Analysis of home health sensor data

B.J.A. Kröse

Analysis of home health sensor data

Digital life

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

This chapter focuses on the analysis of data that is collected from sensors in the home environment. First we discuss the need for a good model that relates sensor data (or features derived from the data) to indicators of health and well-being. Then we present several methods for model building. We distinguish between supervised methods that need data annotated with the desired health indicators, unsupervised methods that find characteristic patterns by just analyzing large amounts of data, and knowledge-driven methods that use expert knowledge. We discuss the advantages and disadvantages of the different methods.

Original language	English
Title of host publication	Handbook of smart homes, health care and well-being
Editors	Joost van Hoof, George Demiris, Eveline J.M. Wouters
Place of Publication	Switzerland
Publisher	Springer International Publishing
Pages	302-313
Number of pages	11
ISBN (Print)	978-3-319-01904-8
Publication status	Published - 2015

Access to Document

https://link.springer.com/content/pdf/10.1007/978-3-319-01583-5.pdf#page=296

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A2 - Wouters, Eveline J.M.

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