Ebook: pHealth 2014
Microsystems, smart textiles, telemedicine, mobile computing, smart implants, sensor-controlled medical devices, and innovative sensor and actuator principles and techniques have become important enablers, not only for monitoring, diagnosis and treatment in both inpatient and outpatient care, but also for personalized, preventive, predictive participative systems medicine.
This book contains the proceedings of pHealth 2014, the 11th in a series of successful international conferences on wearable or implantable micro and nano technologies for personalized medicine, held in Vienna, Austria, in June 2014. This conference combined the presentation of emerging principles, future visions and use with a careful analysis of lessons learned from international and national research and development activities and practical solutions. Included here are the keynotes, as well as the oral presentations and poster presentations selected after having been checked by three independent reviewers for inclusion in the conference. The new EU Framework Program for Research and Innovation, Horizon 2020, addressing pHealth implementation by focusing on technology transfer support and building ecosystems and value chains to ensure better time to market and higher impact of knowledge-based technologies, is properly reflected as well.
The advances made so far in this field are just the beginning of evolutionary and revolutionary changes which will offer significant opportunities for patients and healthcare professionals alike, and this book will be of interest to all those developing, providing or receiving such healthcare services.
Cover Image Courtesy of Don Espresso – aboutpixel.de
The pHealth 2014 Conference is the 11th in a series of scientific events bringing together expertise from medical, technological, political, administrative, and social domains, all related to the provision of personalized health services. Aspects such as cooperation between primary, secondary and tertiary health care establishments, the inclusion of social care, home care and lifestyle management, practical experiences with local or regional telemedicine services, management of chronic diseases, Quality assurance challenges, health games, terminologies and ontologies, data management and visualizations, medical decision support, monitoring of environmental and living conditions of citizens using mobile wearable or implementable technologies as well as social and ethical issues of health (care) provision are to be addressed by almost 40 speakers from various parts of the world. Keynotes, invited talks, and oral presentations discuss foundations and principles, requirements and solutions for pHealth. European success stories and national pilots as well as innovations and industrial products enabling the paradigm change towards participative and personalized health form the scientific program, together with demonstrations of existing and emerging applications in the pHealth domain. Presentations will be complemented by a students' poster competition.
In the last years, the pHealth conferences have emerged as the leading international conference series on wearable micro and nano technologies for personalized medicine and personalized health service provision. Starting in 2003, pHealth has gained importance for attracting well acknowledged scientists in the domains of relevant technologies, medical doctors, and policy makers from academic institutions, hospital administrations, governmental and regulatory bodies, the healthcare industry and allied professions. Collecting the experience of a dynamically emerging professional community from Europe and beyond, the pHealth event series has given visibility to the tremendous potential of micro and nano technologies not only for the future of medicine, but also for the improvement of health care and welfare processes today and tomorrow, thereby helping to integrate health and social care.
Microsystems, smart textiles, telemedicine, mobile computing, smart implants, sensor-controlled medical devices, and innovative sensor and actuator principles and techniques as well as related body, local and wide area networks up to Cloud services have become important enablers not only for monitoring, diagnosis, and treatment in both inpatient and outpatient care, but also for preventive and predictive systems medicine. This is, however, just the beginning of evolutionary and revolutionary changes, paradigm shifts, and the respective significant opportunities for patients, citizens, health professionals, healthcare establishments, and companies engaged in the micro and nano technologies. This indeed addresses the interest of the entire healthcare industry. The multilateral benefits of the whole gamut of enabling pHealth technologies for all addressed stakeholders lead to a win-win situation with enormous potential, not only for medical quality improvement and industrial competitiveness, but for increasing access to care alike whilst managing healthcare costs.
The pHealth 2014 Conference tackles existing and emerging technologies, uptakes the outcome from successful European projects in various domains, and addresses topics beyond the traditional clinical, primary care, and public health scope. The presentations range from latest developments to running projects and initiatives to lessons learned from keeping project results sustainable.
