treatments offered to patients with respiratory failure in ICU. MV assists patient recovery by completely or partially taking over the breathing process and helping with oxygen delivery and removal of carbon dioxide. However, inappropriate MV settings mismatched to a given patient’s condition can cause further damage. On the other hand, suboptimal MV settings can increase the length of stay of the patient in ICU and increase the cost of treatment. Acute Respiratory Distress Syndrome (ARDS) is a major form of Acute Lung Injury (ALI) where clinicians offer a supportive environment for patient recovery by application of MV. ARDS is characterised by inflamed and fluid filled lungs that result in alveolar collapse and thus severe hypoxemia. Application of positive end expiratory pressure (PEEP) is employed to recruit and retain lung units to maximise gas exchange. However, a delicate trade-off is required between maximising gas exchange and preventing further unintended damage to the lungs, when determining optimum PEEP level. Currently, no specific protocols to determine optimum PEEP level exist and selection of PEEP is dependent on medical intuition and experience, primarily due to lack of easy methods to determine patient – specific condition at the patient’s bedside. A mathematical recruitment model is developed in Labview to help determine patient – specific condition based on fundamental lung physiology and engineering principals in this thesis. The model utilises readily available clinical data to determine parameters that identify underlying patient – specific lung characteristics and conditions. Changes in these parameters can be monitored over time and compared between patients to determine the severity of the disease and evolution of disease with time. A second model is developed to determine dynamic functional residual capacity (dFRC), that represents the extra volume retained in a lung through application of PEEP. The model extends previous efforts in the field that applied the stress – strain theory to lung mechanics to estimate dFRC. This model estimates the patient’s dFRC using readily available clinical data (PV data) and can be monitored over time to determine changes in a xiii given patient’s condition. The dFRC model introduces a new parameter, , which is considered a population constant for the particular PEEP. The model offers an easy and reliable method to determine dFRC since other methods are normally invasive or require interruption of MV. The models developed were validated against real – time clinical data obtained through clinical trials. The recruitment model was found to fit the clinical data well with error values within acceptable limits. It also enabled identification of parameters that reflect the underlying patient – specific lung condition. The dFRC model was able to estimate the dFRC for a patient with high level of accuracy for clinically applicable PEEP levels. The two models work well in conjunction with each other and provide a novel and easy method to clinicians to determine patient – specific lung characteristics and ultimately determine optimal MV treatment parameters, especially PEEP.

This thesis is made up of three parts: i) the development of a comprehensive computational model of the pulmonary (patho)physiology of healthy and diseased lungs, ii) the application of a novel optimisation-based approach to validate this computational model, and iii) the use of this model to optimise mechanical ventilator settings for patients with diseased lungs. The model described in this thesis is an extended implementation of the Nottingham Physiological Simulator (NPS) in MATLAB. An iterative multi-compartmental modelling approach is adopted, and modifications (based on physiological mechanisms) are proposed to characterise healthy as well as diseased states. In the second part of the thesis, an optimisation-based approach is employed to validate the robustness of this model. The model is subjected to simultaneous variations in the values of multiple physiologically relevant uncertain parameters with respect to a set of specified performance criteria, based on expected levels of variation in arterial blood gas values found in the patient population. Performance criteria are evaluated using computer simulations. Local and global optimisation algorithms are employed to search for the worst-case parameter combination that could cause the model outputs to deviate from their expected range of operation, i.e. violate the specified model performance criteria. The optimisation-based analysis is proposed as a useful complement to current statistical model validation techniques, which are reliant on matching data from in vitro and in vivo studies. The last section of the thesis considers the problem of optimising settings of mechanical ventilation in an Intensive Therapy Unit (ITU) for patients with diseased lungs. This is a challenging task for physicians who have to select appropriate mechanical ventilator settings to satisfy multiple, sometimes conflicting, objectives including i) maintaining adequate oxygenation, ii) maintaining adequate carbon dioxide clearance and iii) minimising the risks of ventilator associated lung injury (VALI). Currently, physicians are reliant on guidelines based on previous experience and recommendations from a very limited number of in vivo studies which, by their very nature, cannot form the basis of personalised, disease-specific treatment protocols. This thesis formulates the choice of ventilator settings as a constrained multi-objective optimisation problem, which is solved using a hybrid optimisation algorithm and a validated physiological simulation model, to optimise the settings of mechanical ventilation for a healthy lung and for several pulmonary disease cases. The optimal settings are shown to satisfy the conflicting clinical objectives, to improve the ventilation perfusion matching within the lung, and, crucially, to be disease-specific.

À ce jour, cette thèse n’a pas été déposée. L’Université Clermont Auvergne est donc dans l’impossibilité d’en assurer le traitement, la conservation et la diffusion
To date, this thesis has not been deposited. The Université Clermont Auvergne is therefore unable to ensure its processing, conservation and dissemination

En ventilation assistée, les interactions patient-ventilateur, qui sont associés au pronostic, dépendent pour partie des algorithmes de ventilation. Objectifs : Caractériser l'intérêt potentiel des nouveaux algorithmes de ventilation dans l'optimisation des interactions patient-ventilateur : 1) en ventilation invasive, deux modes et leurs algorithmes nous ont semblé novateurs et nous avons cherché à personnaliser l'assistance du ventilateur en fonction de l'effort respiratoire du patient au cours de ces modes proportionnels : ventilation assistée proportionnelle (PAV+) et ventilation assistée neurale (NAVA) ; 2) en ventilation non-invasive (VNI) nous avons évalué si les algorithmes VNI des ventilateurs de réanimation et des ventilateurs dédiés à la VNI diminuaient l'incidence des asynchronies patient-ventilateur. Méthodes : 1) En PAV+ nous avons décrit un moyen de recalculer le pic de pression musculaire réalisée par le patient à chaque inspiration à partir du gain réglé et de la pression des voies aériennes monitorée par le respirateur. Nous avons alors évalué la faisabilité clinique d'ajuster l'assistance en ciblant un intervalle jugé normal de pression musculaire. 2) Nous avons comparé une titration de l'assistance en NAVA et en aide inspiratoire (AI) en se basant sur les indices d'effort respiratoire. 3 et 4) En VNI, nous avons évalué l'incidence des asynchronies patient-ventilateur avec et sans l'utilisation d'algorithmes VNI : sur banc d'essai au cours de conditions expérimentales reproduisant la présence de fuites autour de l'interface ; en clinique chez des patients de réanimation. Résultats : En PAV+, ajuster le gain dans le but de cibler un effort respiratoire normal était faisable, simple et souvent suffisant pour ventiler les patients depuis le sevrage de la ventilation mécanique jusqu'à l'extubation. En NAVA, l'analyse des indices d'effort respiratoire a permis de préciser les bornes d'utilisation et de comparer les interactions patient-ventilateur avec l'AI dans des intervalles d'assistance semblables. En VNI, nos données pointaient l'hétérogénéité des algorithmes VNI sur les ventilateurs de réanimation et retrouvaient une meilleure synchronisation patient-ventilateur avec l'utilisation de ventilateurs dédiés à la VNI pour des qualités de pressurisation par ailleurs identiques. Conclusions : En ventilation invasive, personnaliser l'assistance des modes proportionnels optimise les interactions patient-ventilateur et il est possible de cibler une zone d'effort respiratoire normale en PAV+. En VNI, les ventilateurs dédiés améliorent la synchronisation patient-ventilateur plus encore que les algorithmes VNI sur les ventilateurs de réanimation, dont l'efficacité varie grandement selon le ventilateur considéré
During assisted mechanical ventilation, patient-ventilator interactions, which are associated with outcome, partly depend on ventilation algorithms.Objectives: : 1) during invasive mechanical ventilation, two modes offered real innovations and we wanted to assess whether the assistance could be customized depending on the patient's respiratory effort during proportional ventilatory modes: proportional assist ventilation with load-adjustable gain factors (PAV+) and neurally adjusted ventilator assist (NAVA); 2) during noninvasive ventilation (NIV): to assess whether NIV algorithms implemented on ICU and dedicated NIV ventilators decrease the incidence of patient-ventilator asynchrony.Methods: 1) In PAV+ we described a way to calculate the muscle pressure value from the values of both the gain adjusted by the clinician and the airway pressure. We then assessed the clinical feasibility of adjusting the gain with the goal of maintaining the muscle pressure within a normal range. 2) We compared titration of assistance between neurally adjusted ventilator assist (NAVA) and pressure support ventilation (PSV) based on respiratory effort indices. During NIV, we assessed the incidence of patient-ventilator asynchrony with and without the use of NIV algorithms: 1) using a bench model; 2) and in the clinical settings.Results: During PAV+, adjusting the gain with the goal of targeting a normal range of respiratory effort was feasible, simple, and most often sufficient to ventilate patients from the onset of partial ventilatory support until extubation. During NAVA, the analysis of respiratory effort indices allowed us to precise the boundaries within which the NAVA level should be adjusted and to compare patient-ventilator interactions with PSV within similar ranges of assistance. During NIV, our data stressed the heterogeneity of NIV algorithms implemented on ICU ventilators. We therefore reported that dedicated NIV ventilators allowed better patient-ventilator synchronization than ICU ventilators, even with their NIV algorithms engaged.Conclusions: During invasive mechanical ventilation, customizing the assistance during proportional ventilatory modes with the goal of targeting a normal range of respiratory effort optimizes patient-ventilator interactions and is feasible with PAV+. During NIV, dedicated NIV ventilators allow better patient-ventilator synchrony than ICU ventilators, even with their NIV algorithm engaged. ICU ventilators' NIV algorithms efficiency is however highly variable among ventilators

