Alzheimer’s disease (AD) is a degenerative brain disease with a high and irreversible incidence. In recent years, because brain signals have complex nonlinear dynamics, there has been growing interest in studying complex changes in the time series of brain signals in patients with AD. We reviewed studies of complexity analyses of single-channel time series from electroencephalogram (EEG), magnetoencephalogram (MEG), and functional magnetic resonance imaging (fMRI) in AD and determined future research directions. A systematic literature search for 2000–2019 was performed in the Web of Science and PubMed databases, resulting in 126 identified studies. Compared to healthy individuals, the signals from AD patients have less complexity and more predictable oscillations, which are found mainly in the left parietal, occipital, right frontal, and temporal regions. This complexity is considered a potential biomarker for accurately responding to the functional lesion in AD. The current review helps to reveal the patterns of dysfunction in the brains of patients with AD and to investigate whether signal complexity can be used as a biomarker to accurately respond to the functional lesion in AD. We proposed further studies in the signal complexities of AD patients, including investigating the reliability of complexity algorithms and the spatial patterns of signal complexity. In conclusion, the current review helps to better understand the complexity of abnormalities in the AD brain and provide useful information for AD diagnosis. Alzheimer’s disease (AD) is the most prevalent form of neurodegenerative dementia and includes a set of symptoms, such as memory loss and cognitive decline, that affect the ability to engage in daily activities and processes, including attention, thinking, orientation, or language ,2. In ADBrain imaging analyses have been widely used to explore the mechanisms of AD ,9,10 andIn the present review, we systematically examined 126 identified studies on the complexity of AD from 2000 to 2019. We aim to review the complexity indexes that can accurately represent the functional lesion in AD and outline the better complexity indicators. In addition, by analyzing changes in patients through general trends and comparative studies of brain regions, we identified our knowledge gaps as well as new issues for future research that can serve as a starting point for future applications of complexity analysis for AD patients.Entropy (En) is one of the most commonly used nonlinear concepts in evaluating the dynamic characteristics of signals . This coAlthough they continue to be rigorous and widespread methods used in the analysis of the frequency domain, linear decomposition methods, such as spectral analysis, have recently been suggested to lead to a loss of unique information that is orthogonal to average activity ,32. RenyIn addition to the entropy method, there are many other methods for assessing complexity, such as the Hurst exponent (HE), the Lempel-Ziv complexity (LZC), the correlation dimension (D2), and the fractal dimension (FD). The HE is mainly used to measure the long-term memory and fractal dimension of a time series . The LZCWe examined the use of complexity techniques in the brain imaging of AD patients by performing an overview of these studies. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)  was usedA large number of nonlinear methods have been applied to analyze the characteristics of brain activity in patients with AD, and numerous interesting results have been found. Since resting-state data are not influenced by task-related activation or differences in motivation or performance, these recordings provide more reliable estimates of brain adaptability ,63. RecoIn this section, we review the signal complexity of the resting-state electroencephalogram (rsEEG) in SCI, MCI, and AD patients compared with normal controls (NCs). Several studies have shown that multiple complexity methods, such as LZC, entropy complexity, and other complexity features, differ among SCI, MCI, AD, and control subjects when applied to EEG signals. Hogan et al.  found thWe think that the reduction in the irregularity or complexity of brain signals can be described by a decrease in the dynamic complexity of the brain . Our revEntropy-based MSE analyses can measure the probability of sequences generating new information at different scales and have been applied to cognitive neuroscience. Deng et al.  studied Alqazzaz et al.  found thEn value in the alpha  power and an increase in low-frequency (delta and theta) power . We averpossible . The valIt has been reported that different frequency bands reflect different brain dynamics . We founJeong et al.  found thIn this section, In this section, we review the signal complexity of the MEGs in MCI and AD patients compared with NC participants. The temporal resolution of MEG signals can reach the millisecond level, and the spatial resolution can be less than 2 mm. We found that the research could be generally divided based on the analysis of different brain regions to identify trends in these values. MEG is a noninvasive technique that allows recording of the magnetic fields generated by brain neuronal activity. MEG signals are independent of any reference point and are less affected by extracerebral tissues than EEG signals ,107.Gómez et al. ,109 analWe found that most of the studies were divided based on the analysis of different brain regions and were analyzed on different scales. At low scale factors, the entropy value in AD patients was lower than that in NCs. For high scale factors, the values in AD patients were higher than those in controls. Nonlinear analysis of frequency has also been reported in MEG-based studies by SpecEn and ratios. Poza et al.  studied Gómez et al.  researchIn this section, The fMRI uses magnetic array imaging ,128, whiThe fMRI signals have been used to detect functional abnormalities associated with neuropsychiatric and neurological disorders. Maxim et al.  applied Complexity methods applied to brain imaging data such as EEG, MEG and fMRI provide useful information for the diagnosis of AD using abnormal brain activity signals. This review combines previous findings with a larger overview and a further characterization of multiple modes for a better understanding of the functional lesion in AD. For the complexity of the single-channel time series, the development process of AD is clear and independent of the method used. The decline in AD may be due to plaques and cell death leading to loss of connectivity between cortical neurons, which may lead to more regular brain signals, thus destroying effective communication throughout the brain ,136. FurComplexity methods are suitable for the study of nonlinear brain changes and are sensitive to neurological changes associated with AD patients compared with normal subjects. The entropy method accounts for a large proportion of the complexity methods used. Better performance was exhibited at high scales, and when more brain regions were included in the analysis, the trends were more obvious. The exploration of test–retest reliability and improvements in entropy algorithms will provide great guidance for future applications. As the brain is a complex system in time and space, we can also study network entropy and spatio-temporal entropy in the future. While fMRI has a spatial resolution on the order of millimeters, only a small number of studies have applied complexity to fMRI data to date. Although the time resolution is not very high, it also reacts well and has been used to identify downward trends in different brain regions. It is also important to note that the potential utilization of the high spatial resolution in fMRI and fNIRS data can provide more in-depth information for AD brain dysfunction.Complexity analysis of different types of brain imaging data in AD patients has yielded consistent results. The results showed consistent changes in that the signals in the brains of AD patients are slower, more regular, less complex, and less well organized than those of NCs. The reduction in the irregularity and complexity of brain signals in AD is the main finding obtained, and the occipital, frontal, parietal, and temporal areas are the most affected regions. We found that complexity can capture changes in areas of the brain that are initially affected by AD and accurately respond to its pathological mechanism. Complexity is a promising biomarker in reflecting the pathological mechanism of AD, and entropy is the more widely used of the numerous complexity indicators described in this review. For which entropy index is the best, more research is needed in the future to prove it. In general, different modalities for the same groups with large amounts of data were analyzed by choosing methods with high reliability and accuracy, the results of which will aid in truly understanding the functional lesion in AD. The results of the articles in this review can advance research on quantifying the complexity indexes of different subjects until clinical application is realized.


Refurbishment and remanufacturing are the industrial processes whereby used products or parts that constitute the product are restored. Remanufacturing is the process of restoring the functionality of the product or a part of it to “as-new” quality, whereas refurbishment is the process of restoring the product itself or part of it to “like-new” quality, without being as thorough as remanufacturing. Within this context, the EU-funded project RECLAIM presents a new idea on refurbishment and remanufacturing based on big data analytics, machine learning, predictive analytics, and optimization models using deep learning techniques and digital twin models with the aim of enabling the stakeholders to make informed decisions about whether to remanufacture, upgrade, or repair heavy machinery that is toward its end-of-life. The RECLAIM project additionally provides novel strategies and technologies that enable the reuse of industrial equipment in old, renewed, and new factories, with the goal of saving valuable resources by recycling equipment and using them in a different application, instead of discarding them after use. For instance, RECLAIM provides a simulation engine using digital twin in order to predict maintenance needs and potential faults of large industrial equipment. This simulation engine keeps the virtual twins available to store all available information during the lifetime of a machine, such as maintenance operations, and this information can be used to perform an economic estimation of the machine's refurbishment costs. The RECLAIM project envisages developing new technologies and strategies aligned with the circular economy and in support of a new model for the management of large industrial equipment that approaches the end of its design life. This model aims to reduce substantially the opportunity cost of retaining strategies (both moneywise and resourcewise) by allowing relatively old equipment that faces the prospect of decommissioning to reclaim its functionalities and role in the overall production system. High inRE-manufaCturing and Refurbishment LArge Industrial equipment), focuses on establishing and demonstrating technologies and techniques in order to support a new approach for refurbishment and remanufacturing of large industrial equipment in factories, setting forth the way to a circular economy. The project's main aim is to improve the maintenance process, emphasizing the methods of refurbishment and remanufacturing. Its ultimate objective is to preserve valuable resources by reusing equipment instead of discarding it. In this context, the project will develop new models and strategies for repairing and upgrading equipment and redesigning factory layouts to benefit the manufacturing sector from an economic perspective. These strategies are as follows: improving the machinery operation and avoiding unplanned downtime due to machine failure; estimating life cycle costs and contributing to the reuse of old machinery assets in renewed and new factories; providing maintenance able to identify equipment failures before they occur, in order to minimize the additional costs and downtime associated with the disassembly and transportation of the machinery and maximize the performance of the machinery during its lifetime.The EU Factory of the Future project, RECLAIM  decision support framework (DSF), (b) refurbishment and remanufacturing techniques for industrial equipment, (c) smart sensors’ network for industrial environments, (d) prognosis and health management, (e) cost analysis and cost modeling, (f) optimization planning on refurbishment and remanufacturing, (g) digital twin simulation engine, (h) cybersecurity for IoT devices, and (i) augmented reality (AR).2.1.1.Several methodologies and approaches for decision-making have been developed, addressing either single or multiple decisions, in order to enable the users and the process experts to assess the reusability or remanufacturability of production machines when they are facing the end of their production life. Decision Support Framework) take into account.The aforementioned studies introduced several decision-making methodologies and frameworks that utilize fuzzy logic and include background of the product, environmental criteria, and stakeholders with the intention of providing a reasonable decision for the recovery or rejection of the product. Nevertheless, few of them could help to achieve both machine- and component-level health-based recovery planning while taking into account at the same time both environmental and economic reverberations. Thus, RECLAIM aims to develop a flexible recovery DSF to assist the machinery operators and machinery manufacturers in making efficient remanufacturing, repair, or rejection decisions at different service life periods on electromechanical machines and robotic systems. The proposed solution will combine inputs from optimization techniques, machine learning, digital twins, fault diagnosis, and predictive maintenance simulations.2.1.2.Refurbishment and remanufacturing can contribute significantly to well-being in Europe, as they are important lifetime extension strategies of resource-efficient manufacturing. In particular, the refurbishment process restores the system to meet its original specifications without replacing parts of the system . NumerouWith RECLAIM, a set of novel tools and methodologies will be developed for enhancing the refurbishment and remanufacturing processes for industrial electromechanical machines and robotic systems, differentiating the approach according to the level of action . This approach is aiming not only to improve refurbishment and remanufacturing processes but also to participate in effective decision-making so as to achieve measurable performance improvements. The adaptive sensor network and digital retrofitting infrastructure will have the ability to be attached to machines, modules, and even components to be refurbished or remanufactured. This will allow legacy equipment to be a part of the IoT with advanced vertical and horizontal communication capabilities and also enable sophisticated data analysis, such as predictive maintenance. Those services will be supported by AR mechanisms (AR glasses) that will help technicians and manufacturers with a novel way to visualize and localize information on equipment refurbishment and remanufacturing operations directly situated on top of the physical equipment.2.1.3.Applications in the manufacturing domain, regarding real-time monitoring, maintenance planning, fault detection, etc., based on sensor network and data have yet to be widely adopted. In order to provide automated knowledge extraction from big data gathered by the industrial partners, RECLAIM will use smart real-time control and data analytics, monitoring forecasted production lines and allowing prescriptive and preventative actions. RECLAIM will enable “just-in-time manufacturing” to continuously adjust to the business environment. The analytic tools will allow to easily adapt a) the quantity and variability of heterogeneous information sources across the factory life cycle, b) the different types of targeted manufacturing sectors and their structure, and c) the differences in the enterprise hierarchy level.2.1.4.To determine if a machine is worth refurbishing or remanufacturing, a Prognostics and Health Management (PHM) technique will be used for the estimation of the life cycle cost in relation to the maintenance activities of the machine. Many works have indicated that PHM techniques are used to reduce losses due to reliability issues . Moreovein situ edge-monitoring of PHM provides diagnosis information so that the degradation levels of critical components are estimated in near real-time. The outcome of edge analysis is combined with machine specifications and historical trends to create a trustworthy RECLAIM DSF that can bring benefits in terms of reduced costs and the environmental footprint of manufacturing activities.RECLAIM PHM will address the three main challenges concerning the refurbishment of a machine. First, is the machine worth refurbishing? Second, what is the best time to perform refurbishment at the least cost? Finally, how should the machine be refurbished? To determine if a machine is worth refurbishing, the RECLAIM implements well-established PHM techniques to estimate the life cycle cost associated with the refurbishment of the machine. If the cost of refurbishment is lower than that of a new machine, then it is a cost-effective option. In RECLAIM, the optimal time to perform refurbishment is determined by extracting a machine health indicator through PHM and estimating the RUL of the machine based on the indicator. Ideally, the machine should be refurbished close to the end of its life. To determine how the machine should be refurbished, Therefore, detailed knowledge of the health status of the machinery and its components and the whole production line based on data of the RECLAIM PHM toolkit will offer peer-to-peer health evaluation of the machine and component predictive methods to increase asset uptime; RECLAIM will be able to identify the optimal time and the appropriate components for refurbishment or/and remanufacturing.2.1.5.Cost analysis and modeling cover the cost throughout the product life cycle, including design, manufacturing, service, and disposal. Manufacturing cost analysis and modeling have been well researched. Manufacturing costs normally include material costs, machining costs, and assembly costs, and the machining and assembly costs are normally calculated on the basis of the process design conducted by the production engineers . The proWithin RECLAIM, a real-time  accurate cost estimation model will be developed. This cost model will allow responsive and optimized decision-making regarding production and maintenance. This is achieved by conducting dynamic data collection based on the project's backbone big data infrastructure so that a real-time  accurate cost estimation can be carried out, which reflects the cost implications of real-time maintenance and projected disruptions to the production.2.1.6.Refurbishment and remanufacturing activities in a finite planning horizon are discussed thoroughly in the scientific literature. In the work of Although several researchers have suggested various remanufacturing models, fewer researchers have been able to address the problems in both business and strategic decision-making at the same time. In this project, some mathematical models for decision-making at both business and strategic levels in a remanufacturing environment are proposed. The functionality and the performance of the suggested models are thoroughly examined through computational experiments, simulation schemas of model parameters, and extensive data analysis from multimodal data sources.2.1.7.The first attempt to analyze the concept of “twin” was made by NASA's Apollo Project in which researchers simulated the aircraft's twin body in a real physical system . In thisIn order to optimize maintenance activities , RECLAIM will deploy a simulation engine that will create a virtual environment similar to the actual machine using the digital twin model. This model will analyze patterns in real-time and compare them with historical data about the machinery life cycle. The aim is to monitor and predict the performance and status of factory assets. In this manner, all the necessary information for the preparation and implementation of proper maintenance activities on the machines will be provided so that failures and production line stoppages are avoided. For this purpose, RECLAIM's digital twin model will be divided into three parts, i.e., the physical system , the digital system , and the data and information connection system that links the digital system with the physical system. RECLAIM's digital twin model saves time and money and helps reduce costly production downtimes as it predicts promptly possible failures in infrastructure.Digital twin component, given in 2.1.8.Poor usability of cybersecurity solutions tends to be the effect of security constraints. Finding the right trade-off between usability and security or the preferable integration of usability and security requirements is part of a major research challenge, which recently has been addressed by scholars . For insWithin this project, the edge-computing capabilities of the proposed RECLAIM Solution will be enhanced with lightweight security methods in order to empower resilience to cyberattacks and intrusion detection and prevention. This will allow shared access and flexibility in data governance for edge-based applications and reconfiguration and actuation. Moreover, in order to ensure seamless and trusted service provision over different data, the RECLAIM Solution will be enhanced with capabilities related to the dynamic coupling of microservices offered and embedded devices involved.2.1.9.AR is an emerging technology that can help manufacturers and maintainers, providing the necessary information which are needed regarding the maintenance/refurbishment/remanufacturing procedure by displaying virtual information on top of it. The main challenges faced by manufacturers or maintainers are as follows: (a) a large variety of tasks from diagnosis to repair; (b) varying complexity of maintenance requirements; (c) long life of equipment causing varying levels of quality, standards, and depth in documentation; (d) a large number of equipment types to maintain. It is noteworthy that AR offers opportunities for industrial maintenance applications by displaying contextualized information and accessing end-user data.AR has received increasing attention from researchers in the manufacturing technology community as it is an interactive experience of a real-world environment and a technology that expands the physical world, adding on top of it layers of digital  information . AR makeThe RECLAIM project aims at using AR techniques to support maintenance operations in the industrial domain by creating augmented features in real-time. More specifically, the RECLAIM AR-enabled multimodal interaction system will address the above challenges as it will provide a novel way to visualize and localize information on equipment refurbishment and remanufacturing operations directly situated on top of the physical equipment. During the refurbishment and remanufacturing operations, the system will also provide animated 3D stepwise instructions on disassembly and reassembly required, as well as support in the form of on-the-job remote assistance with real-time audio-visual communication and 3D annotation to technicians during the procedure. In this way, the variety of tasks from diagnosis to repair is addressed by showing the steps that the technician must follow to repair or maintain the machine. Also, information about the useful lifetime of the machine will be displayed as pop-up messages. At the end of the repair, a function registration message will appear that will take into account the different quality levels, standards maintained, etc. One more functionality of this solution is that the system itself performs the authoring steps that require AR expertise and maintainers have to indicate the key information for display, defining its format and sequence. The Authoring Platform is a human-machine interaction interface that allows maintainers to interact with the “Information Frameworks” used for creating AR features. The Application Platform Modules automatically generate AR features according to maintainers' feedback. Apart from contextualizing and rendering maintenance information, they ensure that the information is displayed in the right sequence. The developed system is versatile and effective regarding the support of the maintenance work of both novice and more experienced technicians.2.2.Despite the numerous advances of the RECLAIM Solution, some possible limitations have been considered. First of all, some pilots had not stored any related data before the beginning of the project, so training machine learning models or statistical analyses cannot be done based on many data from the past. This will raise the need for estimations based on information found in the bibliography about similar equipment. Also, probably some data  cannot be provided automatically by some hardware, so the end-users will have to interact with the RECLAIM platform to insert them manually. Furthermore, due to the complexity of interdependencies among software components and the algorithm underlying each of these components, it is possible for computational delays to occur due to the communication latency and/or time complexity of algorithms. In addition, the memory aspect should be taken into account. Given the plenty of pilot raw data, corresponding to several machines and their physical components, and output data from numerous software components, it may be challenging for a single database to store all of them.2.3.Several pilot sites across Europe will be used for demonstration, evaluation, and assessment activities of the RECLAIM project. Due to confidentiality issues, the pilot sites will not be named here. The RECLAIM framework will be tested on a white goods company for (a) refurbishment and renovation of robot cells in B-Cell for making tubs ; (b) modernization and refurbishment of an automatic spraying cabin, using enamel powder applied with help of spraying guns, in a shoe-making factory for maintenance and upgrade of cutting machines , in a wood manufacturing plant for predictive maintenance and refurbishment of the woodworking large production line ), in friction welding machinery for lifetime extension by remanufacturing and predictive maintenance , and finally in a bleaching machine for maintenance, refurbishment, and upgrading .3.DSF, the in situ repair data analytics, and the refurbishment and remanufacturing framework. Finally, the topmost part of the proposed conceptual architecture is the User(s) Interfaces (UI), along with the manufacturing industries, the maintenance supportive companies, and the European Remanufacturing Network (ERN).3.1.DSF, the in situ repair data analytics, and the refurbishment and remanufacturing framework, which are described in detail as follows.As mentioned above, the key components of the RECLAIM platform are the 3.1.1.DSF component is designed to support and improve the effectiveness of decisions concerning the refurbishment and remanufacturing of production infrastructure. The DSF will identify the most suitable actions/strategies based on different criteria such as the impact and the value of refurbishment or enhanced maintenance to extend asset life, the optimal time for replacing an asset, the machines' condition and possible upcoming failures, production planning, and resources allocation. The DSF will include novel tools as follows: the Cost Modeling and Financial Analysis toolkit ; the Adaptive Sensorial Network and Fog Computing Framework ; the Prognostic and Health Management toolkit ; the Fault Diagnosis and Predictive Maintenance Simulation Engine using Digital Twin ; the Optimization Toolkit for Refurbishment and Remanufacturing Planning . The proposed DSF will have attributes from both knowledge-driven and model-driven types of DSF based on the implementation of nondeterministic finite-state automata (finite number of states for the specified machine), simple scoring mechanisms, rule-based decision-making, and AI algorithms. Moreover, the implementation of data mining algorithms such as decision trees, genetic algorithms, and support vector machines will ensure the extraction of valuable information from IoT data. A Visual Analytics Suite will be built on the top of DSF in order to provide users with the most effective presentation of DSF output in the form of strategies, alternatives process models, KPIs visualization, and real-time health assessment of different production aspects.The 3.1.2.Industrial analytics are used to identify and recognize machine operational and behavioral patterns, make fast and accurate predictions, and act with confidence at the points of decision. Situational awareness as a mental state can be considered as a state of knowledge, which can be achieved using various techniques. In particular, in order to raise awareness of the health status of the machine and the situation of the shop floor during maintenance activities, data analytics techniques can be deployed. So, the knowledge about the situation of machines or/and shop floor can be gained from descriptive analytics , predictive analytics , and prescriptive analytics . In addition, big data methodologies  for the analytics of the big and diverse volume of available data gathered by the industrial partners also can give some valuable information about situational awareness. Visual analytics and advanced information visualization technologies can be exploited to present relevant information to different users (shop-floor manager(s), technician(s), manufacturer(s), etc.) in a user-friendly and effective manner. In particular, visual analytics has historically played a key role in business processes optimization. Existing tools can be of great assistance for the visualization of spatiotemporal data in the plant-site/shop-floor, providing temporal plots and heat maps indicating specific types of activities and representation of process time series data along with statistical analysis suitable to assist in discovering variable correlation. The proposed visual analytics suite will be developed based on two major stages so as to support situational awareness: perception (monitoring), which refers to the knowledge of the elements in the environment of plant-site/shop-floor, and comprehension (inspection and exploring), which refers to the combination and the integration of elements received by the sensors network. In terms of on-site repair analytics, both streaming analytics from the field of the repair  and batch analytics results based on on-demand queries will be applied in a planning time horizon so as to ensure enhancing human decisions and understanding and generating significant confidence in the final decision.3.1.3.Adaptive Sensorial Network together with recognition of any system constraints and behaviors.Production planning, scheduling, and control of the fleet of an industrial ecosystem are major managerial challenges in the field of management operations in a manufacturing environment. A complete system approach is important to address all aspects of the production planning optimization, taking into account refurbishment and remanufacturing activities. This component aims to support the planning optimization through multivariable monitoring of the machine's operational parameters where the effects of variable changes will be possible to determine and combine best-known practices methodologies for model-based plant-site/shop-floor control. Based on the multimodal data provided by the IoT infrastructure, new approaches of real-time production planning optimization algorithms, from the perspective of machine learning techniques, will be researched and developed to apply proven optimization methodologies, provide the answers an end-user needs for effective decision-making, and consequently delivers measurable performance improvements. The data and information requirements are integral parts of the optimization phase. To create clear value from this information, production monitoring and surveillance is the first step in the measurement phase and is a prerequisite to analysis, improvement, and control. This monitoring might take into consideration the data collected from the 3.2.DSF for refurbishment and remanufacturing optimization goes beyond the state of the art by allowing automatic and concurrent multiobjective (particularly for three or more objectives) decision-making and assessing multiobjectives in the same turn, so it provides efficient and optimized decision support.In Situ Repair Data Analytics for situational awareness will be a flexible tool, allowing the end-users to connect and integrate with any data source in real-time so as to have the ability for online visualization of significant KPIs for the current status of the machine (inspection) and the repair process. Condition analytics will be a key component that will combine state-of-the-art condition monitoring in order to go beyond machine health management.Refurbishment and Remanufacturing Framework will be enhanced with RECLAIM Solution having a sole objective; that is, the quality of remanufacturing/refurbishment process will have to follow strict reconditioning operations (steps). This effort will be supported by AR tools that utilize the sense of the worker, the ambient environment, and the context of work in the plant-site/shop floor.RECLAIM is an ambitious project that will create and deploy an integrated DSF for machinery lifetime extension. The DSF for the optimization of refurbishment and remanufacturing process in itself is a significant step beyond the state of the art in the provisioning of infrastructure, tools, and services for experimentation in the digital manufacturing domain. The RECLAIM project will offer the following core innovations:4.when is the right time to refurbish or remanufacture industrial machinery, what is the appropriate strategy to follow, which benefits should the manufacturing company expect, and how this strategy will be implemented to deliver those benefits while providing enhanced reliability and safety of the refurbished or remanufactured equipment. The advanced RECLAIM framework aims to assist the machinery operators and machinery manufacturers in making efficient EoL decisions at different service life periods. This framework will consist of the following: a) the core RECLAIM toolkit ; b) a reference architecture along with a set of circular economy strategies and methodologies for manufacturing companies and OEMs.The RECLAIM framework ensures that the remanufacturing and refurbishing interventions make a positive contribution not only toward business  but also toward the environment . In particular, the proposed framework answers the following questions: In Situ Repair Data Analytics for Situational Awareness that allows the end-users to connect and integrate with any data source in real-time so as to have the ability for online visualization of significant KPIs for the current status of the machine (inspection) and the repair process. Therefore, RECLAIM could answer when is the right time to refurbish/remanufacture industrial machinery, what is the appropriate strategy to follow, which benefits should the manufacturing company expect, and how this strategy will be implemented to deliver those benefits while providing for enhanced reliability and safety of the refurbished/remanufactured equipment. Through the proposed framework , RECLAIM ensures that the remanufacturing and refurbishing interventions make a positive contribution not only businesswise  but also toward the environment .RECLAIM is an ambitious project that will create and deploy an integrated DSF for machinery lifetime extension. The DSF for optimization refurbishment and remanufacturing process in itself is a significant step beyond the state of the art in the provisioning of infrastructure, tools, and services for experimentation in the digital manufacturing domain. The RECLAIM project will offer the following key novelty aspects: (a) a DSF for refurbishment and remanufacturing optimization by allowing automatic and concurrent multiobjective (particularly for three or more objectives) decision-making and assessing multiobjectives in the same turn, so it provides efficient and optimized decision support; (b) a Fault Diagnosis and Predictive Maintenance Simulation Engine using Digital Twin to keep the virtual twins that could store all available information during the lifetime of a machine, such as maintenance operations, and this information can be used to perform an economic estimation of the machine's refurbishment costs; (c) The next step after the implementation of RECLAIM is the validation of the proposed technology and the DSF through demonstrations. Those demonstrations will focus on large industrial equipment  from distinct industrial sectors: footwear manufacturers, white goods  manufacturers, wood manufacturing, friction welding machines, and textile manufacturers. Pilots will be supported by existing circular economy methods, which will be classified according to the preferable operation mode.


Dietary Guidelines are an important tool for population health promotion efforts. However, current surveillance data suggest that only a small minority of the population meet the 2014 Brazilian Dietary Guidelines (BDG) recommendations. Translating recommendations into practice may not be immediately clear and behavior-change messages guiding the behaviors that need to be changed and identifying substitute practices to meet a specific recommendation, are required. This study details the methods undertaken to develop and refine messages supporting the adoption of healthy dietary choices and behaviors in adults, as outlined in the BDG.A sequential, five-step, mixed-methods approach, determined a priori, was followed for designing and refining messages. These included: (1) content extraction; (2) audience analysis; (3) input from an expert review panel; (4) message development and message refinement; and a (5) test of content validity.The content extraction process led to the identification of 63 excerpts from the BDG, organized into themes. The audience analysis highlighted barriers to healthy eating that included lack of time , difficulty in accessing healthy food, the convenience and the ubiquitous marketing of ultra-processed foods. Twenty of the 63 DG excerpts reviewed by the expert panel were identified as being a priority for message development and total of 111 messages were developed. Messages were short, structured to be one-sided, conveyed the most important information at the beginning (anticlimactic), used simple language and were explicit in the information they relayed. They were positive and gain-framed and used an empathetic, solution- or substitution-based tone and were presented in the active voice. The messages focused on goals and skill development, behavior regulation, incentivized positive practices as time and/or cost saving. Content validity testing helped further messages and reduced the number of messages from 111 to 40.This study provides the blue-print for the phase-wise development of messages that synthesize the key recommendations of the food-based BDG and communicate the adoption of behaviors and goals that are consistent with it’s message. It details methods which could be adapted and replicated for message development in other contexts. Addresses the dearth of evidence on translating dietary guidelines into actionable and accessible behavior-change messages, furthering implementation science.Details the five-step, mixed-methods approach undertaken to craft and refine theory-based messages supporting the adoption of healthy dietary practices, as outlined in the 2014 Brazilian Dietary Guidelines.Includes results and examples of progressive message refinement and discusses how the methods could be contextually adapted.The final set of messages help distinguish between what to eat from how to incorporate that guidance and are more likely to make dietary change efforts successful.This manuscript:Food-based Dietary Guidelines are an important tool for population nutrition education and health promotion efforts . They deCurrent dietary patterns and nutrition behaviors suggest that only a small minority of the Brazilian population meet BDG recommendations. Instead of being completely avoided, ultra-processed food intake is high at 30% of total caloric consumption in Brazil and is associated with overweight and obesity in these populations . Eating The expert knowledge-consumer behavior gap suggests that DG need be made more accessible, and actionable to be potentially more effective. In addition to elaboration and publication, effective actions for translating the DG recommendations are crucial. While freely available online, and disseminated through social media sites of the Ministry of Health and the Unified Health System, it is unlikely that the DG are widely or frequently accessed by the general population who may find the 5-chapter, 158-page, technical report dense and long, or who may need additional support before they attempt to act on its recommendations. For most people, it may not be immediately clear what series of behaviors need to be changed and what the substitute practices are, to meet a specific recommendation. Indeed, research suggests that distinguishing between dietary guidance (what to eat) from nutrition promotion (how to incorporate that guidance) is more likely to be successful in promoting dietary change . TherefoWhile the importance of creating practical messages has been previously emphasized  and besta priori, was followed for designing and refining messages that support behaviors and choices consistent with the BDG recommendations  and data was collected between October 2017 and August 2018. This study was conducted on behalf of the Brazilian Ministry of Health. The methodological approach was informed by previous literature but also took into consideration time and financial constraints.Content extraction was fundamental for identifying excerpts from the BDG that would make appropriate material for the messages. The BDG content broadly encompasses guidelines/recommendations for a healthy diet along with quantitative and qualitative evidence to justify why these guidelines are important to follow. For this exercise, only recommendations from the BDG were extracted. Two researchers (NK and PdMS), working independently, read through all chapters of the BDG to identify, extract and record relevant sections, verbatim, into an Excel spreadsheet along with information on the chapter and the themes that the excerpt addressed. The two extraction sheets were compared to include any missing information, remove redundancies and to compile a final list of relevant content.food practices, beliefs about food, beliefs about processed food, attitudes towards food. The search was conducted by a study researcher (JRGN) and was geographically restricted to Brazil. A narrative review was conducted to summarize the findings.A formative literature review was undertaken to map beliefs, knowledge and perceptions of adult Brazilians living in urban and semi-urban settings, with regards to healthy eating. Awareness, current dietary patterns, perceived barriers and opportunities towards healthy eating were also assessed. The aim of this step was to better understand the target population of these messages and use this information to design the messages that informed them about healthy practices and provided justification for adopting these practices while countering misconceptions. The databases LILACS, FSTA, Ebsco, SCIELO and Pubmed were searched from their inception to October 2017 for quantitative and qualitative articles published in either English or Portuguese using the key words A panel of experts was invited for a three-hour discussion to help: (i) determine the completeness of the extracted BDG content, (ii) assess the hierarchy of importance of the content, (iii) provide feedback on results from the audience analysis, and (iv) share suggestions for organizing and presenting messages. The four-member panel was composed of researchers who were part of the scientific committee tasked with the development of the original BDG. The experts studied the socio-cultural dimensions of eating practices, and had previously developed various interventions and data collection instruments based on the BDG and therefore were extremely familiar with its content. Study objectives and results from the audience analysis were presented by the study team at the start of the session along with a list of the content extracted from the DG. Experts first recorded their opinions on the relative importance of the content and followed that up with a more detailed discussion to elaborate on their opinions, highlight new information to be included and illustrate ways to contextualize the messages that incorporated learnings from the audience analysis. The discussions were audio-recorded and JRGN served as the notetaker, capturing all suggestions made and decisions reached.Steps 1–3 set the foundation for the creation of a message library that broadly aimed at improving access and comprehension of the BDG and encouraging and facilitating behavior change. Messages were designed to improve awareness and knowledge about healthy dietary patterns, highlight practices and skills, and present solutions and opportunities to improve food choices.The development of the messages was guided by best practices related to message length, content, structure, style, tone, framing and wording , 21–24. A health communications specialist reviewed all messages to further refine their wording, integrate colloquial terminology without compromising on the precision of the information they communicated, and condensed message length or divided the information communicated into two or more messages to make them simpler to read.Messages were tested for their content validity through an online survey created using Qualtrics. This exercise was undertaken to help narrow down the list of messages and to capture feedback on message content and clarity. Messages were presented in the survey in four blocks, organized thematically. A total of 47 experts from across Brazil were invited to give their anonymous feedback on one of four randomly selected blocks. Each block comprised of approximately 10 messages - block one had nine messages, block two comprised of eight messages and blocks three and four had 11 messages each. Experts were chosen from among the contributors listed in the DG, and professors and researchers who had previously published on the DG or were known to use it extensively in their research.Input was solicited on the importance and clarity of each message . Response options were recorded on a 7-point Likert scale and ranged from very important (or very clear) to not at all important . Suggestions for revisions to the messages were also invited [‘Would you change this message in any way to make it clearer or more convincing? You could add or exclude information or choose to divide the message.’]. Multiple messages on the same theme, with near identical content but different wording were displayed together. Participants were requested to first choose the message (or messages) that they thought were most persuasive and then rate the importance and clarity of each of their choices. Providing feedback on the messages was voluntary and no reimbursement was given to incentivize participation in the 20-min long survey.Feedback was captured in an Excel spreadsheet and the mean values of message importance and clarity were calculated. Any suggested modifications to message wording were incorporated as appropriate. Since this was a qualitative exercise to help prioritize and shortlist messages, response to questions were compared and messages were selected based on their relative scores and after extensive discussion with members of the study team.General recommendations for food choice, Guidelines on how to combine food; The act of eating and commensality; and Obstacles in the adherence to recommendations. The excerpts included content from the NOVA classification, described the advantages of certain NOVA categories over others, and presented information on the frequency, types and combinations of foods to consume. The advantages of regularity of meal times, eating in company and in appropriate environments, the importance of developing culinary skills, strategies for addressing the lack of time and being wary of food marketing, were also captured.The content analysis process led to the identification of 63 excerpts from the DG, organized under the following themes: The results from the audience analysis highlighted barriers to healthy eating that included lack of time , difficulty in accessing healthy food, the convenience and the ubiquitous marketing of ultra-processed foods . IrregulTwenty of the 63 DG excerpts reviewed by the panel were identified as being a priority for message development, after considering the results of the audience analysis. These included introducing the NOVA categorization, focusing on variety in the diet that came from unprocessed food, emphasizing water as the beverage of choice and the importance of creating a healthy eating environment. The panel also suggested creating messages to highlight the role of the home food environment, and alternate forms of meal preparation that did not include frying and to make salient the pleasure of eating. In terms of message organization, the panel recommended presenting messages in the sequence of food-related decision-making to help increase their relevance to daily life and maximize their potential of being relatable and actionable. Besides introducing the NOVA classification and the types of food it contained as an overarching theme, messages were organized around the acts of meal planning, shopping, cooking, and eating. Beyond health gains, developing messages that emphasized environmental sustainability, gender-equality, and cost saving were also suggested based on lessons from the audience analysis.A total of 111 messages were developed – 20 messages introduced the NOVA categories with examples and suggestions on frequency of consumption, 17 messages targeted planning and organization of meals, 11 focused on shopping and food purchase, 34 messages presented information on cooking and division of labor and 29 conveyed information on the act of eating. In many instances, multiple messages were created, conveying the same information using marginally different wording  and about a fourth of the experts provided detailed feedback on a quarter of the messages. Based on an evaluation of relative scores, 6.5 was decided as the cut-off for shortlisting and messages that scored 6.5 or higher for importance and clarity were selected and further refined based on the detailed suggestions received. This process helped reduce the number of messages from 111 to 40. Table The research team extensively discussed suggested revisions and incorporated those that were judged to add more clarity and precision. Some suggestions called for dividing messages further. At the end of the content validation and after incorporating feedback from the experts a total of 40 messages were finalized and tested for face validity with the target population (Step 6 of the study). Nine of these messages had 3–4 variants that communicated nearly identical information. They were retained and tested in Step 6 of the study. Besides incorporating the structural elements described above, the final set of messages presented positive social norms and strategies to economize time, money and effort. The messages went beyond focusing on health benefits and instead highlighted practices that were environmentally sustainable and encouraged gender-equality in tasks. A sample of the messages in English (free translation from Portuguese) is presented in Table This study provides the blue-print for the phase-wise development of messages that synthesize the key recommendations of the food-based BDG and communicate the adoption of behaviors and goals that are consistent with it’s message. The creation of messages incorporated evidence-based practices and followed an extensive protocol to ensure appropriateness to the Brazilian context. The multi-step methodology included the use of audience analysis, an expert panel discussion and tested content validity via an online survey. It led to the creation of 111 messages of which 40 were short listed for future testing with the target audience.The methodology used in this study may easily be adapted to different contexts, while taking into consideration available resources. For instance, due to time and monetary constraints, a review of secondary literature was conducted to get an insight into dietary attitudes, practice and misconceptions among the primary audience of these messages. However, other studies have often used focus group discussions to assess similar constructs or employed a combination of ethnographic observations and in-depth interviews along with focus group discussions , 13, 16.This study incorporated features of the message design to maximize attention and appeal. Messages were therefore concise, direct, simple, gain-framed, positive and, where possible, indicative of a benefit. Besides including recommended elements of messages design, the messages also incorporated important constructs from the TDF – behavior regulation, beliefs about capabilities and consequences, social identity, while presenting skills or goals or sharing knowledge. The messages were also broadly targeted to the free-living, urban, adult Brazilian population and addressed several complex behaviors. Sub-groups of the population that may need special focus may still benefit from these messages but would likely need more customized and tailored communication. Past work has tended to focus on either on one aspect of message design or on a small set of behaviors or a more defined population group –39. ThesIn the current study, messages were developed to makes the DG more meaningful and easier to put into practice by making explicit the recommended consumer behavior. While no definite platform for dissemination of these messages was finalized, several options were considered that informed their tone, framing and length. These messages would therefore be suitable for presentation via a brochure, or disseminated through a cellphone application, social media or via text messages. They may also be adapted for health campaigns, incorporated into existing health promotion programs or used in conjunction with interventions –43. FutuThe present study builds on previous work to develop messages that were not just consistent with the BDG but also appropriate to the context in which they were to be used. It details methods which could be adapted and replicated for message development in other contexts. Integrating methods that allow for a deeper understanding of consumer concerns while providing dietary guidance that motivates them to act, is fundamental to the creation of behavior-change messages.


Background: Under normal physiological conditions, renal tissue oxygen is tightly regulated. At high altitude, a physiological challenge is imposed by the decrease in atmospheric oxygen. At the level of the kidney, the physiological adaptation to high altitude is poorly understood, which might relate to different integrated responses to hypoxia over different time domains of exposure. Thus, this systematic review sought to examine the renal physiological adaptation to high altitude in the context of the magnitude and duration of exposure to high altitude in the healthy kidney model.Methods: To conduct the review, three electronic databases were examined: OVID, PubMed, and Scopus. Search terms included: Altitude, renal, and kidney. The broad, but comprehensive search, retrieved 1,057 articles published between 1997 and April 2020. Fourteen studies were included in the review.Results: The inconsistent effect of high altitude on renal hemodynamic parameters , electrolyte balance, and renal tissue oxygen is difficult to interpret; however, the data suggest that the nature and extent of renal physiological adaptation at high altitude appears to be related to the magnitude and duration of the exposure.Conclusion: It is clear that renal physiological adaptation to high altitude is a complex process that is not yet fully understood. Further research is needed to better understand the renal physiological adaptation to hypoxia and how renal oxygen homeostasis and metabolism is defended during exposure to high altitude and affected as a long-term consequence of renal adaptation at high altitude. Tissue hypoxia can present either due to a decrease in oxygen delivery and/or as a result of an increase in oxygen consumption  in the context of renal oxygenation in the healthy animal and human model. The second objective was to identify the gaps in the literature and inform future research directions to enhance the overall understanding of the effect of renal tissue hypoxia on both the healthy and disease kidney model.A systematic review of the literature was conducted and included primary research articles that examined renal adaptation to acute and chronic high altitude-related conditions. To conduct the review, three electronic databases were examined: OVID, PubMed, and Scopus. Search terms included: Altitude, renal, and kidney. The broad, but comprehensive search retrieved 1,057 articles published between 1997 and April 2020 without language restriction. In addition to the above, one article was identified from the reference list of a selected article (via footnote chasing). The title and abstract of 541 articles (after duplicates were removed) were screened by two independent reviewers and excluded for analysis if they (1) were not a primary research article; (2) were a case report; (3) did not examine renal physiological response  to high altitude; (4) examined renal physiological response, but in an existing medical condition or pathophysiological condition ; (5) examined renal physiological response, but under intermittent exposure to high altitude ; (6) examined the genetic change underlying the renal physiological response; (7) examined the effect of exercise training on renal physiological response; (8) examined the effect of treatment on renal physiological response; or (9) full article not available . Any discrepancy between the two independent reviewers was resolved by discussion. In total, 32 articles were retrieved for full article review, of which 14 were included in the final review. The article selection process is shown in Fourteen articles were included in the review shown in . Renal tSix studies examined erythropoietin, hematocrit, hemoglobin, and/or blood viscosity  .Blood pressure  and regulating hormones were examined in six studies  , which could be a function of the extent (or magnitude) of altitude exposure. The relationship between blood pressure and regulating hormones is unclear; however, renin, aldosterone, vasopressin, and norepinephrine may play a role in the increase in mean arterial pressure at chronic exposure (90 d) to high altitude. At acute exposure to high altitude, the hormonal changes appeared to be more transient .Eight studies examined electrolyte balance , an indicator of renal oxygen delivery, decreased at high altitude  , but not at the highest altitude  . Instead, this could reflect a decrease in oxygen delivery as a result of decreased blood flow caused by increased blood viscosity. Arterial PaO2 alone is a poor measure of oxygen delivery, because it does not account for the change in renal blood flow and renal plasma flow. When renal blood flow was used to calculate renal oxygen delivery, renal oxygen delivery increased as a function of hematocrit. Unfortunately, no study examined renal oxygenation in the context of the tubular transport of sodium or the metabolic efficiency of the tubular transport of sodium, which could give great insight into the impact of high altitude on the efficiency of renal oxygen consumption.To summarize, renal oxygenation might decrease initially, but at a lower altitude is able to return to baseline. At a higher altitude, arterial PaOFive studies examined characteristics associated with acute mountain sickness   is a limitation in the field trials and is difficult to account for in the results. Second, most of the field trials did not control and/or measure dietary salt and fluid intake, which can make it difficult to compare results. The use of an altitude chamber, on the other hand, permitted the environment to be controlled. However, the use of a normobaric hypoxic chamber can make comparison to either a hypobaric hypoxic chamber or field trial more difficult. Third, the variation in the measurement of renal function can also make it difficult to compare results . Despite inulin clearance being an accurate measure of glomerular filtration rate, the administration of an exogenous marker may not be practicable on a mountain expedition at high altitude. Creatinine clearance is subject to exercise-induced release and is, again, difficult to account for in the results. Lastly, most of the studies that used a human model did not report baseline characteristics including race, body weight, smoking status, or whether participants used a carbonic anhydrase inhibitor to prevent acute mountain sickness.The systematic review examined the effect of high altitude on renal physiological function . An overview of the renal physiological response is found in In response to high altitude, there is a well-described hypoxic ventilatory response whereby tissue oxygenation is improved by increased pulmonary ventilation, leading to a respiratory alkalosis  excretion. This is referred to as the diuretic and natriuretic response and, again, appears to be triggered within hours of exposure to high altitude, followed by return to baseline with normal renal sodium and fluid excretion rate  delivery is an inverted U-shaped relationship, where at low hematocrit the O2 delivery is decreased because of the limited oxygen-carrying capacity of blood and at high altitude where oxygen delivery is decreased because of decreased blood flow as a result of increased blood viscosity. This relationship was observed in one study whereby a highly significant curvilinear (inverted U-shaped relationship) was found between urine partial pressure of oxygen (PO2) and blood erythropoietin, suggesting that renal tissue PO2 may drive the erythropoietin production , which may be a function of the extent of altitude exposure. However, no difference in systemic blood pressure was observed at chronic exposure to high altitude between rat strains with different polycythemic responses   decreased at all altitudes; however, it returned to baseline by 24 h at the lowest altitude , but not at the highest altitude  , but more specifically it is an estimate of medullary PO2 and is indicative of medullary hypoxia. The medulla is particularly vulnerable to hypoxia because of low medullary blood flow. The mechanism underlying the improvement in urine PO2 at 24 h at the lower altitude is not known; however, it may relate to the initial hypoxic ventilatory response.Concerning electrolyte balance and renal oxygen tension, the data are limited and the evidence that is available is difficult to discern. Nevertheless, renal oxygenation may decrease initially, but return to baseline at lower altitudes. This came from evidence in one study, that showed that at 6 h, urine partial pressure of oxygen  Articles written before 1997 were excluded. The review focused on more recent evidence that looked at the complex system interaction and not at the individual components. (2) The review did not examine AMS and only considered the combined group (AMS and non-AMS) when possible. The pathophysiology underlying the development of AMS is multi-factorial and not well understood; it was not an objective of the review. (3) The review included articles that used the high altitude model to examine renal adaptation to hypoxia, thereby excluding other models and should be understood within the larger body of the literature. (4) The main focus of the review was studies performed in healthy participants. An inherent assumption is that such studies are focused on healthy kidneys at high altitude. However, the literature suggests that kidney function at high altitude is poor, even in apparently healthy individuals  ; however, with time, the hemodynamic response appears to be more related to glomerular filtration rate. Renal plasma flow, renal blood flow, and filtration fraction, which are normally tightly regulated, are markedly changed at high altitude .Lastly, limited evidence is available to understand the relationship between the excretory function of the kidney and renal oxygen homeostasis at high altitude. The oxygen cost of sodium reabsorption in the distal nephron is high and relatively inefficient. However, it is unclear whether this is the case at exposure to high altitude. Further evidence related to intrarenal oxygen consumption, the efficiency of sodium transport, and basal metabolism in the kidney at high altitude is needed to fully delineate the issue.The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.LP and JO'N contributed the conception, design of the study, independently screened, and selected articles to be included. All authors contributed the data analysis, interpretation, participated in the revision of the manuscript, and have read and approved the submitted version. LP wrote the first draft of the manuscript, with the support of JO'N and K'OH.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Telehealth interventions offer an evidenced-based approach to providing cost-effective care, education, and timely communication at a distance. Yet, despite its widespread use, telehealth has not reached full potential, especially in rural areas, due to the complex process of designing and implementing telehealth programs. The objective of this paper is to explore the use of a theory-based approach, the Model for Developing Complex Interventions in Nursing, to design a pilot telehealth intervention program for a rural population with multiple chronic conditions.In order to develop a robust, evidenced based intervention that suits the needs of the community, stakeholders, and healthcare agencies involved, a design team comprised of state representatives, telehealth experts, and patient advocates was convened. Each design team meeting was guided by major model constructs . Overarching the process was a review of the literature to ensure that the developed intervention was congruent with evidence-based practice and underlying the entire process was scope of practice considerations.Ten design team meetings were held over a six-month period. An adaptive pilot intervention targeting home and community-based Medicaid Waiver Program participants in a rural environment with a primary objective of preventing re-institutionalizations was developed and accepted for implementation. To promote intervention effectiveness, asynchronous  and synchronous  telehealth approaches were selected to address the multiple comorbidities of the target population. An economic evaluation plan was developed and included in the pilot program to assess intervention cost efficiency.The Model for Developing Complex Interventions in Nursing provided a simple, structured process for designing a multifaceted telehealth intervention to minimize re-institutionalization of participants with multiple chronic conditions. This structured process may promote efficient development of other complex telehealth interventions in time and resource constrained settings. This paper provides detailed examples of how the model was operationalized. The federal government’s Money Follows the Person (MFP) initiative goals include increasing the use of home and community-based services and reducing the use of institutionally based services for people with chronic conditions and disabilities that have transitioned from institutions back into the community . TransitTelehealth interventions offer an evidenced based approach to providing patient education, timely communication, goal setting, and linking dispersed healthcare teams –9. Many The use of theory to structure the design has been suggested as an effective mechanism for ensuring the incorporation of multiple stakeholders’ views with the systemic/environmental context  , 14. IncThe Take Me Home (TMH), West Virginia Program is a federally funded Money Follows the Person (MFP) Rebalancing Demonstration program funded by the Centers for Medicare and Medicaid Services (CMS) . The MFPAs part of this collaboration, a design team comprised of telehealth experts from West Virginia University and state stakeholders affiliated with WVBMS was established. The design team included: a health policy, management, and leadership (HPML) faculty member; an HPML graduate student; a program manager with graduate training in HPML and business administration; two telehealth experts with a combined 30 years experience implementing telehealth in rural communities; and, state stakeholders purposely selected by the TMH Director based on subject matter expertise and familiarity with the target population. State stakeholders included: the TMH Director; the