The pHealth 2014 Conference thankfully benefits from the experience and the lessons learned from the organizing committees of previous pHealth events, particularly 2009 in Oslo, 2010 in Berlin, 2011 in Lyon, 2012 in Porto, and 2013 in Tallinn. The 2009 conference brought up the interesting idea of having special sessions focusing on a particular topic, and being organized by a mentor/moderator. The Berlin event in 2010 initiated workshops on particular topics prior to the official kick-off of the conference. Lyon in 2011 initiated the launch of so-called dynamic demonstrations allowing the participants to dynamically show software and hardware solutions on the fly without needing a booth. Implementing pre-conference events, the pHealth 2012 in Porto gave attendees a platform for presenting and discussing recent developments and provocative ideas that helped to animate the sessions. Highlights of pHealth 2013 in Tallinn was the special session on European projects' success stories, but also presentations on the newest paradigm changes and challenges coming up with Big Data, Analytics, Translational and Nano Medicine, etc.
The pHealth 2014 Conference combines the presentation of emerging principles, future visions and views with a careful analysis of lessons learned from international and national R&D activities and practical solutions. The new EU Framework Program for Research and Innovation, Horizon 2020, also addresses pHealth implementation by focusing on technology transfer support and building ecosystems and value chains to ensure better time to market and higher impact of knowledge-based technologies. As the acceptance of solutions is crucial for the adoption of technologies, and the acceptance heavily depends on the trust in those solutions, security and privacy issues form an important part of the 2014 event. The conference is completed by a Satellite Conference of the Austrian Scientific Society for Telemedicine and eHealth (ASSTeH).
ASSTeH, but also the Working Groups “Electronic Health Records (EHR)”, “Personal Portable Devices (PPD)”, and “Security, Safety and Ethics (SSE)” of the European Federation for Medical Informatics (EFMI), are supporters of pHealth 2014 and actively involved in the preparation and realization of the conference.
This proceedings volume covers keynotes, oral presentations and poster presentation selected from a bunch of submissions to the pHealth 2014 conference. All submissions have been carefully and critically reviewed. The editors are indebted to the acknowledged and highly experienced reviewers for having essentially contributed to the quality of the conference and the book at hand.
Both the pHealth 2014 Conference and the publication of the pHealth 2014 proceedings at IOS Press would not have been possible without the supporters and sponsors: Health Level 7 International (HL7 International), HL7 Austria, HL7 Germany, ASSTeH, and European Federation for Medical Informatics (EFMI).
The editors are also grateful to the dedicated efforts of the Local Organizing Committee members and their supporters for carefully and smoothly preparing and operating of the conference. They especially thank all team members of the eHealth Research and the management of the University of Applied Sciences Technikum Wien for their continuous involvement in the organization and realization of the conference.
Bernd Blobel, Stefan Sauermann, Alexander Mense
Editors
Smart miniaturized systems, emerging from the integration of heterogeneous technologies like micro- and nano electronics, photonics, biotechnology, materials and information & communication technologies are considered today, after two decades of intensive public support, proven concepts and functional prototypes, as key enablers opening up new opportunities for healthcare and in particular personalized health. They offer an enhanced ability to sense, detect, analyze, communicate, respond, and monitor phenomena from macro (e.g. body, tissues) to nano scale (e.g. molecules, genes). For the majority of these projects, planning for the next phase of prototype validation, product design, supply chain, user targeting, clinical validation and commercial roll-out are now taking full attention. The new EU Framework Program for Research and Innovation, Horizon 2020, is focusing on technology transfer support and building ecosystems and value chains to ensure better time to market and higher impact of knowledge-based technologies. The state-of-the-art and upcoming challenges for the implementation of H2020 and new opportunities in smart systems for pHealth are discussed in the paper.
Current paradigm changes for improving safety, quality and efficiency of care processes under massive deployment of information and communication technologies (ICT) place high requirements on privacy and security. These mainly focus on privilege management and access control harmonized in international standards and their further evolution. NIST and ISO, but especially HL7 play a prominent role in this context. Starting with classic role-based access control (RBAC) foundations to new specifications for security and privacy labeling of segmented health information, HL7 security is presented as a scalable intermediate solution on the way to comprehensive privilege management and access control by explicit, ontology-based, formal and therefore machine-processable policies. The successfully balloted HL7 labeling specification supports context-sensitive communication and cooperation between different stakeholders and processes with different purposes of use, based on meta-data of information, actors and processes involved. Basics of policy management and practical solutions are discussed.
