Joanna Fursse

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This study presents a novel dynamic threshold algorithm that is applied to daily self-measured SpO2 data for management of chronic obstructive pulmonary disease (COPD) patients in remote patient monitoring to improve accuracy of detection of exacerbation. Conventional approaches based on a fixed threshold applied to a single SpO 2 reading to detect(More)
IntroductIon We will begin with data from the Medical Expenditure Panel Survey and use it throughout the text. This dataset has been provided since 1996 and contains yearly information concerning every interaction with the healthcare profession for a cohort of approximately 30,000 patients and 11,000 households. Each household is included in the survey for(More)
BACKGROUND Changes in daily habits can provide important information regarding the overall health status of an individual. This research aimed to determine how meaningful information may be extracted from limited sensor data and transformed to provide clear visualization for the clinicians who must use and interact with the data and make judgments on the(More)
We present experience of implementing and evaluating a platform purpose designed to integrate interoperable telehealth and telecare. We chose the IEEE 11073 standards for all devices and used ZigBee wireless to support many devices concurrently and exploit its mesh networking to extend range around the entire house. We designed the home gateway to be(More)
We describe our experiences of using remote patient monitoring to support the long term management and clinical intervention in patients with chronic disease. Within the project we developed new algorithms to determine from vital signs collected on a daily basis, those patients requiring clinical investigation for their condition. Our aim was for patients(More)
An automated personalised intervention algorithm was developed to determine when and if patients with chronic disease in a remote monitoring programme required intervention for management of their condition. The effectiveness of the algorithm has so far been evaluated on 29 patients. It was found to be particularly effective in monitoring newly diagnosed(More)
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