A Trust Model for Ubiquitous Healthcare Environment on the Basis of Adaptable Fuzzy-Probabilistic Inference System.

Trust is considered to be a determinant on psychologist selection which can ensure patient satisfaction. Hence, trust concept is essential to be introduced into ubiquitous healthcare (UH) environment oriented on patients with anxiety disorders. This is accomplished by trust model estimating psychologists' trustworthiness, a priory to service delivery, with the use of patient's and his/her acquaintances testimonies, i.e., personal interaction experience and reputation (R). In this paper, a trust model is proposed to be materialized via an adaptable cloud inference system (ACIS) that performs trust value (TV) estimation. Taking advantage of a cloud theory, the introduced ACIS estimates TVs via fuzzy-probabilistic reasoning incorporating a cloud relation operator (soft AND) which is proposed to be tuned by trust information sources consistency and coherency. Theoretical analysis along with comparative study conducted within MATLAB environment and experimental investigation verify the effectiveness of the proposed ACIS materialization under different conditions. Especially, the innovative features of ACIS enable TV to be estimated with 45.5% and 62% on average higher accuracy to that providing state-of-the-art trust models, within clean environment and under the influence of large-scale collusive malicious attacks, respectively. The enhanced robustness permits the untrustworthy UH providers to be discriminated with true positive rate at the range of 0.9 although 40% of R testimonies are erroneous. Finally, experimental investigation validates that the adoption of the proposed trust model for psychologists trustworthiness estimation facilitates patient satisfaction to be achieved into UH environment.

A comprehensive Reputation mechanism for ubiquitous healthcare environment exploiting cloud model.

Absence of trust foundations may outweigh benefits of ubiquitous and personalized mental healthcare supervision provided within a Ubiquitous Healthcare environment (UH). Trust is composed by patient's Personal Interaction Experience (PIE) and social entourage accumulated PIE, i.e. Reputation (R). In this paper, a cloud-based Reputation mechanism is proposed. Since PIE is the elementary trust information source, also an Updating mechanism of PIE, is introduced, in this paper. Cloud materialization of combined mechanisms provides adaptability to UH Providers' dynamic behavior, facilitates detection of milking behaviors and complex malicious attacks while meets the challenge of limited accuracy in case of data sparseness. The effectiveness of the proposed mechanisms is verified via simulation in MATLAB.

A novel trust evaluation method for Ubiquitous Healthcare based on cloud computational theory.

The notion of trust is considered to be the cornerstone on patient-psychiatrist relationship. Thus, a trustfully background is fundamental requirement for provision of effective Ubiquitous Healthcare (UH) service. In this paper, the issue of Trust Evaluation of UH Providers when register UH environment is addressed. For that purpose a novel trust evaluation method is proposed, based on cloud theory, exploiting User Profile attributes. This theory mimics human thinking, regarding trust evaluation and captures fuzziness and randomness of this uncertain reasoning. Two case studies are investigated through simulation in MATLAB software, in order to verify the effectiveness of this novel method.

Stress-oriented driver assistance system for electric vehicles.

Stress is physiological and physical reaction that appears in highly demanding situations and affects human's perception and reaction capability. Occurrence of stress events within highly dynamic road environment could lead to life-threatening situation. With the perspective of safety and comfort driving provision to anxious drivers, in this paper a stress-oriented Driver Assistance System (DAS) is proposed. The DAS deployed on Electric Vehicle. This novel DAS customizes driving command signal in respect to road context, when stress is detected. The effectiveness of this novel DAS is verified by simulation in MATLAB/SIMULINK environment.

RespDoc: a new clinical decision support system for childhood asthma management based on Fraction of Exhaled Nitric Oxide (FeNO) measurements.

The use of Fraction of Exhaled Nitric Oxide (FeNO) for measurement of inflammation in the respiratory system is a good way to assess the level of asthma in children. In this paper we present a new Clinical Decision Support System (CDSS) for Childhood Asthma Management based on FeNO, which is named RespDoc. The core of RespDoc is a decision making algorithm and a patient's monitoring process that are extensively analyzed in the paper. The performance of RespDoc is tested through the process and assessment of archived patients' data.

Improving EMG based classification of basic hand movements using EMD.

This paper presents a pattern recognition approach for the identification of basic hand movements using surface electromyographic (EMG) data. The EMG signal is decomposed using Empirical Mode Decomposition (EMD) into Intrinsic Mode Functions (IMFs) and subsequently a feature extraction stage takes place. Various combinations of feature subsets are tested using a simple linear classifier for the detection task. Our results suggest that the use of EMD can increase the discrimination ability of the conventional feature sets extracted from the raw EMG signal.

u-MCHC: a predictive framework for ubiquitous management of exacerbations in chronic diseases.

Exacerbations are crucial events in chronic diseases that require continuous management. Knowledge of the exacerbation risk enhances patient's quality of life and enables self-management and self-organizing of unscheduled doctor visits and/or hospitalization. This paper proposes a new framework for ubiquitous management of chronic diseases named u-MCHC. The proposed framework incorporates monitoring, decision-making, notification and management processes in order to deliver personalized therapeutical options and services. The delivery of services is realized by means of Next Generation Service Delivery Platform (NG-SDP). A prototype implementation of u-MCHC and its performance is demonstrated in a real world case for Chronic Obstructive Pulmonary Disease (COPD).

Application of Multiprotocol Medical Imaging Communications and an Extended DICOM WADO Service in a Teleradiology Architecture.

Multiprotocol medical imaging communication through the Internet is more flexible than the tight DICOM transfers. This paper introduces a modular multiprotocol teleradiology architecture that integrates DICOM and common Internet services (based on web, FTP, and E-mail) into a unique operational domain. The extended WADO service (a web extension of DICOM) and the other proposed services allow access to all levels of the DICOM information hierarchy as opposed to solely Object level. A lightweight client site is considered adequate, because the server site of the architecture provides clients with service interfaces through the web as well as invulnerable space for temporary storage, called as User Domains, so that users fulfill their applications' tasks. The proposed teleradiology architecture is pilot implemented using mainly Java-based technologies and is evaluated by engineers in collaboration with doctors. The new architecture ensures flexibility in access, user mobility, and enhanced data security.

PKI security in large-scale healthcare networks.

During the past few years a lot of PKI (Public Key Infrastructures) infrastructures have been proposed for healthcare networks in order to ensure secure communication services and exchange of data among healthcare professionals. However, there is a plethora of challenges in these healthcare PKI infrastructures. Especially, there are a lot of challenges for PKI infrastructures deployed over large-scale healthcare networks. In this paper, we propose a PKI infrastructure to ensure security in a large-scale Internet-based healthcare network connecting a wide spectrum of healthcare units geographically distributed within a wide region. Furthermore, the proposed PKI infrastructure facilitates the trust issues that arise in a large-scale healthcare network including multi-domain PKI infrastructures.

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.

A proposed Next Generation Service Delivery Platform (NG-SDP) for eHealth domain.

Nowadays, providing healthcare personalized services in user's intelligent space is an important issue for improving personal health, supporting predictive care and saving medical costs. In this paper, we propose an architecture for the Next Generation Service Delivery Platform (NG-SDP), suitable for composing and delivering personalized healthcare services. The core component of NG-SDP is a Context Decision Making Enabler (CDME) that assesses user contextual and bio information to yield personalized services. A prototype implementation of the proposed NG-SDP is also demonstrated. Finally a real case study demonstrates the CDME performance.

e-SCP-ECG Protocol: An Expansion on SCP-ECG Protocol for Health Telemonitoring-Pilot Implementation.

Standard Communication Protocol for Computer-assisted Electrocardiography (SCP-ECG) provides standardized communication among different ECG devices and medical information systems. This paper extends the use of this protocol in order to be included in health monitoring systems. It introduces new sections into SCP-ECG structure for transferring data for positioning, allergies, and five additional biosignals: noninvasive blood pressure (NiBP), body temperature (Temp), Carbon dioxide (CO(2)), blood oxygen saturation (SPO(2)), and pulse rate. It also introduces new tags in existing sections for transferring comprehensive demographic data. The proposed enhanced version is referred to as e-SCP-ECG(+) protocol. This paper also considers the pilot implementation of the new protocol as a software component in a Health Telemonitoring System.

A contextual data mining approach toward assisting the treatment of anxiety disorders.

Anxiety disorders are considered the most prevalent of mental disorders. Nevertheless, the exact reasons that provoke them to patients remain yet not clearly specified, while the literature concerning the environment for monitoring and treatment support is rather scarce warranting further investigation. Toward this direction, in this study a context-aware approach is proposed, aiming to provide medical supervisors with a series of applications and personalized services targeted to exploit the multiparameter contextual data collected through a long-term monitoring procedure. More specifically, an application that assists the archiving and retrieving of the patients' health records was developed, and four treatment supportive services were considered. The three of them focus on the discovery of possible associations between the patient's contextual data; the last service aims at predicting the stress level a patient might suffer from, in a given context. The proposed approach was experimentally evaluated quantitatively (in terms of computational efficiency and time requirements) and qualitatively by experts on the field of mental health domain. The feedback received was very encouraging and the proposed approach seems quite useful to the anxiety disorders' treatment.

Leveraging dynamic user profiles for the assistance of anxiety disorders' treatment using inferential rules.

While anxiety disorders exhibit an impressive spread especially in western societies, context-awareness seems a promising technology to provide assistance to physicians in psychotherapy sessions. In the present paper an approach addressing the assistance of the anxiety disorders' treatment is proposed. The suggested method employs the a priori association rule mining algorithm in order to achieve dynamic update of patient profiles according to generated rules describing the underlying relations between patients' main context conditions and their stress level. This method was evaluated by therapists specializing in the mental health domain and the feedback received was very encouraging with respect to the assistance dynamic patient profiles offer, during CBT sessions.