Advances in information and communications technologies (ICT) enable new personalized health care concepts which are often characterized by four “P” terms, i.e. personalized, predictive, preventive and participatory. However, real world implementations of the complete 4P spectrum hardly exist today. The Internet of Things (IoT) has been defined as an extension to the current Internet that enables pervasive communication between the physical and the virtual world. Smart devices and enabling elements like Near Field Communication (NFC) and Radio Frequency Identification (RFID) technology already exist and increasingly will be a mainstream element of our lives. This future vision paper attempts to assess if and how the Internet of Things for personalized health (IoT4pH) can help to facilitate the 4P healthcare paradigm and discusses related challenges and opportunities.
Healthcare information is distributed through multiple heterogeneous and autonomous systems. Access to, and sharing of, distributed information sources are a challenging task. To contribute to meeting this challenge, this paper presents a formal, complete and semi-automatic transformation service from Relational Databases to Web Ontology Language. The proposed service makes use of an algorithm that allows to transform several data models of different domains by deploying mainly inheritance rules. The paper emphasizes the relevance of integrating the proposed approach into an ontology-based interoperability service to achieve semantic interoperability.
In healthcare a huge amount of assessment scales and score systems are in use to abbreviate and summarize the results of clinical observations to interpret a patient's condition in a valid and reliable manner. It is challenging to convey the information in a semantic interoperable form to other systems. A bad approach would be to invent individual models for each of them. Within this paper we would like to demonstrate that a generic model is sufficient by demonstrating the realization with the Glasgow Coma Scale.
A Personal Health Record (PHR) is a health information repository controlled and managed directly by a patient or his/her custodian, or a person interested in his/her own health. PHR System's adoption and compliance with international standards is foremost important because it can help to meet international, national, regional or institutional interoperability and portability policies. In this paper, an interoperable PHR System for supporting the control of type 2 diabetes mellitus is proposed, which meets the mandatory interoperability requirements proposed in the Personal Health Record System Functional Model standard (ISO 16527). After performing a detailed analysis of different applications and platforms for the implementation of electronic Personal Health Records, the adaptation of the Indivo Health open source platform was completed. Interoperability functions were added to this platform by integrating the Mirth Connect platform. The assessment of the platform's interoperability capabilities was carried out by a group of experts, who verified the interoperability requirements proposed in the ISO 16527 standard.
The integration of health and social care is the latest dogma for improving the quality of care for chronic and frail patients. In the Veneto Region, a unique platform has been developed for the provision of both telecare and telehealth to chronic patients that are equipped at home with a personal health system for real time detection of emergencies situations and to measure their clinical parameters according to a plan scheduled by their clinician. The integrated service is centrally managed by a regional eHealth center that represents the point of intermediation between the patient and the health and social care professionals.
The use of biomedical ontologies is increasing, especially in the context of health systems interoperability. Ontologies are key pieces to understand the semantics of information exchanged. However, given the diversity of biomedical ontologies, it is essential to develop tools that support harmonization processes amongst them. Several algorithms and tools are proposed by computer scientist for partially supporting ontology harmonization. However, these tools face several problems, especially in the biomedical domain where ontologies are large and complex. In the harmonization process, matching is a basic task. This paper explains the different ontology harmonization processes, analyzes existing matching tools, and proposes a prototype of an ontology harmonization service. The results demonstrate that there are many open issues in the field of biomedical ontology harmonization, such as: overcoming structural discrepancies between ontologies; the lack of semantic algorithms to automate the process; the low matching efficiency of existing algorithms; and the use of domain and top level ontologies in the matching process.
Problem: Stress-related disorders have become one of the main problems of public health in many countries and of worldwide organizations, and they are expected to become more common in the forthcoming decades.
Objective: This article aims at providing a systematic review and a descriptive evaluation of the interventions supported by ICT for the prevention and treatment of occupational stress.
