Modeling of a context-aware system to support interventions in physical activities and healthy nutrition

Los sistemas de salud en todo el mundo afrontan el desafío de combatir el gran incremento de  enfermedades crónicas no transmisibles (ECNT), especialmente enfermedades cardiovasculares. Estas enfermedades pueden ser prevenidas si se logra la adopción de hábitos y estilos de vida saludables por parte de las personas, fundamentalmente el incremento de la actividad física y la nutrición sana. El objetivo de este artículo es describir el proceso de modelado de un sistema consciente del contexto, con el fin de soportar intervenciones que promuevan la actividad física y dieta saludable y se adapten a las características del contexto del usuario. Los principales resultados de este trabajo son a) un modelo de clasificación del contexto en salud y un modelo del proceso de  adaptabilidad y personalización del contexto, b) una propuesta de un modelo de contexto para un sistema consciente en el contexto que apoye la promoción de actividad física y nutrición saludable, c) una arquitectura de referencia y un prototipo del sistema desarrollado sobre esta arquitectura, el cual consiste en una aplicación móvil soportada en tecnologías NFC y GPS y d) la evaluación de la usabilidad de la solución.Health systems around the world are currently facing a challenge to fight the tremendous growth of non-transmissible chronic diseases (NTCD), especially cardiovascular diseases. These diseases can be prevented if adoption of healthy habits and lifestyles are adopted by people, specifically by increasing their physical activity and having a healthy nutrition. The objective of this article is to describe the modeling process of a contextaware system with the purpose of supporting interventions to promote physical activity and healthy nutrition, duly adjusted to the characteristics of the user’s context. The main results of this article are: a) a classification model of health context and a context adaptability and personalization process model; b) a proposal of a context model for a context-aware system, which supports the promotion of physical activity and healthy nutrition; c) a reference architecture and a prototype of the system developed on such architecture, which consists of a mobile application supported by NFC and GPS technologies; and d) an evaluation of the solution usability

Toward a Deep Neural Approach for Knowledge-Based IR

International audienceThis paper tackles the problem of the semantic gap between a document and a query within an ad-hoc information retrieval task. In this context, knowledge bases (KBs) have already been acknowledged as valuable means since they allow the representation of explicit relations between entities. However, they do not necessarily represent implicit relations that could be hidden in a corpora. This latter issue is tackled by recent works dealing with deep representation learning of texts. With this in mind, we argue that embedding KBs within deep neural architectures supporting document-query matching would give rise to fine-grained latent representations of both words and their semantic relations. In this paper, we review the main approaches of neural-based document ranking as well as those approaches for latent representation of entities and relations via KBs. We then propose some avenues to incorporate KBs in deep neural approaches for document ranking. More particularly, this paper advocates that KBs can be used either to support enhanced latent representations of queries and documents based on both distributional and relational semantics or to serve as a semantic translator between their latent distributional representations

A Real-Time intelligent system for tracking patient condition

Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance

Designing for practice-based context-awareness in ubiquitous e-health environments

Existing approaches for supporting context-aware knowledge sharing in ubiquitous healthcare give little attention to practice-based structures of knowledge representation. They guide knowledge re-use at an abstract level and hardly incorporate details of actionable tasks and processes necessary for accomplishing work in a real-world context. This paper presents a context-aware model for supporting clinical knowledge sharing across organizational and geographical boundaries in ubiquitous e-health. The model draws on activity and situation awareness theories as well as the Belief-Desire Intention and Case-based Reasoning techniques in intelligent systems with the goal of enabling clinicians in disparate locations to gain a common representation of relevant situational information in each other's work contexts based on the notion of practice. We discuss the conceptual design of the model, present a formal approach for representing practice as context in a ubiquitous healthcare environment, and describe an application scenario and a prototype system to evaluate the proposed approach

Hospital-home health care logistics management in Valle del Cauca :Characterization and diagnosis

RESUMEN: Este artículo presenta el primer diagnóstico de la gestión logística de las instituciones habilitadas por el Ministerio de Salud y Protección Social para la prestación de servicios de hospitalización domiciliaria(HHC) en el Valle del Cauca, Colombia. El objetivo es caracterizar cómo los proveedores de HHC toman las decisiones logísticas asociadas con el proceso de prestación del servicio, e identificar oportunidades de mejoramiento e investigación. El diagnóstico se construyó mediante la aplicación de una encuesta semiestructurada que evaluó 6 ejes de trabajo y el grado de madurez de los procesos de servicio. Los resultados muestran que se requiere una gestión más integral de las decisiones logísticas, apoyada en el conocimiento del perfil epidemiológico y demográfico de la población atendida.ABSTRACT: This paper presents the first logistics management diagnosis for the health care institutions certifiedby the Ministry of Health to provide Home Health Care (HHC) services in the state of Valle del Cauca,Colombia. The objective is to characterize how HHC providers make logistics decisions associated withthe service delivery process, and to identify improvement and research opportunities in the field. Thediagnosis was conducted through the application of a semi-structured questionnaire that evaluated sixwork axes and the maturity level of service processes. The results show the need for a more integrallogistics management supported by the knowledge of the epidemiological and demographic profile ofthe population in the state

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

A multivariant secure framework for smart mobile health application

This is an accepted manuscript of an article published by Wiley in Transactions on Emerging Telecommunications Technologies, available online: https://doi.org/10.1002/ett.3684 The accepted version of the publication may differ from the final published version.Wireless sensor network enables remote connectivity of technological devices such as smart mobile with the internet. Due to its low cost as well as easy availability of data sharing and accessing devices, the Internet of Things (IoT) has grown exponentially during the past few years. The availability of these devices plays a remarkable role in the new era of mHealth. In mHealth, the sensors generate enormous amounts of data and the context-aware computing has proven to collect and manage the data. The context aware computing is a new domain to be aware of context of involved devices. The context-aware computing is playing a very significant part in the development of smart mobile health applications to monitor the health of patients more efficiently. Security is one of the key challenges in IoT-based mHealth application development. The wireless nature of IoT devices motivates attackers to attack on application; these vulnerable attacks can be denial of service attack, sinkhole attack, and select forwarding attack. These attacks lead intruders to disrupt the application's functionality, data packet drops to malicious end and changes the route of data and forwards the data packet to other location. There is a need to timely detect and prevent these threats in mobile health applications. Existing work includes many security frameworks to secure the mobile health applications but all have some drawbacks. This paper presents existing frameworks, the impact of threats on applications, on information, and different security levels. From this line of research, we propose a security framework with two algorithms, ie, (i) patient priority autonomous call and (ii) location distance based switch, for mobile health applications and make a comparative analysis of the proposed framework with the existing ones.Published onlin