Expert System for Nutrition Care Process of Older Adults

This paper presents an expert system for a nutrition care process tailored for the specific needs of elders. Dietary knowledge is defined by nutritionists and encoded as Nutrition Care Process Ontology, and then used as underlining base and standardized model for the nutrition care planning. An inference engine is developed on top of the ontology, providing semantic reasoning infrastructure and mechanisms for evaluating the rules defined for assessing short and long term elders’ self-feeding behaviours, to identify unhealthy dietary patterns and detect the early instauration of malnutrition. Our expert system provides personalized intervention plans covering nutrition education, diet prescription and food ordering adapted to the older adult’s specific nutritional needs, health conditions and food preferences. In-lab evaluation results are presented proving the usefulness and quality of the expert system as well as the computational efficiency, coupling and cohesion of the defined ontology

A Menu Planning Model Using Hybrid Genetic Algorithm And Fuzzy Reasoning: A Study On Malaysian Geriatric Cancer Patients

Dewasa ini, terdapat banyak model perancangan menu yang menyediakan nasihat umum kepada pelanggan di pasaran. Namun, penyelesaian yang dijana daripada model ini biasanya sangat subjektif dan sukar untuk diwakili secara sistematik. Oleh itu, pemakanan yang betul bagi warga tua adalah penting untuk mengekalkan kesihatan dan kesejahteraan. Kajian ini menghasilkan model perancangan menu berasaskan ontologi menggunakan algoritma genetik hibrid dan penaakulan kabur terhadap pesakit kanser geriatrik di Malaysia. Kajian ini adalah bertujuan untuk mengemukakan perwakilan pelan diet berdasarkan ontologi pelan diet; mereka bentuk enjin perancangan dengan mengintegrasikan algoritma genetik dengan pencarian setempat untuk memperbaiki pelan menu; membangunkan pelan menu untuk pesakit tersebut dengan menggunakan mekanisme penaakulan kabur. Dengan tujuan untuk merancang menu yang sihat kepada pesakit, ontologi digunakan untuk mengklasifikasikan nutrien, jenis makanan, struktur pemakanan dan profil peribadi. Selain itu, algoritma genetik hibrid (HGA) digunakan untuk memastikan bahawa perancangan menu dapat memenuhi semua objektif dan kekangan yang telah ditetapkan. Tambahan pula, kawalan logik kabur (FLC) diaplikasikan dalam pemodelan fungsi keahlian set kabur bagi menganggarkan keperluan pemakanan. Nowadays, there are many diet recommendation models in the market that provide general advice to the clients. However, the generated menu plan from these models are usually very subjective and difficult to be represented systematically. Thus, proper nutrition for the elderly is important to maintain health and well-being, which can lead to fulfilling and independent lives. This research presents a study on ontology-based menu planning model using hybrid genetic algorithm and fuzzy reasoning for Malaysian geriatric cancer patients. The proposed work aims to produce a diet plan representation based on diet plan ontology; design a planning engine by integrating genetic algorithm with local search technique to enhance menu planning; and develop a menu planning approach to cater for Malaysian geriatric cancer patients using fuzzy reasoning mechanism. With the aim of planning healthy menu to patients, ontology is used to classify nutrients, food groups, meal structure and personal profile. Following that, hybrid genetic algorithm (HGA) is employed to ensure that the constructed menu satisfies all the objectives and predefined constraints. Furthermore, a fuzzy logic control (FLC) was applied in the modeling of membership functions of fuzzy sets for estimating nutrition needs

