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In Japan, the number of elderly recipients who take medicines regularly has been increasing due to population aging. Since they have many risks of incorrect medication, we have developed the intelligent medicine case system (iMec System) for assisting their caretakers in medication monitoring. The system confirms the type, quantity and timing of medication every time a recipient picks medicines up...
The mechanical ventilator settings in patients with respiratory diseases like chronic obstructive pulmonary disease (COPD) during episodes of acute respiratory failure (ARF) is not a simple task that in most cases is successful based on the experience of physicians. This paper describes an interactive tool based in mathematical models, developed to make easier the study of the interaction between...
Disease Management (DM) is a system of coordinated healthcare intervention and communications for populations with conditions in which patient self-care efforts are significant. e-DM makes reference to processes of DM based on clinical guidelines sustained in the scientific medical evidence and supported by the intervention of Information and Telecommunication Technology (ICT) in all levels where...
The CHRONIOUS system addresses a smart wearable platform, based on multi-parametric sensor data processing, for monitoring people suffering from chronic diseases in long-stay setting. Several signals are being recorded through wearable sensors and are stored together with additional information, entered by the patient. An Intelligent System, placed at a Smart Assistant Device, analyzes incoming data...
Background: Cardiovascular disease (CVD) is the leading chronic diseases affecting developed countries. Traditional approach to secondary prevention of CVD through hospital-based cardiac rehabilitation (CR) is hampered by the lack of uptake and adherence. Objective: To address this, the Australian e-Health Research Centre and Queensland Health have developed an alternative ICT-enabled CR program to...
This paper presents a system capable of predicting in real-time the evolution of Intensive Care Unit (ICU) physiological patient data streams. It leverages a state of the art stream computing platform to host analytics capable of making such prognosis in real time. The focus is on online algorithms that do not require a training phase. We use Fading-Memory Polynomial filters on the frequency domain...
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