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Abstract
Remote patient monitoring (RPM) involves the collection of data from wearable sensors that typically requires analysis in real time. The real time analysis of data continuously streaming challenges data mining algorithms that have been developed for static data residing in central repositories. RPM also generates huge data sets that present storage challenges. These factors combine to make data analytics with continuous patient data challenging however, the careful design of RPM systems can lead to health care improvements. This is illustrated by drawing on a case study involving the real time analysis of patient vital sign data to detect deterioration in Indian hospitals.