VITASENIOR-MT: a telehealth solution for the elderly focused on the interaction with TV

Remote monitoring of health parameters is a promising approach to improve the health condition and quality of life of particular groups of the population, which can also alleviate the current expenditure and demands of healthcare systems. The elderly, usually affected by chronic comorbidities, are a specific group of the population that can strongly benefit from telehealth technologies, allowing them to reach a more independent life, by living longer in their own homes. Usability of telehealth technologies and their acceptance by end-users are essential requirements for the success of telehealth implementation. Older people are resistant to new technologies or have difficulty in using them due to vision, hearing, sensory and cognition impairments. In this paper, we describe the implementation of an IoT-based telehealth solution designed specifically to address the elderly needs. The end-user interacts with a TV-set to record biometric parameters, and to receive warning and recommendations related to health and environmental sensor recordings. The familiarization of older people with the TV is expected to provide a more user-friendly interaction ensuring the effectiveness integration of the end-user in the overall telehealth solution.This work has been financially supported by the IC&DT project VITASENIOR-MT CENTRO-01-0145-FEDER- 023659 with FEDER funding through programs CENTRO2020 and FCT.info:eu-repo/semantics/publishedVersio

Estrategias dirigidas a las atenciones de salud domiciliaria

OBJECTIVE: The aim was to present the different strategies that are aimed at public health at home and to identify the perspectives of other authors about it. METHODOLOGY: quantitative approach, descriptive design and a systematic review, for which the current regulations will be reviewed and the pros and main problems in the health sector will be analyzed, to establish significant solutions to help improve the health sector in the Ancash region, hand in hand with user satisfaction. RESULTS: Being a systematic research, it is based on a literature review and empirical analysis of the main problems in the health sector. CONCLUSION: In addition, it provides an alternative solution through home visits, an important component in health promotion, which precisely seeks to know the possible ailments of the population in their initial stages and establish policies so that these are attended and generate an effective solution in the welfare of patients and vulnerable population.OBJETIVO: Como fin tuvo presentar las diferentes estrategias que están dirigidas a la salud pública a domicilio e identificar las perspectivas de otros autores acerca de ello. METODOLOGÍA: enfoque cuantitativo, diseño descriptivo y una revisión sistemática, para el cual se revisará la normativa vigente y se analizarán los pros y principales problemas en el sector salud, para establecer soluciones significativas que ayuden a la mejora del ámbito salud en la región Ancash, de la mano con la satisfacción del usuario. RESULTADOS: Al ser una investigación sistemática está basada en revisión bibliográfica y análisis empírico sobre las principales problemáticas del sector salud. CONCLUSIÓN: Además, brinda una alternativa de solución a través de las visitas domiciliarias, componente importante en la promoción de la salud, la cual buscan justamente conocer los posibles males de la población en sus etapas iniciales y establecer políticas para que estos sean atendidos y generar una solución eficaz en el bienestar de los pacientes y población vulnerable. &nbsp

Innovative Business Model for Smart Healthcare Insurance

Information revolution and technology growth have made a considerable contribution to restraining the cost expansion and empowering the customer. They disrupted most business models in different industries. The customer-centric business model has pervaded the different sectors. Smart healthcare has made an enormous shift in patient life and raised their expectations of healthcare services quality. Healthcare insurance is an essential business in the healthcare sector; patients expect a new business model to meet their needs and enhance their wellness. This research develops a holistic smart healthcare architecture based on the recent development of information and communications technology. Then develops a disruptive healthcare insurance business model that adapts to this architecture and classifies the patient according to their technology needs. Finally, and implementing a prototype of a system that matches and suits the healthcare recipient condition to the proper healthcare insurance policy by applying Web Ontology Language (OWL) and rule-based reasoning model using SWRL using Protég

Ambient Intelligence Based on IoT for Assisting People with Alzheimer s Disease Through Context Histories

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Towards Smart and Green Features of Cloud Computing in Healthcare Services: A Systematic Literature Review

