Affiliation:
1. Federation University, Australia
Abstract
Remote patient monitoring involves the collection of data from wearable sensors that typically requires analysis in real time. The real-time analysis of data streaming continuously to a server challenges data mining algorithms that have mostly been developed for static data residing in central repositories. Remote patient monitoring also generates huge data sets that present storage and management problems. Although virtual records of every health event throughout an individual's lifespan known as the electronic health record are rapidly emerging, few electronic records accommodate data from continuous remote patient monitoring. These factors combine to make data analytics with continuous patient data very challenging. In this chapter, benefits for data analytics inherent in the use of standards for clinical concepts for remote patient monitoring is presented. The openEHR standard that describes the way in which concepts are used in clinical practice is well suited to be adopted as the standard required to record meta-data about remote monitoring. The claim is advanced that this is likely to facilitate meaningful real time analyses with big remote patient monitoring data. The point is made by drawing on a case study involving the transmission of patient vital sign data collected from wearable sensors in an Indian hospital.
Reference44 articles.
1. Real time processing of data from patient biodevices.;R.Abadia;Proceedings of the Fourth Australasian Workshop on Health Informatics and Knowledge Management-Volume 120,2011
2. ECG Reduction for Wearable Sensor
3. A count data model for heart rate variability forecasting and premature ventricular contraction detection.;R.Allami;Signal, Image and Video Processing,2017
4. SOAP based Assistive Care Loop using wireless sensor networks