Abstract
This paper explores automated activity recognition using a WIreless Sensor nEtwork (WISE) connected via Bluetooth to a smartphone. Automated activity recognition enables patients, such as diabetics, to keep more accurate logs of their activities (intensity and duration of the activity) and so to prevent short-terms complication, such as hypoglycaemias. We developed a platform records motion using two wearable sensory devices equipped with 3-axis accelerometers, worn on the waist and the shank, and a wireless heart rate monitor. Data are transmitted via Bluetooth to a smartphone, annotated and analyzed to recognize user activity. WISE platform architecture is described along with recognition accuracy performed by multiple classifiers.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Kouris, I., Koutsouris, D. (2012). Activity Recognition Using Smartphones and Wearable Wireless Body Sensor Networks. In: Nikita, K.S., Lin, J.C., Fotiadis, D.I., Arredondo Waldmeyer, MT. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 83. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29734-2_5
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DOI: https://doi.org/10.1007/978-3-642-29734-2_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29733-5
Online ISBN: 978-3-642-29734-2
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