An IoT architecture for decision support system in precision livestock

Sustainable animal production is a primary goal of technological development in the livestock industry. However, it is crucial to master the livestock environment due to the susceptibility of animals to variables such as temperature and humidity, which can cause illness, production losses, and discomfort. Thus, livestock production systems require monitoring, reasoning, and mitigating unwanted conditions with automated actions. The principal contribution of this study is the introduction of a self-adaptive architecture named e-Livestock to handle animal production decisions. Two case studies were conducted involving a system derived from the e-Livestock architecture, encompassing a Compost Barn production system - an environment and technology where bovine milk production occurs. The outcomes demonstrate the effectiveness of e-Livestock in three key aspects: (i) abstraction of disruptive technologies based on the Internet of Things (IoT) and Artificial Intelligence and their incorporation into a single architecture specific to the livestock domain, (ii) support for the reuse and derivation of an adaptive self-architecture to support the engineering of a decision support system for the livestock subdomain, and (iii) support for empirical studies in a real smart farm to facilitate future technology transfer to the industry. Therefore, our research’s main contribution is developing an architecture combining machine learning techniques and ontology to support more complex decisions when considering a large volume of data generated on farms. The results revealed that the e-Livestock architecture could support monitoring, reasoning, forecasting, and automated actions in a milk production/Compost Barn environment.Na indústria pecuária, a produção animal sustentável é o principal objetivo do desenvolvimento tecnológico. Porém, é fundamental manter boas condições no ambiente devido à suscetibilidade dos animais a variáveis como temperatura e umidade, que podem causar doenças, perdas de produção e desconforto. Assim, os sistemas de produção pecuária requerem monitoramento, controle e mitigação das condições indesejadas através de ações automatizadas. A principal contribuição deste estudo é a introdução de uma arquitetura auto-adaptativa denominada e-Livestock para apoiar as decisões relacionadas à produção animal. Foram conduzidos dois estudos de caso, envolvendo a arquitetura e-Livestock, que foi utilizada no sistema de produção Compost Barn - ambiente e tecnologia onde ocorre a produção de gado leiteiro. Os resultados demonstraram a utilidade do e-Livestock para avaliar três aspectos principais: (i) abstração de tecnologias disruptivas baseadas em Internet das Coisas (IoT) e Inteligência Artificial, e sua incorporação em uma arquitetura única, específica para o domínio da pecuária, (ii) suporte para a reutilização e derivação de uma arquitetura auto-adaptativa para apoiar o desenvolvimento de uma aplicação de apoio à decisão para o subdomínio da pecuária e (iii) suporte para estudos empíricos em uma fazenda inteligente real para facilitar a transferência de tecnologia para a indústria. Portanto, a principal contribuição dessa pesquisa é o desenvolvimento de uma arquitetura combinando técnicas de machine learning e ontologia para apoiar decisões mais complexas ao considerar um grande volume de dados gerados nas fazendas. Os resultados revelaram que a arquitetura e-Livestock pode apoiar monitoramento, controle, previsão e ações automatizadas em um ambiente de produção de leite/Compost Barn.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superio

Формирование персонализированного рациона питания с использованием структурной оптимизации

The design of a human personalized diet considering a variety of different factors is associated with system analysis and formalization of data and knowledge, as well as with the development of digital technologies. The paper presents the methodology of optimization and formation of personalized diets based on structural-parametric modeling. The proposed approach allows solving the following tasks: 1)  to analyze the daily diet or individual meals (breakfast, lunch, afternoon snack, dinner, additional meals or snacks) with a known quantitative set of finished products in terms of energy value and chemical composition in order to reveal dietary disorders; 2)  to calculate quantity of products optimal for a meal from the fixed list, thereby composing an individual reference diet with regard to the mental and physical activities, nutritive status of a consumer and economic aspects; 3) to optimize a diet depending on the task at hand by selecting a group of finished products from a complete or selected list of archival data, equally taking into account all the necessary parameters; 4) to adjust the diet taking into account dietary deviations in certain parameters of the chemical composition and energy value by additional introduction of special purpose products with the increased biological value, multivitamin and multivitamin-mineral supplements, as well as natural bioactive substances.Конструирование персонализированного рациона питания человека с учетом многообразия различных факторов связано с системным анализом и формализацией накопленных данных и знаний, а также с развитием цифровых технологий. В работе представлена методология оптимизации и формирования персонализированных рационов питания на основе структурно-параметрического моделирования. Предлагаемый подход позволяет решать следующие задачи: 1) анализировать суточный рацион или отдельные приемы пищи (завтрак, обед, полдник, ужин, дополнительные приемы пищи (перекус)) с известным количественным набором готовых продуктов по энергетической ценности и химическому составу с целью выявления диетических нарушений; 2) рассчитывать оптимальное для приема пищи количество продуктов из фиксированного перечня, тем самым составляя индивидуальный эталонный рацион с учетом умственной и физической нагрузки, нутритивного статуса потребителя, а также экономических аспектов; 3) оптимизировать рацион в зависимости от поставленной задачи путем подбора группы готовых продуктов из полного или избранного перечня архивных данных, равнозначно учитывая при этом все необходимые параметры; 4) корректировать рацион питания с учетом диетических отклонений по отдельным параметрам химического состава и энергетической ценности за счет дополнительного введения продуктов повышенной биологической ценности специального назначения, поливитаминных и поливитаминно-минеральных препаратов, а также природных биологически активных веществ

Cognitive assisted living ambient system: a survey

The demographic change towards an aging population is creating a significant impact and introducing drastic challenges to our society. We therefore need to find ways to assist older people to stay independently and prevent social isolation of these population. Information and Communication Technologies (ICT) provide various solutions to help older adults to improve their quality of life, stay healthier, and live independently for a time. Ambient Assisted Living (AAL) is a field to investigate innovative technologies to provide assistance as well as healthcare and rehabilitation to impaired seniors. The paper provides a review of research background and technologies of AAL

Automatic Generation of Personalized Recommendations in eCoaching

Denne avhandlingen omhandler eCoaching for personlig livsstilsstøtte i sanntid ved bruk av informasjons- og kommunikasjonsteknologi. Utfordringen er å designe, utvikle og teknisk evaluere en prototyp av en intelligent eCoach som automatisk genererer personlige og evidensbaserte anbefalinger til en bedre livsstil. Den utviklede løsningen er fokusert på forbedring av fysisk aktivitet. Prototypen bruker bærbare medisinske aktivitetssensorer. De innsamlede data blir semantisk representert og kunstig intelligente algoritmer genererer automatisk meningsfulle, personlige og kontekstbaserte anbefalinger for mindre stillesittende tid. Oppgaven bruker den veletablerte designvitenskapelige forskningsmetodikken for å utvikle teoretiske grunnlag og praktiske implementeringer. Samlet sett fokuserer denne forskningen på teknologisk verifisering snarere enn klinisk evaluering.publishedVersio

An ontology to integrate multiple knowledge domains of training-dietary-competition in weightlifting: A nutritional approach

This study is a part of weightlifting “TrainingDietary-Competition” (TDC) cycle ontology. The main objective of TDC-cycle is to build a knowledge framework for Olympic weightlifting, bringing together related fields such as training methodology, weightlifting biomechanics, and nutrition while modelling the synergy among them. In so doing, terminology, semantics, and used concepts are unified among athletes, coaches, nutritionists, and researchers to partially obviate the problem of unclear results and paucity of information. The uniqueness of this ontology is its ability to solve the knowledge sharing problem in which the knowledge owned by these experts in each field are not captures, classified or integrated into an information system for decision-making. The whole weightlifting TDC-cycle is semantically modelled by conceiving, designing, and integrating domain and task ontologies with the latter devising reasoning capability toward an automated and tailored weightlifting TDC-cycle. However, this study will focus mainly on the nutrition domain. The intended application of this part of ontology is to provide a useful decision-making platform for a sport nutritionist who gathers and integrate relevant scientific information, equation, and tools necessary when providing nutritional services. The system is constructed by using Web Ontology Language (OWL), Semantic Web Rule Language (SWRL), and Semantic Query-Enhanced Web Rule Language (SQWRL). The use of weightlifting TDC-cycle ontology can be helpful for nutritionists to create a well-planned nutrition program for athletes (especially, in the process of nutrition monitoring to identify energy imbalance in athletes) by reducing time consumption and calculation errors.The authors would like to thank Prof.Adriano Tavares for his guidance and providing necessary in formation regarding the project

