Investigating the characteristics of biomass wastes via particle feeder in downdraft gasifier.

Particle feeding plays a crucial role in the gasifier due to its effects on the efficiency and performance metrics of the thermochemical process. Investigating particle size distribution's impact on downdraft gasification reactor performance, this study delves into the significance of feedstock characteristics (moisture, volatile matter, fixed carbon, and ash contents) during the particle feeding stage. Various biomass wastes (date palm waste, olive pomace and sewage sludge) at diverse compositions and sizes are subjected to empirical determination of mass flow rates (MFR), power ratings, and storage times for each feedstock. The preheating process in the gasifier is considered, employing both an approximation and analytical solution. In addition, the influence of the equivalence ratio (ER) on the syngas yield is analyzed. The collected data reveals that for average particle size of 200 µm, the highest MFR (in g/min) are 0.518 ± 0.033, 7.691 ± 0.415, and 16.111 ± 1.050, for palm wood biomass, olive pomace and sewage sludge, respectively. Smaller particles (80 µm) led to extended storage times. Moreover, the lumped capacitance approximation method consistently underestimates preheating time, with a percentage error of 6.26%-17.08%. Response surface methodology (RSM) optimization analysis provides optimal gasification conditions for palm wood biomass, olive pomace, and sewage sludge with maximum cold gas efficiencies (CGEs) of 58.01%, 63.29%, and 52.27%. The peak conversion was attained at gasification temperatures of 1089.83 °C, 1151.93 °C, and 1102.91 °C for palm wood biomass, olive pomace, and sewage sludge, respectively. In addition, gasification equilibrium model determined optimal gasification temperatures as 1150 °C for palm biomass, 1200 °C for olive pomace, and 1150 °C for sewage sludge with respective syngas efficiencies of 59.62%, 64.13%, and 53.66%. Consequently, the examination of the dosing procedure, preheating dynamics, particle dimensions, ER, storage time, and their combined impacts offer practical insights to effectively control downdraft gasifiers in handling a variety of feedstocks.

Quantum Efficiency Measurement and Modeling of Silicon Sensors Optimized for Soft X-ray Detection.

Hybrid pixel detectors have become indispensable at synchrotron and X-ray free-electron laser facilities thanks to their large dynamic range, high frame rate, low noise, and large area. However, at energies below 3 keV, the detector performance is often limited because of the poor quantum efficiency of the sensor and the difficulty in achieving single-photon resolution due to the low signal-to-noise ratio. In this paper, we address the quantum efficiency of silicon sensors by refining the design of the entrance window, mainly by passivating the silicon surface and optimizing the dopant profile of the n+ region. We present the measurement of the quantum efficiency in the soft X-ray energy range for silicon sensors with several process variations in the fabrication of planar sensors with thin entrance windows. The quantum efficiency for 250 eV photons is increased from almost 0.5% for a standard sensor to up to 62% as a consequence of these developments, comparable to the quantum efficiency of backside-illuminated scientific CMOS sensors. Finally, we discuss the influence of the various process parameters on quantum efficiency and present a strategy for further improvement.

Hydrothermal and thermal-alkali pretreatments of wheat straw: Co-digestion, substrate solubilization, biogas yield and kinetic study.

Agro-waste having lignocellulosic biomass is considered most effective (heating value 16 MJ/kg) for energy production through anaerobic digestion (AD). However, recalcitrant lignocellulosic fraction in agro-waste obstructs its biotransformation and is a rate-limiting step of the process. This study investigated the effects of hydrothermal and thermal-alkaline pretreatment on anaerobic co-digestion of wheat straw (WS). The hydrothermal pretreatment of WS revealed that 60 min was the best pretreatment time to achieve the highest substrate solubilization. It was employed for thermal-alkali pretreatment at variable temperatures and NaOH doses. Thermal-alkali pretreatment at 125°C-7% NaOH shows the highest (34%) biogas yield of 662 mL/gVS, followed by 646 mL/gVS biogas yield at 150°C-1% NaOH assay (31% higher) over control. Although the 125°C-7% NaOH assay achieved the highest biogas yield, the 150°C-1% NaOH assay was found more feasible considering the cost of a 6% higher chemical used in the earlier assay. The thermal-alkali pretreatment was observed to reduce the formation of recalcitrant compounds (HMF, Furfural) and increase the buffering capacity of the slurry over hydrothermal pretreatment. Principal component analysis (PCA) of the various pretreatment and AD operational parameters was carried out to study their in-depth correlation. Moreover, a kinetic study of the experimental data was performed to observe the biodegradation trend and compare it with the Modified Gompertz (MG) and First Order (FO) models.

