Logic-centred architecture for ubiquitous health monitoring

One of the key points to maintain and boost research and development in the area of smart wearable systems (SWS) is the development of integrated architectures for intelligent services, as well as wearable systems and devices for health and wellness management. This paper presents such a generic architecture for\ud multiparametric, intelligent and ubiquitous wireless sensing platforms. It is a transparent, smartphone-based sensing framework\ud with customizable wireless interfaces and plug‘n’play capability to easily interconnect third party sensor devices. It caters to wireless\ud body, personal, and near-me area networks. A pivotal part of the platform is the integrated inference engine/runtime environment\ud that allows the mobile device to serve as a user-adaptable personal health assistant. The novelty of this system lays in a rapid visual\ud development and remote deployment model. The complementary visual InferenceEngineEditor that comes with the package enables\ud artificial intelligence specialists, alongside with medical experts, to build data processing models by assembling different components\ud and instantly deploying them (remotely) on patient mobile devices. In this paper, the new logic-centered software architecture for ubiquitous health monitoring applications is described, followed by a\ud discussion as to how it helps to shift focus from software and hardware development, to medical and health process-centered design of new SWS applications

Towards Evidence Based M-Health Application Design in Cancer Patient Healthy Lifestyle Interventions

Cancer is one of the most prevalent diseases in Europe and the world. Significant correlations between dietary habits and cancer incidence and mortality have been confirmed by the literature. Physical activity habits are also directly implicated in the incidence of cancer. Lifestyle behaviour change may be benefited by using mobile technology to deliver health behaviour interventions. M-Health offers a promising cost-efficient approach to deliver en-masse interventions. Smartphone apps with constructs such as gamification and personalized have shown potential for helping individuals lose weight and maintain healthy lifestyle habits. However, evidence-based content and theory-based strategies have not been incorporated by those apps systematically yet. The aim of the current work is to put the foundations for a methodologically rigorous exploration of wellness/health intervention literature/app landscape towards detailed design specifications for connected health m-apps. In this context, both the overall work plan is described as well as the details for the significant steps of application space and literature space review. Both strategies for research and initial outcomes of it are presented. The expected evidence based design process for patient centered health and wellness interventions is going to be the primary input in the implementation process of upcoming patient centered health/wellness m-health interventions.ENJECT COST-STSM-ECOST-STSM-TD1405-220216-07045

Healthcare Robotics

Robots have the potential to be a game changer in healthcare: improving health and well-being, filling care gaps, supporting care givers, and aiding health care workers. However, before robots are able to be widely deployed, it is crucial that both the research and industrial communities work together to establish a strong evidence-base for healthcare robotics, and surmount likely adoption barriers. This article presents a broad contextualization of robots in healthcare by identifying key stakeholders, care settings, and tasks; reviewing recent advances in healthcare robotics; and outlining major challenges and opportunities to their adoption.Comment: 8 pages, Communications of the ACM, 201

Trends in Patient Generated Data – An Initial Review

In recent years, patient-centered care has gained significant momentum in healthcare and the patient is more involved as an active participant in data generation. In this state of the art review we identify trends in patient generated data (PGD) and areas in need of further research by reviewing papers published in the health tracks of five high-ranked IS conferences. Our results suggest that research is mostly empirically grounded and primarily focuses on sickness rather than wellness issues. There is an emphasis on chronic diseases and self-management, dealing with user motivation, and a focus mostly on mobile apps. Though technology plays an important part, there is scarce problematization of and theorization on PGD. Further studies are needed that investigate the effects of PGD on patients and healthcare providers, include a wider range of issues and incorporate wearable devices more comprehensively

ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-time Constraints

Remote health monitoring is becoming indispensable, though, Internet of Things (IoTs)-based solutions have many implementation challenges, including energy consumption at the sensing node, and delay and instability due to cloud computing. Compressive sensing (CS) has been explored as a method to extend the battery lifetime of medical wearable devices. However, it is usually associated with computational complexity at the decoding end, increasing the latency of the system. Meanwhile, mobile processors are becoming computationally stronger and more efficient. Heterogeneous multicore platforms (HMPs) offer a local processing solution that can alleviate the limitations of remote signal processing. This paper demonstrates the real-time performance of compressed ECG reconstruction on ARM's big.LITTLE HMP and the advantages they provide as the primary processing unit of the IoT architecture. It also investigates the efficacy of CS in minimizing power consumption of a wearable device under real-time and hardware constraints. Results show that both the orthogonal matching pursuit and subspace pursuit reconstruction algorithms can be executed on the platform in real time and yield optimum performance on a single A15 core at minimum frequency. The CS extends the battery life of wearable medical devices up to 15.4% considering ECGs suitable for wellness applications and up to 6.6% for clinical grade ECGs. Energy consumption at the gateway is largely due to an active internet connection; hence, processing the signals locally both mitigates system's latency and improves gateway's battery life. Many remote health solutions can benefit from an architecture centered around the use of HMPs, a step toward better remote health monitoring systems.Peer reviewedFinal Published versio

Holistic System Design for Distributed National eHealth Services

publishedVersio

Towards a Holistic Approach to Designing Theory-based Mobile Health Interventions

Increasing evidence has shown that theory-based health behavior change interventions are more effective than non-theory-based ones. However, only a few segments of relevant studies were theory-based, especially the studies conducted by non-psychology researchers. On the other hand, many mobile health interventions, even those based on the behavioral theories, may still fail in the absence of a user-centered design process. The gap between behavioral theories and user-centered design increases the difficulty of designing and implementing mobile health interventions. To bridge this gap, we propose a holistic approach to designing theory-based mobile health interventions built on the existing theories and frameworks of three categories: (1) behavioral theories (e.g., the Social Cognitive Theory, the Theory of Planned Behavior, and the Health Action Process Approach), (2) the technological models and frameworks (e.g., the Behavior Change Techniques, the Persuasive System Design and Behavior Change Support System, and the Just-in-Time Adaptive Interventions), and (3) the user-centered systematic approaches (e.g., the CeHRes Roadmap, the Wendel's Approach, and the IDEAS Model). This holistic approach provides researchers a lens to see the whole picture for developing mobile health interventions