Human Coaching Methodologies for Automatic Electronic Coaching (eCoaching) as Behavioral Interventions with Information and Communication Technology: Systematic Review

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AI and robotics to help older adults: Revisiting projects in search of lessons learned

Abstract This article is a retrospective overview of work performed in the domain of Active Assisted Living over a span of almost 18 years. The authors have been creating and refining artificial intelligence (AI) and robotics solutions to support older adults in maintaining their independence and improving their quality of life. The goal of this article is to identify strong features and general lessons learned from those experiences and conceive guidelines and new research directions for future deployment, also relying on an analysis of similar research efforts. The work considers key points that have contributed to increase the success of the innovative solutions grounding them on known technology acceptance models. The analysis is presented with a threefold perspective: A Technological vision illustrates the characteristics of the support systems to operate in a real environment with continuity, robustness, and safety; a Socio-Health perspective highlights the role of experts in the socio-assistance domain to provide contextualized and personalized help based on actual people's needs; finally, a Human dimension takes into account the personal aspects that influence the interaction with technology in the long term experience. The article promotes the crucial role of AI and robotics in ensuring intelligent and situated assistive behaviours. Finally, considering that the produced solutions are socio-technical systems, the article suggests a transdisciplinary approach in which different relevant disciplines merge together to have a complete, coordinated, and more informed vision of the problem

Becoming Eco-Logical With Second-Order Systems Theory: Sustainability In Re-Organization Of Economies And Food Systems

Ecological Economics has emerged across disciplines, and has begun to disentangle, not only the relationship between biophysical earth systems and economic activity, but also, fundamental relationships between objectivity, power, value, ethics, perspective and purpose. In part, this thesis represents an effort to illustrate basic transdisciplinary concepts necessary for understanding the project of Ecological Economics. At present, Ecological Economics is challenged by a seemingly infinite number of available considerations, with a relatively narrow repertoire of impactful mechanisms of control. Given this, it is apparent that the application of Cybernetics to Ecological Economics might provide insights. Cybernetics can help to lend concise language to manners for implementing control and also help to navigate the paradoxes which arise for self- regulating systems. While Cybernetics played an early role in the formulation of the relationship between the economy and an environment with available energy, second- order cybernetics can help to formulate the autonomy of Ecological Economics as a self-regulating system and shed light on the epistemology and ethics of circularity. The first article of this thesis identifies occasions when Ecological Economics has confronted circularity, and explores options moving forward. Ultimately, confronting paradox and circularity provide the means for the substantiation of Ecological Economics. The food system is prominent within Ecological Economics discourse. It serves as a good example of the ‘emergence’ of coordinated activity. In Cybernetics jargon, we can think of the ‘Food System’ as a symbol for the redundancy found in linked characteristics of particular Ecological-Economic inquiry. For instance, when we consider the food system we can be sure that we are dealing with resources that are essential, both rival and non-rival, excludable and non-excludable, and also highly sensitive to boundaries in scope, and scale, and thus highly sensitive to political and social change. In this sense, the food system acts as a symbol for the coordination of activity, and produces an output which is an input to the Ecological Economic ‘boundary’ between the Economy and the Ecosystem. The second article of this thesis provides an analysis of GHG emissions within the Chittenden County Foodshed. We conclude that urban agriculture, dietary change and agro-ecological production in concert, provide emission reductions which are not achieved when these options are considered separately. Given these conditions, we see mitigation beyond 90% of current emissions