Using greenhouse gases in the synthesis gas production processes: Thermodynamic conditions.

The work concerns the thermodynamic analysis of CH4 reforming with various oxidants (CO2, H2O, O2) in the technological variants DRM (Dry Reforming of Methane) and TRM (Tri-reforming of Methane) technological variants. Both processes of synthesis gas production (raw material for the production of value-added products) are problematic in terms of environmental protection. In the process, two components of greenhouse gases are used as a substrate: CO2 and CH4. The influence of temperature, pressure, and the molar ratio of oxidants to methane on the efficiency of both processes was analyzed using the deterministic method: raw material conversion, product efficiency and selectivity - H2 and CO, and the value of the H2/CO ratio characterizing the suitability of the synthesis gas for various syntheses. The problem of carbon deposition tendency in DRM was minimized through the selection of operational process conditions, and in the case of TRM, it was fully reduced. The deterministic method of non-linear programming by defining the objective function with constraints helped formulate allowed one the values of TRM parameters: complete reduction of the coking problem, maintaining the H2/CO ratio at the desired level - 2 and CO2 conversion equal to 90%, led to a hydrogen efficiency of over 90%. This efficiency can be obtained at the process temperature T = 273 K, with a pressure of 1 atm, and the molar ratios of oxidants to methane: CH4/CO2/H2O/O2 = 1/0.36/0.77/0.01.

Management of biological sewage sludge: Fertilizer nitrogen recovery as the solution to fertilizer crisis.

In the current situation of a serious raw material crisis related to the disruption of supply chains, the bioeconomy is of particular significance. Rising prices and the problem with the availability of natural gas have made N fertilizers production very expensive. It is expected that due to natural gas shortages, conventional production of nitrogen fertilizers by chemical synthesis will be hindered in the coming season. An important alternative and an opportunity to solve the problems of fertilizer nitrogen availability are biological wastewater treatment plants, which can be treated as a renewable biological nitrogen mines. Sewage sludge (including activated sludge) contains up to 6-8% DM. N. Considering the quantity of sewage sludge generated in wastewater treatment plants, it can become an important raw material for the sustainable production of organic-mineral fertilizers from renewable resources available locally, with a low carbon footprint. Furthermore, the sewage sludge management method should take nitrogen retention into account and should not allow the emission of greenhouse gases containing nitrogen. This article analyzes the technological solutions of nitrogen recovery for fertilization purposes from biological wastewater treatment plants in the context of a new and difficult resource situation. Conventional and new nitrogen recovery methods were analyzed from the perspective of the current legal situation. An attempt was made to evaluate the possibility of implementing the assumptions of the circular economy through the recovery of renewable nitrogen resources from municipal wastewater treatment plants.

Maximizing the potential of leachate from sewage sludge as a sustainable nutrients source to alleviate the fertilizer crisis.

Leachate from separate digesters in biological wastewater treatment plants contains valuable biogenic compounds that can serve as fertilizer nutrients. In this study, a method was developed to utilize leachate from sewage sludge dewatering as a raw material for the preparation of a plant conditioner, providing water, nutrients, and growth-stimulating amino acids. A chemical conditioning procedure (65% HNO3) was used to prepare the leachate solution for fertilization. The feasibility of producing an amino acid-based fertilizer using shrimp shells and inorganic acids (96% H2SO4 and 85% H3PO4) was also demonstrated. Microbiological analysis confirmed the safety of the formulations, and chelation of micronutrients with available amino acids was proven (up to 100% chelating degree). The bioavailability of all nutrients was confirmed through extraction tests (extraction in neutral ammonium citrate). Germination tests showed similar fresh plant masses to those with commercial preparations, demonstrating the effectiveness of the developed technology. This approach aligns with circular economy principles and sustainable development and contributes to mitigating the impacts of climate change.

Biomass-based micronutrient fertilizers and biofortification of raspberries fruits.