Mechanical ventilation (MV) therapy has been utilised in the intensive care unit (ICU) for 50 years to treat patients with respiratory illness by supporting the work of breathing, providing oxygen and removing carbon dioxide. MV therapy is utilised by 30-50% of ICU patients, and is a major driver of increased length of stay, increased cost and increased mortality. For patients suffering from acute respiratory distress syndrome (ARDS), the optimal MV settings are highly debated. ARDS patients suffer from a lack of recruited alveoli, and the application of positive end expiratory pressure (PEEP) is often used to maintain recruitment to maximise gas exchange and minimise lung damage. However, determining what level of PEEP is best for the patient is difficult. In particular, it involves a complex trade off between patient safety and ventilation efficacy. Currently, no clinical protocols exist to determine a patient-specific “best” PEEP. Model-based approaches provide an alternative patient-specific method to help clinical diagnosis and therapy selection. In particular, model-based methods can utilise a mix of both engineering and medical principles to create patient-specific models. The models are used for optimising ventilation settings and providing greater physiological insight into lung status than is currently available. Two model-based approaches are presented here. First, a quasi-static, minimal model of lung mechanics is presented based solely on fundamental lung physiology and mechanics. Secondly, a model of dynamic functional residual capacity (dFRC) is developed and presented based on model-based status of lung stress and strain. These models are validated with retrospective clinical data to evaluate the potential of such model-based approaches. Finally, the models are further validated with real time clinical data over a broader spectrum of pressure-volume ranges than prior studies to evaluate the clinical viability of model-based approaches to optimise MV therapy. When validated with real-time clinical trials data, the outputs of the recruitment model provide a range of optimal patient-specific values of PEEP based on different clinically and physiologically derived criteria. The recruitment model is also shown to have the ability to track the disease state of ARDS over time. The dFRC model introduces the PEEP stress parameter, β, which represents a unique population constant. The dFRC model suggests that clinically reasonable estimates of dFRC can be achieved by using this novel value of β, rather than the current, potentially hazardous, methods of deflating the lung to atmospheric pressure. Finally, a third model, combining the principles of recruitment and gas exchange is introduced. The combined model has the ability to estimate cardiac output (CO) changes with respect to PEEP changes during MV therapy. In addition, the model relates the coupled areas of circulation and pulmonary management, as well as linking these MV decision support models to oxygenation based clinical endpoints. A proof of concept is shown for this model by combining two different retrospective datasets and highlighting its ability to capture clinically expected drops in CO as PEEP increases. The model allows valuable cardiovascular circulation data to be predicted and also provides an alternative method and clinical end point by which PEEP could be optimised. The model requires further clinical validation before clinical use, but shows significant promise. The models developed and tested in this research enable rapid parameter identification from minimal, readily available clinical data, and thus provide a novel way of guiding therapy. The models can potentially provide clinicians with information to select an optimal patient-specific level of PEEP using only standard ventilation data, such as pressure-volume curves. In addition, the development of a dFRC stress model provides a unique population constant, β. Overall, the modelling approaches developed and validated in this research provide several novel methods of guiding therapy setting mechanical ventilation parameters and tracking and assess a patient’s lung condition. This research thus creates and provides novel validated methods for improving MV therapy with minimal cost or added invasiveness.