Methods: A systematic review of five databases (EBSCO, The Cochrane Library, PubMed, ScienceDirect and IEEEXplorer) was carried out.
Results: This article provides a quantitative and qualitative description of 21 studies about occupational stress interventions supported by ICT. The following factors were considered for the analysis: impact of the intervention, design of the study, type of intervention, purpose of the intervention, type of instrument for the measurement of occupational stress, and type of ICT used.
Conclusions: The systematic review demonstrated that interventions supported by ICT for the prevention and treatment of occupational stress are scarce but effective.
There is the potential that cognitive activity may delay cognitive decline in people with mild cognitive impairment. Games provide both cognitive challenge and motivation for repeated use, a prerequisite for long lasting effect. Recent advances in technology introduce several new interaction methods, potentially leading to more efficient, personalized cognitive gaming experiences. In this paper, we present an Augmented Reality (AR) cognitive training game, utilizing cubes as input tools, and we test the cube interaction with a pilot study. The results of the study revealed the marker occlusion problem, and that novice AR users can adjust to the developed AR environment after a small number of sessions.
Antibiotic resistance is a heterogeneous phenomenon. It does not only differ between countries or states, but also between wards of hospitals, where different resistance patterns have been found. To support clinicians in administering empiric antibiotic therapy, we developed software to present information about antibiotic resistance using a mobile concept. A pre-existing infrastructure was deployed as the server component. The systems analyze and aggregate data from laboratory information systems, generating statistical data on antibiotic resistance. The information is presented to the Android client using a Representational State Transfer (REST) interface. Geographical localization is performed using near field communication (NFC) tags. The prototype provides tabulated data concerning antibiotic resistance patterns in the wards of a hospital. Using Android, NFC, and data caching, the usability of the system is estimated to be high. We hypothesize that antibiotic stewardship in hospitals can be supported by this software, thus improving medical monitoring of antibiotic resistance. Future studies in a productive environment are needed to measure the impact of the system on the outcome of patient care.
In this study, the transmission and reflection of two conductive fabrics are investigated in the frequency range from 2 to 18 GHz. One of the fabrics is a non-woven polypyrrole, and the other consists of a polyethylene warp with steel threads in the weft. Reflection and transmission measurements are performed in order to characterize the electromagnetic properties of the materials. Reflection measurements are performed for two polarizations at normal, 0°, and 60° incident angles. Transmission measurements are also done for two polarization directions at normal incidence. The results show that the fabric with the steel filler reflects most of the incident radiation, and has very low transmission with some polarization dependence. The polypyrrole non-woven fabric, on the other hand, has reflection and transmission properties that show that it is absorbing the incident radiation. Wearable on-body sensors that in addition are comfortable to wear can be integrated in the textile of clothes. These sensors can e.g., be used to monitor health or analyze gait. The fabrics have the potential to be used in health applications when designing on-body sensors, e.g. for movement analysis.
Monitoring human physical activity has become an important research area and is essential to evaluate the degree of functional performance and general level of activity of a person. The discrimination of daily living activities can be implemented with machine learning techniques. A public dataset provided during the European Symposium on Artificial Neural Networks 2013, with time and frequency domain features extracted from raw signals of the smartphone inertial sensors, was used to implement and evaluate an activity classifier. Using a decision tree classifier, an accuracy of 86% was achieved for the classification of walk, climb stairs, stand, sit, and lay down. The results obtained suggest that the smartphone's inertial sensors could be used for an accurate physical activity classification even with real-time requirements.
Glomerular filtration rate (GFR) is considered the best parameter for the assessment of renal function, being usually determined on the basis of urine or plasma clearance of exogenous renal markers. The common methodology is invasive, time consuming and cumbersome, with multiple blood and/or urine sampling and following laboratory assays required. The method detailed here allows to transcutaneously determine the renal function in awake animals, in a non-invasive and efficient manner by using an electronic device which detects the fluorescence emitted through the skin from the renal marker FITC-Sinistrin. A crucial target has been to improve the fixation of the device, which is dependent on the skin structure. For validation, the technique has been compared with the classical clearance method, and its robustness has been demonstrated in healthy and diseased murine models. Moreover, the method allows sequential measurements in the same individual. Thus progression and recovery of renal failure can be followed. Therefore, its future application in humans would allow an accurate and appropriate prediction and monitoring of patients with established kidney disease over time. Furthermore, it will be possible to observe those patients under other pathological conditions with associated risk of developing renal problems.
A Body Area Network (BAN) is a wireless network of wearable or implantable computing devices. A BAN typically consists of several miniaturized radio-enabled body sensor/actuator that communicate with a single coordinator. Medical applications usually impose stringent constraints on the BAN operational reliability, quality of service, and power consumption. However, as there is no coordination among multiple co-located BANs, cross-interference could make achieving these objectives a challenging problem. Assuming Time Division Multiple Access (TDMA) at each BAN, this paper investigates the ability of regret matching based transmission scheduling algorithm to ease the impact of inter-BAN interference. This scheduling algorithm uses pattern of past interference for implicit coordination between different BAN transmissions. Simulation results demonstrate potential benefits of the proposed scheme for inter-BAN interference mitigation.
Nowadays, more than 450 millions of people around the world suffer from mental disorders. One of the main problems of that type of illnesses is the lack of early detection, generally due to the reduced number of professionals specialized in mental health, especially in low- and middle-income countries. This article aims at describing the process of construction of an m-Health system that supports the collection of clinical data, including EEG signals, in order to assist the initial assessment of neurologic problems. The system has been mainly developed by using low-cost technology, implemented under the open-source platform SANA, and integrating a non-professional EEG device for the acquisition of bioelectric signals of the brain. The functionalities of this application and its usefulness have been evaluated by a group of six experts who concluded that a) the system implements 100% of the functionalities described in the system design phase, and b) the usefulness of the system's functionalities is 96%.
This article presents the development process of an acquisition and data storage system managing clinical variables through a cloud storage service and a Personal Health Record (PHR) System. First, the paper explains how a Wireless Body Area Network (WBAN) that captures data from two sensors corresponding to arterial pressure and heart rate is designed. Second, this paper illustrates how data collected by the WBAN are transmitted to a cloud storage service. It is worth mentioning that this cloud service allows the data to be stored in a persistent way on an online database system. Finally, the paper describes, how the data stored in the cloud service are sent to the Indivo PHR System, where they are registered and charted for future revision by health professionals. The research demonstrated the feasibility of implementing WBAN networks for the acquisition of clinical data, and particularly for the use of Web technologies and standards to provide interoperability with PHR Systems at technical and syntactic levels.
pHealth occurs in uncontrolled and unsecure environment where predefined organizational trust does not exist. To be accepted by users, pHealth requires a privacy model where privacy is a personal property, i.e., a person can perform own will and define policies which regulate how personal health information (PHI) is used. Privacy and trust are interconnected concepts. Therefore, before beginning to use pHealth services, the person needs practical and reliable information that enables her or him to determine the trustworthiness level of services.
To avoid the use of blind trust, organizations, researchers, policymakers, and standardization organizations have proposed the use of dynamic context-aware policies for privacy management in pHealth. To make meaningful privacy decision, a person should understand the impact of selected policy rules on the processing of PHI in different situations.
In this paper, the use of computational trust information for defining privacy polies and reducing their number is proposed. A trust value and understandable trust attributes enable a person to tailor privacy policies requested for trustworthy use of pHealth services. Trust attributes proposed are derived from privacy concerns existing in open ubiquitous environment. These attributes also force pHealth services providers to publish information needed for trust calculation and in this way to support openness and transparency.
Data from personal health devices is expected to be an important part of personalized care in future, but communication frameworks for such data create new challenges for security and privacy. Continua Health Alliance has been very active and successful in defining guidelines and a reference architecture for transmitting personal health device data based on well-known international standards. But looking at the security definitions, the concepts are still facing open issues and weaknesses like identity management or missing end-2end (E2E) encryption. This paper presents an approach for an E2E encryption framework based on Continua's reference architecture and the underlying base standards. It introduces the basic process and proposes necessary extensions to the architecture as well as to the standardized protocols of ISO/IEEE 11073 and HL7 version 2.