The increasing amount of bio-waste creates the need to develop a method for efficient management based on processes that are more environmentally friendly than incineration and composting. This research aimed to utilize the waste of raspberry seeds after supercritical CO2 extraction. The biomass was enriched with micronutrients by the biosorption process to prepare micronutrient fertilizers for organic farming and biofortification of raspberries fruits. It was observed that at 100% dose of micronutrients, raspberry crop yield increased by 3%, and transfer of micronutrients to fruit biomass increased by 4.7%, 6.4%, and 8.8% (Cu, Mn, Zn, respectively) compared to commercial fertilizer. The supply of micronutrients at a dose of 150% led to a significant increase in micronutrient content of 3%, 41%, and 8% (Cu, Mn, and Zn, respectively) compared to commercial fertilizer. Research shows that the application of higher doses of micronutrients leads to the enrichment of edible parts of fruits, and fertilizers ensure environmental safety. The fruits contained on average 11.5% more microelements compared to the groups fertilized with the commercial product. The fruit yield (9.09-10.4 Mg per hectare) and the sugar content (9.82-10.2%) were also the highest. The micronutrients released from fertilizers and available to plants throughout the vegetation period affect the increase in yield, especially in the case of plants fruiting several times a year.

Recent innovations in various methods of harmful gases conversion and its mechanism in poultry farms.

Poultry breeding takes place in intensive, high-production systems characterized by high animal density, which is a source of harmful emission of odorous volatile organic compounds (VOCs), ammonia (NH3), hydrogen sulfide (H2S) and greenhouse gases, which in turn sustain animal welfare. This study identified and examined the characteristics of chemical compounds emitted in intensive poultry farming (laying hens, broilers) and their toxicity, which led to recommending methods of deodorization. Emphasis was placed on the law relative to air purification in poultry farms. Various methods of air treatment in poultry farms have been described: the modification of animal diet to improve nutrient retention and decrease the amount of their excrement; chemical oxidation technologies (ozonation, photocatalysis, Fenton reaction); various types/brands of biofilters, bioscrubbers and membrane reactors. Numerous studies show that biofilters can reduce ammonia emissions by 51%, hydrogen sulfide by 80%, odors by 67%, while scrubbers brings down ammonia emissions by 77% and odors by 42%, and the application of UV light lowers ammonia emissions by 28%, hydrogen sulfide by 55%, odors by 69% and VOCs by 52%. The paper presents both the solutions currently used in poultry farming and those which are currently in the research and development phase and, as innovative solutions, could be implemented in the near future.

Potential environmental pollution from copper metallurgy and methods of management.

This paper presents the latest overview of the environmental impact of wastes from the non-ferrous metallurgical industry. Ashes, slags and dusts - by-products from mining and metal processing - are sources of toxic metals, such as Pb, Cd, Hg, As, Al, as well as particulate matter. Physical, chemical and biological processes transform industrial wastes and cause water, soil and air pollution. Improperly protected heaps are subject to wind erosion and rain water leaching. Heavy metals and particulate matter are transported over long distances, contaminating the soil, living areas, watercourses, while in combination with mist they create smog. Water erosion releases heavy metals, which are leached into groundwater or surface runoff. This paper focuses on the range of pollution emissions from non-ferrous metallurgy wastes, hazards, mechanisms of their formation and fallouts, on the current state of technology and technological risk reduction solutions. The impact of pollution on human health and the biosphere, and methods of waste reduction in this industry sector are also presented. A sustainable and modern mining industry is the first step to cleaner production.

Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation.

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical details for calculating the kinematics, generalized forces, muscle forces, joint reaction loads, and predicting ground reaction wrenches during walking. Emphasis was given to reduce computational latency while maintaining accuracy as compared to the offline counterpart. Notably, we highlight the influence of adequate filtering and differentiation under noisy conditions and its importance for consequent dynamic calculations. Real-time estimates of the joint moments, muscle forces, and reaction loads closely resemble OpenSim's offline analyses. Model-based estimation of ground reaction wrenches demonstrates that even a small error can negatively affect other estimated quantities. An application of the developed system is demonstrated in the context of rehabilitation and gait retraining. We expect that such a system will find numerous applications in laboratory settings and outdoor conditions with the advent of predicting or sensing environment interactions. Therefore, we hope that this open-source framework will be a significant milestone for solving this grand challenge.

New directions for agricultural wastes valorization as hydrogel biocomposite fertilizers.

