Ubiquitous healthcare profile management applying smart card technology

Nowadays, the patient-centric healthcare approach is focused on ubiquitous healthcare services. Furthermore, the adoption of cloud computing technology leads to more efficient ubiquitous healthcare systems. Moreover, the personalization of the delivery of ubiquitous healthcare services is enabled with the introduction of user profiles. In this paper, we propose five generic healthcare profile structures corresponding to the main categories of the participating entities included in a typical ubiquitous healthcare system in a cloud computing environment. In addition, we propose a profile management system incorporating smart card technology to increase its efficiency and the quality of the provided services of the ubiquitous healthcare system

Profile Management System in Ubiquitous Healthcare Cloud Computing Environment

A shift from the doctor-centric model to a patient-centric model is required to face the challenges of the healthcare sector. The vision of patient-centric model can be materialized integrating ubiquitous healthcare and the notion of personalization in services. Cloud computing can be the underlying technology for ubiquitous healthcare. The use of profiles enables the personalization in healthcare services and the use of profile management systems facilitates the deployment of these services. In this paper, we propose a profile management system in ubiquitous healthcare cloud computing environment. The proposed system exploits the cloud computing technology and the smart card technology to increase the efficiency and the quality of the provided healthcare services in the context of the patient-centric model. Furthermore, we propose generic healthcare profile structures corresponding to the main classes of the participating entities in a ubiquitous healthcare cloud computing environment

Towards personalized services in the healthcare domain

Healthcare services are designed for enabling the provision of medical care to the patient. The traditional healthcare services are based on the doctor-centric paradigm. Essentially, they enable healthcare providers to assess patients’ health status based on information derived from medical examination and information stored in patient’s electronic Medical Health Records (eMHRs) [1]. Hence, it is crucial for patient’s health data to be digitalized and organized in such a way allowing their exploitation by the healthcare provider at a later point of time [2]. The doctor-centric healthcare services enhance healthcare providers’ diagnosing skills and enable them to give patients accurate treatment directions aiming to their earlier and safer de-hospitalization

A new framework architecture for next generation e-Health services

The challenge for fast and low-cost deployment of ubiquitous personalized e-Health services has prompted us to propose a new framework architecture for such services. We have studied the operational features and the environment of e-Health services and we led to a framework structure that extends the ETSI/Parlay architecture, which is used for the deployment of standardized services over the next generation IP networks. We expanded the ETSI/Parlay architecture with new service capability features as well as sensor, profiling and security mechanisms. The proposed framework assists the seamless integration, within the e-Health service structure, of diverse facilities provided by both the underlying communication and computing infrastructure as well as the patient's bio and context sensor networks. Finally, we demonstrate the deployment of a tele-monitoring service in smart home environment based on the proposed framework architecture

Estimation of the Microbiological Quality of Meat using Rapid and Non-Invasive Spectroscopic Sensors

© 2020 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.Spectroscopic methods in tandem with machine learning methodologies have attracted considerable research interest for the estimation of food quality. The objective of this study was the evaluation of Fourier transform infrared (FTIR) spectroscopy and multispectral imaging (MSI) coupled with appropriate machine learning regression algorithms for assessing meat microbiological quality. For this purpose, minced pork patties were stored aerobically and under modified atmosphere packaging (MAP) conditions, at isothermal and dynamic temperature conditions. At regular time intervals during storage, samples were subjected to (i) microbiological analysis, (ii) FTIR measurements and (iii) MSI acquisition. The collected FTIR data were processed by feature extraction methods to reduce dimensionality, and subsequently Support Vector Machines (SVM) regression models were trained using spectral features (FTIR and MSI) to estimate microbiological quality of meat (microbial population). The regression models were evaluated with different experimental replicates using distinct meat batches. The performance of the models was evaluated in terms of correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE) and residual prediction deviation (RPD). The RMSE values for the microbial population estimation models using FTIR were 1.268 and 1.024 for aerobic and MAP storage, respectively. The performance in terms of RMSE for the MSI-based models was 1.144 for aerobic and 0.923 for MAP storage, while the combination of FTIR and MSI spectra resulted in models with RMSE equal to 1.146 for aerobic and 0.886 for MAP storage. The experimental results demonstrated the potential of estimating the microbiological quality of minced pork meat from spectroscopic data.Peer reviewe

Group profile management in ubiquitous healthcare environment

Nowadays, ubiquitous healthcare is of utmost importance in the patient-centric model. Furthermore, the personalization of ubiquitous healthcare services plays a very important role to make the patient-centric model a reality. The personalization of the ubiquitous healthcare services is based on the profiles of the entities participating in these services. In this paper, we propose a group profile management system in a ubiquitous healthcare environment. The proposed system is responsible for the dynamic creation of a group profile and its management

Ubiquitous healthcare profile management applying smart card technology

Nowadays, the patient-centric healthcare approach is focused on ubiquitous healthcare services. Furthermore, the adoption of cloud computing technology leads to more efficient ubiquitous healthcare systems. Moreover, the personalization of the delivery of ubiquitous healthcare services is enabled with the introduction of user profiles. In this paper, we propose five generic healthcare profile structures corresponding to the main categories of the participating entities included in a typical ubiquitous healthcare system in a cloud computing environment. In addition, we propose a profile management system incorporating smart card technology to increase its efficiency and the quality of the provided services of the ubiquitous healthcare system

Healthcare profile management system in smart cards

Nowadays, healthcare profile management systems are essential for ubiquitous healthcare systems in cloud computing environments. However, these profile management systems incorporate user profiles consisting of limited user information associated with user preferences and interests. Thus, it is required the deployment of profile management systems enabling the reliable creation and efficient management of enriched user profiles. Toward to this effort, in this paper, we propose a smart card file system design for the user healthcare smart cards incorporated in a healthcare profile management system applying in a typical ubiquitous healthcare system