Pursuing perspectives on ambient intelligence.

This paper takes a broad perspective on ambient, intelligent technologies in the context of contemporary European society at the turn of the 21st century. The underlying ideas and expectations of ambient intelligence in a period when Europe focuses progressively on the various social, economic, and ethical challenges facing the Information Society are discussed. The use of information and communication technologies in different organizational and economic settings are explored, with an illustrative focus on eHealth. It is particularly argued that more space, effort and facilities need to be created for a public social and ethical debate among European‟s citizens with regard to information and communication technologies development

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

The Impact of Digital Service Quality Toward Customer Engagement: A Case Study of Telemedicine in Thailand

Purpose: The aims of this study are to examine the effect of digital service quality on customer engagement with telemedicine systems and to investigate how such effects change depending on a variety of socioeconomic characteristics.   Design/methodology/approach:  The survey research with online questionnaire was conducted with 405 telemedicine experienced samples. The proposed hypotheses were tested using the Structural Equation Modeling (SEM) method.   Findings:  The results revealed that digital service quality significantly influences customer engagement. A second-order confirmatory factor analysis of the digital service quality (DSQ) construct revealed that the efficiency dimension best explained DSQ, followed by the responsiveness and interaction dimensions. The study of moderation revealed that the effect of DSQ on CE was greater in younger age groups than in older age groups. In addition, those with a higher level of formal education appear to have higher levels of CE than those with a lesser level of formal education.   Research, Practical & Social implications: The study will help practitioners create telemedicine services that are more efficient and effective so that patients are more engaged and loyal to the telemedicine service providers.   Originality/value: The value of the study is that it is one of the rare attempts to clarify the consequences of digital service quality from the perspective of the consumer, and it proposes several implications and recommendations

Pervasive Business Intelligence: A New Trend in Critical Healthcare

In the field of intensive medicine, presentation of medical information is identified as a major concern for the health professionals, since it can be a great aid when it is necessary to make decisions, of varying gravity, for the patient's state. The way in which this information is presented, and especially when it is presented, may make it difficult for the intensivists within intense healthcare units to understand a patient's state in a timely fashion. Should there be a need to cross various types of clinical data from various sources, the situation worsens considerably. To support the health professional's decision-making process, the Pervasive Business Intelligence (PBI) Systems are a forthcoming field. Based on this principle, the current study approaches the way to present information about the patients, after they are received in a BI system, making them available at any place and at any time for the intensivists that may need it for the decision-making. The patient's history will, therefore, be available, allowing examination of the vital signs data, what medicine that they might need, health checks performed, among others. Then, it is of vital importance, to make these conclusions available to the health professionals every time they might need, so as to aid them in the decision-making. This study aims to make a stance by approaching the theme of PBI in Critical Healthcare. The main objective is to understand the underlying concepts and the assets of BI solutions with Pervasive characteristics. Perhaps consider it a sort of guide or a path to follow for those who wish to insert Pervasive into Business Intelligence in Healthcare area.Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013info:eu-repo/semantics/publishedVersio

Logico-linguistic semantic representation of documents

The knowledge behind the gigantic pool of data remains largely unextracted. Techniques such as ontology design, RDF representations, hpernym extraction, etc. have been used to represent the knowledge. However, the area of logic (FOPL) and linguistics (Semantics) has not been explored in depth for this purpose. Search engines suffer in extraction of specific answers to queries because of the absence of structured domain knowledge. The current paper deals with the design of formalism to extract and represent knowledge from the data in a consistent format. The application of logic and linguistics combined greatly eases and increases the precision of knowledge translation from natural language. The results clearly indicate the effectiveness of the knowledge extraction and representation methodology developed providing intelligence to machines for efficient analysis of data. The methodology helps machines to precise results in an efficient manner

Toward energy-efficient and trustworthy eHealth monitoring system

The rapid technological convergence between Internet of Things (IoT), Wireless Body Area Networks (WBANs) and cloud computing has made e-healthcare emerge as a promising application domain, which has significant potential to improve the quality of medical care. In particular, patient-centric health monitoring plays a vital role in e-healthcare service, involving a set of important operations ranging from medical data collection and aggregation, data transmission and segregation, to data analytics. This survey paper firstly presents an architectural framework to describe the entire monitoring life cycle and highlight the essential service components. More detailed discussions are then devoted to {em data collection} at patient side, which we argue that it serves as fundamental basis in achieving robust, efficient, and secure health monitoring. Subsequently, a profound discussion of the security threats targeting eHealth monitoring systems is presented, and the major limitations of the existing solutions are analyzed and extensively discussed. Finally, a set of design challenges is identified in order to achieve high quality and secure patient-centric monitoring schemes, along with some potential solutions

What Characterizes Safety of Ambient Assisted Living Technologies?

Ambient assisted living (AAL) technologies aim at increasing an individual's safety at home by early recognizing risks or events that might otherwise harm the individual. A clear definition of safety in the context of AAL is still missing and facets of safety still have to be shaped. The objective of this paper is to characterize the facets of AAL-related safety, to identify opportunities and challenges of AAL regarding safety and to identify open research issues in this context. Papers reporting aspects of AAL-related safety were selected in a literature search. Out of 395 citations retrieved, 28 studies were included in the current review. Two main facets of safety were identified: user safety and system safety. System safety concerns an AAL system's reliability, correctness and data quality. User safety reflects impact on physical and mental health of an individual. Privacy, data safety and security issues, sensor quality and integration of sensor data, as well as technical failures of sensors and systems are reported challenges. To conclude, there is a research gap regarding methods and metrics for measuring user and system safety in the context of AAL technologies