The tremendous amount of waste is an environmental and social problem worldwide. The agri-food sector is the largest producer of waste and requires the extensive use of fertilizers, which entails the need to look for innovative solutions in waste management. Properly recycled bio-waste can be reused as fertilizer. Polymer capsules with immobilized waste biomass can be applied as carriers for fertilizer nutrients. The amount of components exerts a certain influence on the effectiveness of copper ions binding. The most important physicochemical properties of biocomposites, such as swelling, SEM (Scanning Electron Microscopy) and FTIR (Fourier Transform Infrared Spectroscopy) were investigated. FTIR analyzes revealed that carboxyl and hydroxyl groups play a key role in Cu2+ ion binding. Morphology analysis showed that ion binding leads to homogenization of the composite surface, while coating the structure makes it more regular and cohesive. The sorption kinetics and the determination of the process's equilibrium parameters (Qmax = 29.4 ± 0.493 mg g-1) play an important role. The study of Cu2+ ion release in different media showed that the chitosan layer slowed down the diffusion of cations by about 50% in NaNO3 (1% m/m) solution. Preliminary studies of the applicability of the capsules in germination tests demonstrate that the biocomposites have no phytotoxic effects on the test plant. The chitosan coating slows the release of Cu2+ ions by about 20% compared to uncoated capsules. New fertilizer formulations containing chitosan-encapsulated hydrogel with biomass-immobilized micronutrients can be applied for precision agriculture to minimize the loss of fertilizer nutrients to the environment. These fertilizers could be used to cultivate houseplants and greenhouse crops.

Innovative high digestibility protein feed materials reducing environmental impact through improved nitrogen-use efficiency in sustainable agriculture.

Sustainable development in agriculture brings both environmental and economic benefits. Contemporary agriculture is also about increasing nutrient use efficiency, especially nitrogen, as the critical nutrient causing the most significant environmental pressure. This creates the need to produce highly digestible protein feed with high bioavailability, reducing losses of biogenic elements to feces. In this review, the latest trends and the potential for their implementation in sustainable agriculture have been compared, as well as the need to reduce the negative environmental impact of agriculture has been demonstrated. Applying local protein sources to feed animals reduces greenhouse gas emissions associated with transportation. The production of highly digestible fodder leads to a reduction in environmental pollution caused by excessive nitrogen outflows. Another approach indecreasing ammonia emissions from livestock farming is feed protein reduction and amino acid supplementation. All of the aforementioned approaches may result in beneficial long-term changes, contributing to environmental safety, animal welfare and human health.

Evaluation of the biogas potential of agricultural biomass waste for energy applications in Greece: A case study of the western Greece region.

Agricultural biomass can be best described as the organic matter residues from farming that remain within the fields after harvesting, along with tree trimmings. From the overall Greek Energy Balance, only a small fraction consists of biomass and this has been the main driving force behind this study. Due to the numerous ongoing agricultural activities, western Greece was selected as an ideal area for a case study. As a second step, the aim was to investigate the feasibility of the current anaerobic digestion plants to utilize the total biomass as feedstock. An additional scope to provide certifiable proof of the essential rural biomass assets available. Information on the potential of agricultural biomass is provided, with a focus on the performance specifications and the social advantages, but also the soil added substances and the produced biofuels. Subsequently, two options for waste management were discussed to illustrate the possibility of generating energy. The anaerobic digestion plants available in western Greece are illustrated in detail and the yearly rate of the main agrarian biomass is evaluated to be 715,080 tons. Arable crops, mechanical plants and tree trimming are recorded as the noteworthy sources. It is estimated that the proposed anaerobic digestion system will handle the entire amount of biomass and deliver max per year electricity 775 GWh and thermal energy 1.119 GWh.

Real-Time Prediction of Joint Forces by Motion Capture and Machine Learning.

Conventional biomechanical modelling approaches involve the solution of large systems of equations that encode the complex mathematical representation of human motion and skeletal structure. To improve stability and computational speed, being a common bottleneck in current approaches, we apply machine learning to train surrogate models and to predict in near real-time, previously calculated medial and lateral knee contact forces (KCFs) of 54 young and elderly participants during treadmill walking in a speed range of 3 to 7 km/h. Predictions are obtained by fusing optical motion capture and musculoskeletal modeling-derived kinematic and force variables, into regression models using artificial neural networks (ANNs) and support vector regression (SVR). Training schemes included either data from all subjects (LeaveTrialsOut) or only from a portion of them (LeaveSubjectsOut), in combination with inclusion of ground reaction forces (GRFs) in the dataset or not. Results identify ANNs as the best-performing predictor of KCFs, both in terms of Pearson R (0.89-0.98 for LeaveTrialsOut and 0.45-0.85 for LeaveSubjectsOut) and percentage normalized root mean square error (0.67-2.35 for LeaveTrialsOut and 1.6-5.39 for LeaveSubjectsOut). When GRFs were omitted from the dataset, no substantial decrease in prediction power of both models was observed. Our findings showcase the strength of ANNs to predict simultaneously multi-component KCF during walking at different speeds-even in the absence of GRFs-particularly applicable in real-time applications that make use of knee loading conditions to guide and treat patients.

Deep CNN Sparse Coding for Real Time Inhaler Sounds Classification.

Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indicates, medication adherence can effectively be monitored by successfully identifying actions performed by patients during inhaler usage. This study focuses on the recognition of inhaler audio events during usage of pressurized metered dose inhalers (pMDI). Aiming at real-time performance, we investigate deep sparse coding techniques including convolutional filter pruning, scalar pruning and vector quantization, for different convolutional neural network (CNN) architectures. The recognition performance has been assessed on three healthy subjects following both within and across subjects modeling strategies. The selected CNN architecture classified drug actuation, inhalation and exhalation events, with 100%, 92.6% and 97.9% accuracy, respectively, when assessed in a leave-one-subject-out cross-validation setting. Moreover, sparse coding of the same architecture with an increasing compression rate from 1 to 7 resulted in only a small decrease in classification accuracy (from 95.7% to 94.5%), obtained by random (subject-agnostic) cross-validation. A more thorough assessment on a larger dataset, including recordings of subjects with multiple respiratory disease manifestations, is still required in order to better evaluate the method's generalization ability and robustness.

Integrating an openEHR-based personalized virtual model for the ageing population within HBase.

BACKGROUND: Frailty is a common clinical syndrome in ageing population that carries an increased risk for adverse health outcomes including falls, hospitalization, disability, and mortality. As these outcomes affect the health and social care planning, during the last years there is a tendency of investing in monitoring and preventing strategies. Although a number of electronic health record (EHR) systems have been developed, including personalized virtual patient models, there are limited ageing population oriented systems. METHODS: We exploit the openEHR framework for the representation of frailty in ageing population in order to attain semantic interoperability, and we present the methodology for adoption or development of archetypes. We also propose a framework for a one-to-one mapping between openEHR archetypes and a column-family NoSQL database (HBase) aiming at the integration of existing and newly developed archetypes into it. RESULTS: The requirement analysis of our study resulted in the definition of 22 coherent and clinically meaningful parameters for the description of frailty in older adults. The implemented openEHR methodology led to the direct use of 22 archetypes, the modification and reuse of two archetypes, and the development of 28 new archetypes. Additionally, the mapping procedure led to two different HBase tables for the storage of the data. CONCLUSIONS: In this work, an openEHR-based virtual patient model has been designed and integrated into an HBase storage system, exploiting the advantages of the underlying technologies. This framework can serve as a base for the development of a decision support system using the openEHR's Guideline Definition Language in the future.

Introduction of the trapezoidal thermodynamic technique method for measuring and mapping the efficiency of waste-to-energy plants: A potential replacement to the R1 formula.

Waste-to-energy plants have the peculiarity of being considered both as energy production and as waste destruction facilities and this distinction is important for legislative reasons. The efficiency of waste-to-energy plants must be objective and consistent, independently if the focus is the production of energy, the destruction of waste or the recovery/upgrade of materials. With the introduction of polygeneration technologies, like gasification, the production of energy and the recovery/upgrade of materials, are interconnected. The existing methodology for assessing the efficiency of waste-to-energy plants is the R1 formula, which does not take into consideration the full spectrum of the operations that take place in waste-to-energy plants. This study introduces a novel methodology for assessing the efficiency of waste-to-energy plants and is defined as the 3T method, which stands for 'trapezoidal thermodynamic technique'. The 3T method is an integrated approach for assessing the efficiency of waste-to-energy plants, which takes into consideration not only the production of energy but also the quality of the products. The value that is returned from the 3T method can be placed in a tertiary diagram and the global efficiency map of waste-to-energy plants can be produced. The application of the 3T method showed that the waste-to-energy plants with high combined heat and power efficiency and high recovery of materials are favoured and these outcomes are in accordance with the cascade principle and with the high cogeneration standards that are set by the EU Energy Efficiency Directive.

Substance deposition assessment in obstructed pulmonary system through numerical characterization of airflow and inhaled particles attributes.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and asthma are considered as the two most widespread obstructive lung diseases, whereas they affect more than 500 million people worldwide. Unfortunately, the requirement for detailed geometric models of the lungs in combination with the increased computational resources needed for the simulation of the breathing did not allow great progress to be made in the past for the better understanding of inflammatory diseases of the airways through detailed modelling approaches. In this context, computational fluid dynamics (CFD) simulations accompanied by fluid particle tracing (FPT) analysis of the inhaled ambient particles are deemed critical for lung function assessment. Also they enable the understanding of particle depositions on the airways of patients, since these accumulations may affect or lead to inflammations. In this direction, the current study conducts an initial investigation for the better comprehension of particle deposition within the lungs. More specifically, accurate models of the airways obstructions that relate to pulmonary disease are developed and a thorough assessment of the airflow behavior together with identification of the effects of inhaled particle properties, such as size and density, is conducted. Our approach presents a first step towards an effective personalization of pulmonary treatment in regards to the geometric characteristics of the lungs and the in depth understanding of airflows within the airways. METHODS: A geometry processing technique involving contraction algorithms is established and used to employ the different respiratory arrangements associated with lung related diseases that exhibit airways obstructions. Apart from the normal lung case, two categories of obstructed cases are examined, i.e. models with obstructions in both lungs and models with narrowings in the right lung only. Precise assumptions regarding airflow and deposition fraction (DF) over various sections of the lungs are drawn by simulating these distinct incidents through the finite volume method (FVM) and particularly the CFD and FPT algorithms. Moreover, a detailed parametric analysis clarifies the effects of the particles size and density in terms of regional deposition upon several parts of the pulmonary system. In this manner, the deposition pattern of various substances can be assessed. RESULTS: For the specific case of the unobstructed lung model most particles are detected on the right lung (48.56% of total, when the air flowrate is 12.6 L/min), a fact that is also true when obstructions arise symmetrically in both lungs (51.45% of total, when the air flowrate is 6.06 L/min and obstructions occur after the second generation). In contrast, when narrowings are developed on the right lung only, most particles are pushed on the left section (68.22% of total, when the air flowrate is 11.2 L/min) indicating that inhaled medication is generally deposited away from the areas of inflammation. This observation is useful when designing medical treatment of lung diseases. Furthermore, particles with diameters from 1 µm to 10 µm are shown to be mainly deposited on the lower airways, whereas particles with diameters of 20 µm and 30 µm are mostly accumulated in the upper airways. As a result, the current analysis indicates increased DF levels in the upper airways when the particle diameter is enlarged. Additionally, when the particles density increases from 1000 Kg/m3 to 2000 Kg/m3, the DF is enhanced on every generation and for all cases investigated herein. The results obtained by our simulations provide an accurate and quantitative estimation of all important parameters involved in lung modeling. CONCLUSIONS: The treatment of respiratory diseases with inhaled medical substances can be advanced by the clinical use of accurate CFD and FPT simulations and specifically by evaluating the deposition of inhaled particles in a regional oriented perspective in regards to different particle sizes and particle densities. Since a drug with specific characteristics (i.e. particle size and density) exhibits maximum deposition on particular lung areas, the current study provides initial indications to a qualified physician for proper selection of medication.

Energy Efficient Monitoring of Metered Dose Inhaler Usage.

Life-long chronic inflammatory diseases of the airways, such as asthma and Chronic Obstructive Pulmonary Disease, are very common worldwide, affecting people of all ages, race and gender. One of the most important aspects for the effective management of asthma is medication adherence which is defined as the extent to which patients follow their prescribed action plan and use their inhaler correctly. Wireless telemonitoring of the medication adherence can facilitate early diagnosis and management of these diseases through the use of an accurate and energy efficient mHealth system. Therefore, low complexity audio compression schemes need to be integrated with high accuracy classification approaches for the assessment of adherence of patients that use of pressurized Metered Dose Inhalers (pMDIs). To this end, we propose a novel solution that enables the energy efficient monitoring of metered dose inhaler usage, by exploiting the specific characteristics of the reconstructed audio features at the receiver. Simulation studies, carried out with a large dataset of indoor & outdoor measurements have led to high levels of accuracy (98 %) utilizing only 2 % of the recorded audio samples at the receiver, demonstrating the potential of this method for the development of novel energy efficient inhalers and medical devices in the area of respiratory medicine.