Establishing telemedicine system to support urgent incidents around the borderline of Greece: implemented architecture and evaluation.

An evaluation of a wide area Telemedicine System (TS) designed for a country with singular geomorphology like Greece is presented. It targets to improve the outcome in emergency cases, by means of an early and specialized pre-hospital treatment. The TS makes use of modern technologies leading to the cooperation of 30 mobile medical units, 3 Telemedicine Coordination Centers and 7 Regional Teleconference Rooms. An adaptive protocol is used to reduce the data transmission time and the resources required for archiving. An automated network switching keeps the communication live in most cases while a telemedicine service co-ordinates all the co-operating endpoints, providing call and connection management, remote healthcare assistance, teleconference capabilities and real-time vital signs' transmission.

Integrity mechanism for eHealth tele-monitoring system in smart home environment.

During the past few years, a lot of effort has been invested in research and development of eHealth tele-monitoring systems that will provide many benefits for healthcare delivery from the healthcare provider to the patient's home. However, there is a plethora of security requirements in eHealth tele-monitoring systems. Data integrity of the transferred medical data is one of the most important security requirements that should be satisfied in these systems, since medical information is extremely sensitive information, and even sometimes life threatening information. In this paper, we present a data integrity mechanism for eHealth tele-monitoring system that operates in a smart home environment. Agent technology is applied to achieve data integrity with the use of cryptographic smart cards. Furthermore, the overall security infrastructure and its various components are described.

WADA service: an extension of DICOM WADO service.

The Web Access to Digital Imaging and Communication in Medicine (DICOM) Persistent Objects (WADO) service is standardized as the Web extension to DICOM. This paper analyzes the operational specifications of the WADO service and extends its access capability to the whole DICOM hierarchy (patient, study, series, and object). The proposed Web Access to DICOM Archives (WADA) service, as opposed to WADO, also includes an extrainternal query mechanism and support of medical reports submission. A pilot implementation of WADA as software components and their integration into a three-tier architecture are also presented. Advanced security mechanisms are augmented to ensure communication encryption, user identification, and access restriction to data according to user roles. The proposed service is a simple approach, and can be embedded in any system managing medical images and reports. WADA can also be integrated into the Cross-Enterprise Document Sharing-Imaging (XDS-I) standard, which is considered to be the most likely future standard for medical imaging exchange.

A hierarchical, ontology-driven Bayesian concept for ubiquitous medical environments--a case study for pulmonary diseases.

The present paper extends work on an existing computer-based Decision Support System (DSS) that aims to provide assistance to physicians as regards to pulmonary diseases. The extension deals with allowing for a hierarchical decomposition of the task, at different levels of domain granularity, using a novel approach, i.e. Hierarchical Bayesian Networks. The proposed framework uses data from various networking appliances such as mobile phones and wireless medical sensors to establish a ubiquitous environment for medical treatment of pulmonary diseases. Domain knowledge is encoded at the upper levels of the hierarchy, thus making the process of generalization easier to accomplish. The experimental results were carried out under the Pulmonary Department, University Regional Hospital Patras, Patras, Greece. They have supported our initial beliefs about the ability of Bayesian networks to provide an effective, yet semantically-oriented, means of prognosis and reasoning under conditions of uncertainty.

Reference implementation model for Medical Information Systems' interoperability.

Interoperability, in the electronic environment of healthcare enterprises, is required for the effective communication between the various Medical Information Systems (MISs). However, interoperability is a large and multidimensional issue. Its syntactic dimension is linked with the use of existing messaging standards. Their proprietary and specialized implementations have led to the establishment of advanced middleware platforms in order to support the communication between heterogeneous MISs. This paper approaches syntactic interoperability from the standardization point of view and proposes a Reference Implementation Model (RImM), for the middleware platforms. RImM specifies the functional entities of this platform, the end-to-end services and the internal common messages format. It also specifies common communication profiles and interfaces that allow real world events and information to be visibly handled and distributed among MISs without any interference in their structure.

Dynamic biosignal management and transmission during telemedicine incidents handled by Mobile Units over diverse network types.

Early and specialized pre-hospital patient treatment improves outcome in terms of mortality and morbidity, in emergency cases. This paper focuses on the design and implementation of a telemedicine system that supports diverse types of endpoints including moving transports (MT) (ambulances, ships, planes, etc.), handheld devices and fixed units, using diverse communication networks. Target of the above telemedicine system is the pre-hospital patient treatment. While vital sign transmission is prior to other services provided by the telemedicine system (videoconference, remote management, voice calls etc.), a predefined algorithm controls provision and quality of the other services. A distributed database system controlled by a central server, aims to manage patient attributes, exams and incidents handled by different Telemedicine Coordination Centers (TCC).