Power transmission and workload balancing policies in eHealth mobile cloud computing scenarios

The Internet of Things (IoT) holds big promises for healthcare, especially in proactive personal eHealth. Prediction of symptomatic crises in chronic diseases in the IoT scenario leads to the deployment of ambulatory monitoring systems. These systems place a major concern in the amount of data to be processed and the intelligent management of the energy consumption. The huge amount of data generated for these systems require high computing capabilities only available in Data Centers. This paper presents a real case of prediction in the eHealth scenario, devoted to neurological disorders. The presented case study focuses on the migraine headache, a disease that affects around 15% of the European population. This paper extrapolates results from real data and simulations in a study where migraine patients are monitored using an unobtrusive Wireless Body Sensor Network. Low-power techniques are applied in monitorization nodes. Techniques such us: on-node signal processing and radio policies to make node’s autonomy longer and save energy, have been applied. Workload balancing policies are carried out in the coordinator nodes and Data Centers to reduce the computational burden in these facilities and minimize its energy consumption. Our results draw average savings of € 288 million in this eHealth scenario applied only to 2% of European migraine sufferers; in addition to savings of € 1272 million due to the benefits of the migraine prediction

Power transmission and workload balancing policies in eHealth mobile cloud computing scenarios

The Internet of Things (IoT) holds big promises for healthcare, especially in proactive personal eHealth. Prediction of symptomatic crises in chronic diseases in the IoT scenario leads to the deployment of ambulatory monitoring systems. These systems place a major concern in the amount of data to be processed and the intelligent management of the energy consumption. The huge amount of data generated for these systems require high computing capabilities only available in Data Centers. This paper presents a real case of prediction in the eHealth scenario, devoted to neurological disorders. The presented case study focuses on the migraine headache, a disease that affects around 15% of the European population. This paper extrapolates results from real data and simulations in a study where migraine patients are monitored using an unobtrusive Wireless Body Sensor Network. Low-power techniques are applied in monitorization nodes. Techniques such us: on-node signal processing and radio policies to make node’s autonomy longer and save energy, have been applied. Workload balancing policies are carried out in the coordinator nodes and Data Centers to reduce the computational burden in these facilities and minimize its energy consumption. Our results draw average savings of € 288 million in this eHealth scenario applied only to 2% of European migraine sufferers; in addition to savings of € 1272 million due to the benefits of the migraine prediction.Ministerio de Economía, Comercio y Empresa (España)Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEpu

Dynamics of Technology Acceptance to the Sustainability of eHealth Systems in Resource Constrained Environments

Healthcare in developing countries is confronted with a shortage of skilled healthcare workforce, medical errors, inequity and inefficient healthcare service delivery. Innovative ways of solving healthcare problems through Information and communication technology (ICT) can improve the efficiency, effectiveness, access and quality of the healthcare system. Despite highly anticipated benefits of eHealth system to improve the efficiency of healthcare delivery, the healthcare had barely begun to take advantage of ICT mainly in a resource-constrained environment. The implementation of eHealth systems in developing countries could not proceed beyond the pilot phase to demonstrate sustainability in a large-scale rollout. The general research problem in this thesis focuses on how factors of eHealth implementation interplay to influence technology and information use to ensure the long-term sustainability of eHealth in resource-constrained settings. Systems thinking and system dynamics modelling method were used to handle complexity in the implementation of eHealth. Moreover, sustainability theory, technology acceptance model (TAM) and IS success models were used to develop a system dynamics model of sustainable eHealth implementation. The socio-technical, techno-organizational and techno-economic factors of sustainable eHealth systems are discussed to address the research objectives. The system dynamics simulation model of sustainable eHealth implementation is developed, verified, validated and tested. This applied research study focused on addressing the problems of sustainable eHealth systems implementation in resource-constrained environments. The model-based theory-building research study followed in this thesis aimed at enhancing the understanding of sustainable eHealth implementation in a resource-constrained environment to maximize the acceptance of eHealth by the end-users. Both the ontological and epistemological assumptions of this research study supported the position of the constructivist research paradigm. Methodologically, this study mainly applies qualitative research methodology which is common in the interpretive approach. Structured and semi-structured questionnaires were used to elicit information from purposefully sampled eHMIS and SmartCare health facilities in Ethiopia. Field notes, document review, interview and focus group discussion data were analysed using ATLAS.ti software. Vensim DSS Version 6.3D was used to model and simulate the system dynamics model. Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) approach was followed in the systematic literature review of techno-economic factors. The simulation results confirmed that the ‘effectiveness of training’ was a dominant factor to improve the ‘acceptance rate’ of eHMIS and SmartCare in the socio-technical dimension of sustainable eHealth implementation. The adequacy of ICT and healthcare workforce within eHealth implementing facility and end-users’ familiarity with digital technology showed a stronger influence on the ‘acceptance rate’ of both eHMIS and SmartCare systems in the techno-organizational dimension. An economic incentive, funding duration, funding amount, funding source and economic benefit are identified as techno-economic factors that influence the long-term sustainability of eHealth projects.Thesis (PhD)--University of Pretoria, 2019.Graduate School of Technology Management (GSTM)PhDUnrestricte