BMS medical director and two BMS nurses; the program manager for the state traumatic brain injury (TBI) waiver and manager of the organization providing care management services to TBI waiver participants; the director of the WV Home and Community-Based Services program; one Medicaid Waiver participant advocate; and, the chief operations officer and regional manager of homemaker services for Medicaid recipients. All decisions related to the telehealth design were made by consensus.The MDCN Fig.  3] is a is a3] iTen meetings over a six-month period were held with the constituted design team. Table What are the issues with your population? What is it that keeps your population out of the community? What possible telehealth interventions would be beneficial to your population? What are the policy issues? What are the reimbursement issues? In preparation for this meeting, design team members were asked to think about answers to the following questions:Family & Social Support Education Income Employment Health Behaviors Community Safety The design team identified the following as primary concerns: lack of support, isolation, transportation, remoteness, as well as complex inter-personal issues. These issues were further classified according to the Social Determinants of Health :Family These issues were being challenged through personnel limitations from program policies and provider reimbursement. West Virginia Medicaid only reimburses for real time telehealth communications . No reimbursement is currently made for store-and-forward or remote patient monitoring .The second meeting defined the target population in preparation to identify the overall intervention objectives. The design team selected the following target population: Medicaid Traumatic Brain Injury (TBIW) and Aged and Disabled (ADW) Waiver participants (ages 18 and older) who elect to participate in accessing the Waiver TMH Transition Program to support their transition from long-term care facilities to the community with rolling enrollment to begin in the spring of 2020. As guided by the model, the target population was selected based on the first step, problem identification. To come to this conclusion, the group considered and discussed the information and knowledge gathered through the practice, policy, and needs analysis in relation to the four groups of individuals that qualify for home services already being provided. Based on this knowledge, the group decided that two groups would benefit from telehealth services. Additionally, the group discussion highlighted that if the project was feasible, acceptable, and successful, scalability of the intervention to other populations could happen in the future.At the third design team meeting, the overall objectives for the proposed pilot intervention were established Table .Table 2At the start of the fourth design team meeting, the university-based team members presented the importance of selecting an academic model to follow. After considering multiple recommendations from the telehealth literature, the group selected the Chronic Care Model . ChoosinCommunity Resources and Policies, in this case, is the CMS Money Follows the Person initiative. The Health Systems of interest are the TBIW and ADW programs. Self-Management Support is about empowering and preparing participants to manage their health and healthcare. Interventions that support this approach include telehealth assessment, goal-setting, planning, problem-solving, and follow-up. Delivery System Design is transforming a system that is essentially reactive - responding mainly when a person is sick - to one that is proactive and focused on keeping a person as healthy as possible in the community . Decision Support in the model is about promoting clinical care that is consistent with scientific evidence and participant preferences. In this project, the proposed intervention is supported by evidence and is designed to promote patient acceptance. Clinical Information Systems organize participant data to measure efficient and effective care. Guided by this model, our designed telehealth interventions include providing timely reminders, identifying when proactive care is needed, individual participant care planning, and sharing clinical information with participants and their healthcare providers to coordinate care. The model depicts productive interactions between an informed participant of the community and the healthcare team that then leads to improved functional and clinical outcomes.Figure During the fifth and sixth design team meetings, telehealth medicine experts from the university presented and discussed six main types of telehealth interventions . Based uThirteen telehealth vendors that met quality assurance standards including providing safe and effective services direct to patients and meeting the highest standards of care were investigated and considered as potential collaborators for the project. Each vendor was evaluated based on types of services provided, ease of use, years of providing telehealth, cost of services, and interoperability. The top four vendors gave product and service demonstrations to the design team, after which the design team selected two appropriate vendors.The final two design team meetings involved finalizing the intervention specifics and assessing the feasibility with end users. Vendor contracting and intervention implementation will take 8 weeks and is subject to revisions as needed. While currently residing in a long-term care facility, after being identified as meeting eligibility for either TBIW or ADW services, participants 18 years of age or older who agree to in-home monitoring using technology will be enrolled in the pilot telehealth intervention. Consent to participate in the monitoring as well as evaluation of the intervention will be obtained by the transition coordinator. Once consent has been obtained, assessment of the individual as well as planning for the appropriate telehealth intervention will be performed by the TMH Transition Coordinator using the results of the required assessments with assistance from the project nurse and telehealth vendor clinical staff. The project manager will enter the appropriate variables of measurement into the evaluation database and notify the vendor of the enrolling participant needs. The vendor will deliver the appropriate equipment to the participant’s home and provide instructions for use. Participant information from the remote devices will be sent to the Registered Nurse or Case Manager of the waiver program or primary care provider as necessary per protocol for appropriate coordination and planning of care. Care will continue in this manner for 6 months at which time the vendor will collect the equipment and distribute the evaluation data to the project manager. The project manager will also contact the participant and providers to collect information on satisfaction with the telehealth services.As telehealth interventions are identified, data on the costs associated with their implementation will be collected by the project manager. Team members will help devise cost data collection protocols to capture outlays, which are expected to include the vendor contract that includes all remote monitoring devices, broadband coverage, and personnel time. These numbers will be incorporated into a summary of start-up (implementation) costs of the interventions. We will also conduct an outcomes analysis, examining changes in rates of emergency department visits, urgent care center visits, and hospitalizations. These outcomes – and their associated costs – will be captured using Medicaid claims data. We will further design a sustainability model that will calculate a capitated per member per month estimate, and will estimate required reimbursement rates for the intervention program to be viable in the long run. Cost-effectiveness will be evaluated in terms of both dollar units and natural units.The design team held an expert review with academic experts, medical directors, program directors, managers of patient support services, nurses, telehealth experts, vendors, service providers, participant advocates, potential participants, and students. After a summary of the work accomplished at the 9 meetings with the design team guided by the Model for Developing Complex Interventions in Nursing followed by a “day in the life” case study presentation of the proposed pilot telehealth demonstration, the group was asked whether or not there were any “hard stops”. More specifically, the group was asked whether or not any aspect of the proposed telehealth demonstration project would be unfeasible or logistically untenable in their respective populations. After clarifying the rationale behind the use of a historic control group for the assessment of cost-effectiveness, the use of a landline and/or Wi-Fi, and the potential integration of rehabilitation services in the future, it was determined that there were no aspects of the proposal that were deemed to be unfeasible and in need of redesign. Additional suggestions and comments related to the work were solicited.To our knowledge, this article is the first to translate the MDCN into a step-wise iterative process. We have described progressing through the process by means of 10 meetings with a group of stakeholders to design a telehealth intervention for a specific population. The use of the MDCN was essential to the successful development of a robust, adaptive, and empirically grounded telehealth intervention. Telehealth interventions have been developed and used in other states to improve care access and outcomes . A strucThere are limitations to this type of approach. Assembling the right stakeholders requires connecting dispersed individuals with academic and pragmatic knowledge. Additionally, the ability to engage in open collegial, and multi-directional dialogue is required. Time can be an issue in working through the process in multiple ways. Scheduling meetings requires gathering multiple busy individuals and in addition to the time required in meetings, independent work and reflection is required between meetings. Lastly, the academic research process of designing large randomized controlled trials may not be possible within the given workflows and cost constraints of established practices. Control groups, population focus, and length of intervention may be based on cost of implementation instead of the gap in the current science.A process driven approach facilitated the development of a pilot telehealth demonstration intervention. This demonstration, funded by West Virginia’s Money Follows the Person Program, will provide critical information to promote scalability of telehealth services to other home and community-based services within West Virginia.