L’atteinte neuromusculaire, responsable notamment d’une dégradation des muscles, entraine une insuffisance respiratoire sévère. Cette dernière constitue la composante majeure de la maladie, tant en termes de pronostic que de prise en charge. A ce jour, seule la ventilation mécanique permet de compenser l’affection respiratoire. Elle s’impose donc comme indication thérapeutique incontournable et son efficacité n’est plus à prouver. En effet, l’utilisation de la ventilation mécanique a permis l’impact de l’atteinte respiratoire très tôt le pronostic vital. En 40 ans, ce traitement a permis d’allonger considérablement l’espérance de vie des malades, passant pour par exemple les myopathies de Duchenne de Boulogne de 15 ans à plus de 30 ans à l’heure actuelle.Aujourd’hui, pour ces personnes dont la durée de vie a pu être allongée, se pose l’inévitable question de leur Qualité de vie, d’autant plus que cet allongement de vie s’accompagne d’une aggravation de la déficience musculaire et donc des dysfonctions motrices. De plus, il apparaît que la ventilation mécanique, si elle assure un confort respiratoire indispensable, accroît considérablement le niveau de dépendance des malades et fait émerger chez eux de nouvelles problématiques identitaires, psychosociales ou même économiques. Il s’avère essentiel d’identifier les conséquences de la maladie et du Handicap qu’elle entraine. Il convient ensuite d’analyser l’impact direct de la ventilation mécanique sur la qualité de vie des malades et notamment son effet délétère sur la communication et la déglutition des patients. L’objectif principal de ce travail est de proposer en réponse à notre problématique des alternatives visant à améliorer la qualité de vie des patients en optimisant les deux grandes fonctions physiologiques que sont la parole et la déglutition
Neuromuscular diseases responsible of a wasting of the muscles, may involve severe respiratory failure. It is a major component of the disease, both in terms of prognosis and management. Up to now, only mechanical ventilation can compensate the respiratory disease. It is therefore required as an essential therapeutic indication and its effectiveness is already proven. Indeed, mechanical ventilation has allowed a significant increase of life expectancy. Over the past 40 years, this treatment has considerably increased the life expectancy of patients; for instance patients with Duchenne who passed away in their late teens survive now over their 30’s. Nowadays, for those people whose life has been extended, the question of their quality of life is unavoidable, especially as this longer life is accompanied by a worsening of muscle impairment and of motor disorder. Moreover, it appears that mechanical ventilation, if it provides breathing comfort, increases the level of dependency of patients and leads to the emerging psychological and even economical problems. It is essential to identify the consequences of the disease and the disability that it involves. It is then necessary to analyze the direct impact of mechanical ventilation on the quality of life of patients and especially its deleterious effects on communication and swallowing

Cette étude est consacrée à l'optimisation géométrique du contrôle actif dans les gaines de ventilation. La première partie de ce travail concerne l'étude du contrôle hybride (actif+passif) dans les gaines de ventilation et de ses avantages suivant la géométrie de la gaine et la présence ou non de revêtements absorbants. Les effets du contrôle passif du bruit (dissipatif, réflexif et diffusif) dans une gaine de ventilation améliorent l'efficacité du contrôle actif. Un contrôle hybride (actif + passif) présente donc des avantages, même aux basses fréquences. La seconde partie de ce mémoire s'intéresse au placement des microphones d'erreur et des sources secondaires. Pour une excitation harmonique, une méthode de calcul par programmation linéaire et entière détermine un nombre suffisant de microphones d'erreur ainsi qu'une position optimale des microphones d'erreur et des sources secondaires. Cette méthode de placement est appliquée pour la réduction du bruit dans les gaines de ventilation.