EcoSta 2018: Registration
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Title: Monitoring data quality in a personalized health tracking system Authors:  Inez Zwetsloot - City University of Hong Kong (Hong Kong) [presenting]
Abstract: Rapid advances in information and sensor technology have led to the development of tools and methods for individual health monitoring. These techniques support elderly health management by tracking vital signs and detecting physiological changes. We develop a data quality monitoring system to ensure that the collected data is accurate. We consider data from an all-in-one station-based health monitoring device that collects daily vital signs of elderly in an elderly home in Hong Kong. Due to the nature of the data both the sample sizes as well as the number of measured variables changes over time. We develop a new control chart to monitor the data quality. This new method has the ability to monitor data with varying sample sizes and varying number of parameters effectively. We illustrate the new method using the data on vital signs of the participants.