Background: The healthcare sector has been facing multilateral challenges regarding the quality of services and access to healthcare innovations. As the population grows, the sector requires faster and more reliable services, but the opposite is true in developing countries. As a robust technology, cloud computing has numerous features and benefits that are still to be explored. The intervention of the latest technologies in healthcare is crucial to shifting toward next-generation healthcare systems. In developing countries like Ethiopia, cloud features are still far from being systematically explored to design smart and green healthcare services. Objective: To excavate contextualized research gaps in the existing studies towards smart and green features of cloud computing in healthcare information services. Methods: We conducted a systematic review of research publications indexed in Scopus, Web of Science, IEEE Xplore, PubMed, and ProQuest. 52 research articles were screened based on significant selection criteria and systematically reviewed. Extensive efforts have been made to rigorously review recent, contemporary, and relevant research articles. Results: This study presented a summary of parameters, proposed solutions from the reviewed articles, and identified research gaps. These identified research gaps are related to security and privacy concerns, data repository standardization, data shareability, self-health data access control, service collaboration, energy efficiency/greenness, consolidation of health data repositories, carbon footprint, and performance evaluation. Conclusion: The paper consolidated research gaps from multiple research investigations into a single paper, allowing researchers to develop innovative solutions for improving healthcare services. Based on a rigorous analysis of the literature, the existing systems overlooked green computing features and were highly vulnerable to security violations. Several studies reveal that security and privacy threats have been seriously hampering the exponential growth of cloud computing. 54 percent of the reviewed articles focused on security and privacy concerns. Keywords: Cloud computing, Consolidation, Green computing, Green features, Healthcare services, Systematic literature review

Az IoT-koncepción alapuló egészségügyi eszközök fogyasztók közötti elterjedését befolyásoló faktorok vizsgálata

Napjainkban számos területen érezhetjük a digitalizáció pozitív hatását. Nincs ez máshogy az egészségügy területén sem, ahol az IoT-koncepció (Internet of Things) adatgyűjtéssel, illetve a Big Data koncepció adatkezeléssel kapcsolatos megoldásai hozzájárulnak az adatorientált, személyre szabott egészségügyi döntésekhez. Jelen kutatás célja a fogyasztók témakörrel kapcsolatos véleményének felmérése, illetve a technológiai megoldások diffúzióját befolyásoló faktorok meghatározása annak érdekében, hogy a kutatás folytatásaként az igényekhez illeszkedő hardver- és szoftverplatform kialakítására nyíljon lehetőség. Az elfogadottságot befolyásoló tényezők vizsgálata érdekében kérdőíves felmérés történt öt fő témakört érintően, beleértve a különböző eszközökről és szolgáltatásokról alkotott véleményt. Az általános változók mellett a UTAUT2-technológia elfogadásának és használatának kiegészített modellje került alkalmazásra, a területhez való alkalmazkodás érdekében. Az elemzés során strukturális egyenletek modellezése (PLS-SEM) zajlott, majd az egyes tényezők látens változókra gyakorolt hatása ordinális logisztikus regresszióval került górcső alá, ezzel vizsgálva a modell fejlesztésének lehetőségeit

Machine learning and audio processing : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at Massey University, Albany, Auckland, New Zealand

In this thesis, we addressed two important theoretical issues in deep neural networks and clustering, respectively. Also, we developed a new approach for polyphonic sound event detection, which is one of the most important applications in the audio processing area. The developed three novel approaches are: (i) The Large Margin Recurrent Neural Network (LMRNN), which improves the discriminative ability of original Recurrent Neural Networks by introducing a large margin term into the widely used cross-entropy loss function. The developed large margin term utilises the large margin discriminative principle as a heuristic term to navigate the convergence process during training, which fully exploits the information from data labels by considering both target category and competing categories. (ii) The Robust Multi-View Continuous Subspace Clustering (RMVCSC) approach, which performs clustering on a common view-invariant subspace learned from all views. The clustering result and the common representation subspace are simultaneously optimised by a single continuous objective function. In the objective function, a robust estimator is used to automatically clip specious inter-cluster connections while maintaining convincing intra-cluster correspondences. Thus, the developed RMVCSC can untangle heavily mixed clusters without pre-setting the number of clusters. (iii) The novel polyphonic sound event detection approach based on Relational Recurrent Neural Network (RRNN), which utilises the relational reasoning ability of RRNNs to untangle the overlapping sound events across audio recordings. Different from previous works, which mixed and packed all historical information into a single common hidden memory vector, the developed approach allows historical information to interact with each other across an audio recording, which is effective and efficient in untangling the overlapping sound events. All three approaches are tested on widely used datasets and compared with recently published works. The experimental results have demonstrated the effectiveness and efficiency of the developed approaches

SHELDON Smart habitat for the elderly.

An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare