Abstract
This paper presents methods for the investigation and visualization of spatial, physical and physiological data acquired by wearable sensors. Several clustering methods and descriptive statistics are combined. Based on graph theory, an individual network was constructed depending on daily physiological and activity data. By using such networks, clusters and day-to-day differences can be utilized to present physiological status and activity. One possible application is the usage of these subject-specific location and activity based influences in diagnostic and therapy such as of cardiac diseases.
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