Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie

Strategies for online personalised nutrition advice employed in the development of the eNutri web app

The internet has considerable potential to improve health-related food choice at low-cost. Online solutions in this field can be deployed quickly and at very low cost, especially if they are not dependent on bespoke devices or offline processes such as the provision and analysis of biological samples. One key challenge is the automated delivery of personalised dietary advice in a replicable, scalable and inexpensive way, using valid nutrition assessment methods and effective recommendations. We have developed a web-based personalised nutrition system (eNutri) which assesses dietary intake using a validated graphical FFQ and provides personalised food-based dietary advice automatically. Its effectiveness was evaluated during an online randomised controlled trial dietary intervention (EatWellUK study) in which personalised dietary advice was compared with general population recommendations (control) delivered online. The present paper presents a review of literature relevant to this work, and describes the strategies used during the development of the eNutri app. Its design and source code have been made publicly available under a permissive open source license, so that other researchers and organisations can benefit from this work. In a context where personalised diet advice has great potential for health promotion and disease prevention at-scale and yet is not currently being offered in the most popular mobile apps, the strategies and approaches described in the present paper can help to inform and advance the design and development of technologies for personalised nutrition

Mobile nutrition assessment and decision support system for village health teams in Uganda.

The government of Uganda through the Ministry of Health and other stakeholders are in efforts of strengthening information systems for nutrition, through data collection, management and dissemination. In these effortshealth centers at the regional level were used to carry-out nutrition assessments and training to village health teams(VHTs) to extend the service to the families. The Ministry of health and other implementing partners are encouraging community based service delivery and this is being done by involving the VHTs in all services provided to the community. The VHTs work as the vocal people for the families in the communities hence are able to idenify the needs of the communities. The main objective of this study is to design and develop a mobile nutrition assessment and decision support systems for VHTs in Uganda to support them in nutrition assessment and giving families feeding recommendations.The study will use the available nutrition assessment data to design and develop a decision support system that supports proper feeding, manage follow-ups and referrals to avoid relapses among children who are enrolled in the nutrition clinic.In this thesis a Design Science Research Methodology (DSRM) was used to help us direction in coming up with an artefact.In addition, the user centered design approach was followed, to allow involvement of users throughout the design of the prototype.The project worked closely with the staff at the health center. Interviews and focus group discussions were applied to get qualitative feedback.Furthermore, a prototype was demonstrated and the questionnaires distributed to get feedback on the designed prototype.A low and high fidelity prototype for nutrition assessment and decision support has been developed to be used by VHTs and health facilities to manage nutrition and make real time decisions

Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

Chronic diseases are becoming more widespread. Treatment and monitoring of these diseases require going to hospitals frequently, which increases the burdens of hospitals and patients. Presently, advancements in wearable sensors and communication protocol contribute to enriching the healthcare system in a way that will reshape healthcare services shortly. Remote patient monitoring (RPM) is the foremost of these advancements. RPM systems are based on the collection of patient vital signs extracted using invasive and noninvasive techniques, then sending them in real-time to physicians. These data may help physicians in taking the right decision at the right time. The main objective of this paper is to outline research directions on remote patient monitoring, explain the role of AI in building RPM systems, make an overview of the state of the art of RPM, its advantages, its challenges, and its probable future directions. For studying the literature, five databases have been chosen (i.e., science direct, IEEE-Explore, Springer, PubMed, and science.gov). We followed the (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) PRISMA, which is a standard methodology for systematic reviews and meta-analyses. A total of 56 articles are reviewed based on the combination of a set of selected search terms including RPM, data mining, clinical decision support system, electronic health record, cloud computing, internet of things, and wireless body area network. The result of this study approved the effectiveness of RPM in improving healthcare delivery, increase diagnosis speed, and reduce costs. To this end, we also present the chronic disease monitoring system as a case study to provide enhanced solutions for RPMsThis research work was partially supported by the Sejong University Research Faculty Program (20212023)S

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

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic