The OCarePlatform : a context-aware system to support independent living

Background: Currently, healthcare services, such as institutional care facilities, are burdened with an increasing number of elderly people and individuals with chronic illnesses and a decreasing number of competent caregivers. Objectives: To relieve the burden on healthcare services, independent living at home could be facilitated, by offering individuals and their (in)formal caregivers support in their daily care and needs. With the rise of pervasive healthcare, new information technology solutions can assist elderly people ("residents") and their caregivers to allow residents to live independently for as long as possible. Methods: To this end, the OCarePlatform system was designed. This semantic, data-driven and cloud based back-end system facilitates independent living by offering information and knowledge-based services to the resident and his/her (in)formal caregivers. Data and context information are gathered to realize context-aware and personalized services and to support residents in meeting their daily needs. This body of data, originating from heterogeneous data and information sources, is sent to personalized services, where is fused, thus creating an overview of the resident's current situation. Results: The architecture of the OCarePlatform is proposed, which is based on a service-oriented approach, together with its different components and their interactions. The implementation details are presented, together with a running example. A scalability and performance study of the OCarePlatform was performed. The results indicate that the OCarePlatform is able to support a realistic working environment and respond to a trigger in less than 5 seconds. The system is highly dependent on the allocated memory. Conclusion: The data-driven character of the OCarePlatform facilitates easy plug-in of new functionality, enabling the design of personalized, context-aware services. The OCarePlatform leads to better support for elderly people and individuals with chronic illnesses, who live independently. (C) 2016 Elsevier Ireland Ltd. All rights reserved

An eHealth Intervention for Patients in Rural Areas: Preliminary Findings From a Pilot Feasibility Study

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.Background: eHealth facilitation of chronic disease management has potential to increase engagement and effectiveness and extend access to care in rural areas. Objective: The objective of this study was to demonstrate the feasibility and acceptability of an eHealth system for the management of chronic conditions in a rural setting. Methods: We developed an online management program which incorporated content from the Flinders Chronic Condition Management Program (Flinders Program) and used an existing software platform (goACT), which is accessible by patients and health care workers using either Web-enabled mobile phone or Internet, enabling communication between patients and clinicians. We analyzed the impact of this eHealth system using qualitative and simple quantitative methods. Results: The eHealth system was piloted with 8 recently hospitalized patients from rural areas, average age 63 (SD 9) years, each with an average of 5 chronic conditions and high level of psychological distress with an average K10 score of 32.20 (SD 5.81). Study participants interacted with the eHealth system. The average number of logins to the eHealth system by the study participants was 26.4 (SD 23.5) over 29 weeks. The login activity was higher early in the week. Conclusions: The pilot demonstrated the feasibility of implementing and delivering a chronic disease management program using a Web-based patient-clinician application. A qualitative analysis revealed burden of illness and low levels of information technology literacy as barriers to patient engagement

Detecting Falls with Wearable Sensors Using Machine Learning Techniques

Cataloged from PDF version of article.Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and magnetometer/compass). Fourteen volunteers perform a standardized set of movements including 20 voluntary falls and 16 activities of daily living (ADLs), resulting in a large dataset with 2520 trials. To reduce the computational complexity of training and testing the classifiers, we focus on the raw data for each sensor in a 4 s time window around the point of peak total acceleration of the waist sensor, and then perform feature extraction and reduction. Most earlier studies on fall detection employ rule-based approaches that rely on simple thresholding of the sensor outputs. We successfully distinguish falls from ADLs using six machine learning techniques (classifiers): the k-nearest neighbor (k-NN) classifier, least squares method (LSM), support vector machines (SVM), Bayesian decision making (BDM), dynamic time warping (DTW), and artificial neural networks (ANNs). We compare the performance and the computational complexity of the classifiers and achieve the best results with the k-NN classifier and LSM, with sensitivity, specificity, and accuracy all above 99%. These classifiers also have acceptable computational requirements for training and testing. Our approach would be applicable in real-world scenarios where data records of indeterminate length, containing multiple activities in sequence, are recorded

Privacy protection for telecare medicine information systems using a chaotic map-based three-factor authenticated key agreement scheme

Telecare Medicine Information Systems (TMIS) provides flexible and convenient e-health care. However the medical records transmitted in TMIS are exposed to unsecured public networks, so TMIS are more vulnerable to various types of security threats and attacks. To provide privacy protection for TMIS, a secure and efficient authenticated key agreement scheme is urgently needed to protect the sensitive medical data. Recently, Mishra et al. proposed a biometrics-based authenticated key agreement scheme for TMIS by using hash function and nonce, they claimed that their scheme could eliminate the security weaknesses of Yan et al.’s scheme and provide dynamic identity protection and user anonymity. In this paper, however, we demonstrate that Mishra et al.’s scheme suffers from replay attacks, man-in-the-middle attacks and fails to provide perfect forward secrecy. To overcome the weaknesses of Mishra et al.’s scheme, we then propose a three-factor authenticated key agreement scheme to enable the patient enjoy the remote healthcare services via TMIS with privacy protection. The chaotic map-based cryptography is employed in the proposed scheme to achieve a delicate balance of security and performance. Security analysis demonstrates that the proposed scheme resists various attacks and provides several attractive security properties. Performance evaluation shows that the proposed scheme increases efficiency in comparison with other related schemes

Technische Systeme im Pflege- und Versorgungsmix für ältere Menschen: Expertise zum Siebten Altenbericht der Bundesregierung

Technische Assistenzsysteme können körperbezogen oder raumbezogen (z.B. in der Wohnung) gesundheitsrelevante Daten bei älteren Menschen aufnehmen, analysieren und gegebenenfalls weiterleiten. Ihre Aufgaben umfassen unter anderem die Alarmierung und Notfallidentifikation sowie die Unterstützung bei Erkrankungen und Funktionsdefiziten. Sie werden auch für nicht mit der Gesund-heitsversorgung in Zusammenhang stehende Zwecke verwendet. Bei der Entwicklung altersgerechter technischer Assistenzsysteme gab es erhebliche Fortschritte. Es ist zu erwarten, dass diese zu neuen Lebensweisen und neuen Versorgungsformen führen und dass sich das persönliche Umfeld einer Person (und hier insbesondere die Wohnung) zum neuen, zusätzlichen Gesundheitsstandort entwickeln wird. Es ist weiterhin zu erwarten, dass durch die Nutzung solcher Systeme neue diagnostische und therapeutische Verfahren entwickelt werden können, die verbesserte Möglichkeiten der Pflege als auch der ärztlichen Versorgung erwarten lassen und die zu einer längeren selbstständigen Lebensführung beitragen können. Neue Herausforderungen ergeben sich im Datenschutz, bei der informationellen Selbstbestimmung und bei der Finanzierung. Auch bei der Nutzung technischer Assistenzsysteme geht es darum, zu einer möglichst langen selbstständigen Lebensführung und zu einem aktiven Altern in Selbst- und Mitverantwortung beizutragen. Ob und inwieweit dies der Fall ist, muss weiter belegt werden. Hierzu sind nach wissenschaftlichen Standards geplante Studien notwendig, welche Aspekte wie diagnostische Relevanz und therapeutische Wirksamkeit sowie Lebensqualität untersuchen

Wearable Devices in Health Monitoring from the Environmental towards Multiple Domains: A Survey

The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and the Internet of medical things (IoMT), wearables are most important for continuous health monitoring. In this work, we analyze wearables in healthcare from a perspective of innovation by categorizing them according to the four domains. Furthermore, we consider the mode of wearability, costs, and prolonged monitoring. We identify features and investigate the wearable devices in the terms of sampling rate, resolution, data usage (propagation), and data transmission. We also investigate applications of wearable devices. Web of Science, Scopus, PubMed, IEEE Xplore, and ACM Library delivered wearables that we require to monitor at least one environmental parameter, e.g., a pollutant. According to the number of domains, from which the wearables record data, we identify groups: G1, environmental parameters only; G2, environmental and behavioral parameters; G3, environmental, behavioral, and physiological parameters; and G4 parameters from all domains. In total, we included 53 devices of which 35, 9, 9, and 0 belong to G1, G2, G3, and G4, respectively. Furthermore, 32, 11, 7, and 5 wearables are applied in general health and well-being monitoring, specific diagnostics, disease management, and non-medical. We further propose customized and quantified output for future wearables from both, the perspectives of users, as well as physicians. Our study shows a shift of wearable devices towards disease management and particular applications. It also indicates the significant role of wearables in proactive healthcare, having capability of creating big data and linking to external healthcare systems for real-time monitoring and care delivery at the point of perception

What are the likely changes in society and technology which will impact upon the ability of older adults to maintain social (extra-familial) networks of support now, in 2025 and in 2040?

This report reviews evidence on how changes in information and communication technology might affect the ability of older people to maintain social networks of support. It considers both traditional and new forms of social media, along with technological advances in support such as robotics and telecare

Emerging Trends in Family Caregiving Using the Life Course Perspective: Preparing Health Educators for an Aging Society

Background: As life expectancy and morbidity related to chronic disease increase, the baby boomers will be called upon to provide care to aging members of their family or to be care recipients themselves. Purpose: Through the theoretical lens of the life course perspective, this review of the literature provides insight into what characteristics of baby boomers separate them from previous caregiving cohorts and how these characteristics will affect family caregiving. Methods: A systematic process to identify literature was completed using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Results: Findings suggest multiple emerging trends related to caregiving, including (1) increasing use of digital technology for information gathering and support, (2) more diversity among caregivers and care recipients, (3) strained finances and loss of entitlements, (4) more complex care and care management, (5) demand for public policies related to caregiving, and (6) balancing work, family, chronic disease, and caregiving. Discussion: Examining the literature related to family caregiving and baby boomers through a life course perspective offers a unique and more complete understanding of emerging trends related to chronic disease management. Translation to Health Education Practice: These emerging trends offer health educators implications for strategies and best practices intended to support those involved in family caregiving