title: Application of data fusion techniques and technologies for wearable health monitoring.
abstract: Technological advances in sensors and communications have enabled discrete integration into everyday objects, both in the home and about the person. Information gathered by monitoring physiological, behavioural, and social aspects of our lives, can be used to achieve a positive impact on quality of life, health, and well-being. Wearable sensors are at the cusp of becoming truly pervasive, and could be woven into the clothes and accessories that we wear such that they become ubiquitous and transparent. To interpret the complex multidimensional information provided by these sensors, data fusion techniques are employed to provide a meaningful representation of the sensor outputs. This paper is intended to provide a short overview of data fusion techniques and algorithms that can be used to interpret wearable sensor data in the context of health monitoring applications. The application of these techniques are then described in the context of healthcare including activity and ambulatory monitoring, gait analysis, fall detection, and biometric monitoring. A snap-shot of current commercially available sensors is also provided, focusing on their sensing capability, and a commentary on the gaps that need to be bridged to bring research to market.
authors.affiliation: School of Biological Sciences, Biomedical Engineering, University of Reading, Reading, United Kingdom. Electronic address: rachel.king@reading.ac.uk.
authors.forename: Rachel C
authors.initials: RC
authors.lastname: King
authors.affiliation: University of Exeter, Medical School, Exeter, United Kingdom. Electronic address: e.villeneuve@exeter.ac.uk.
authors.forename: Emma
authors.initials: E
authors.lastname: Villeneuve
authors.affiliation: School of Biological Sciences, Biomedical Engineering, University of Reading, Reading, United Kingdom. Electronic address: r.j.white@pgr.reading.ac.uk.
authors.forename: Ruth J
authors.initials: RJ
authors.lastname: White
authors.affiliation: School of Biological Sciences, Biomedical Engineering, University of Reading, Reading, United Kingdom. Electronic address: sherratt@ieee.org.
authors.forename: R Simon
authors.initials: RS
authors.lastname: Sherratt
authors.affiliation: School of Biological Sciences, Biomedical Engineering, University of Reading, Reading, United Kingdom. Electronic address: w.holderbaum@reading.ac.uk.
authors.forename: William
authors.initials: W
authors.lastname: Holderbaum
authors.affiliation: School of Biological Sciences, Biomedical Engineering, University of Reading, Reading, United Kingdom. Electronic address: w.s.harwin@reading.ac.uk.
authors.forename: William S
authors.initials: WS
authors.lastname: Harwin
mesh_terms: D000465:Algorithms; D006801:Humans; D008991:Monitoring, Physiologic / Q000295:instrumentation / Q000379:methods*; D013223:Statistics as Topic / Q000379:methods*; D000076251:Wearable Electronic Devices
keywords: Data fusion; Health monitoring; Sensors; Wearable technology