DocumentCode :
2445496
Title :
Estimating Personal Energy expenditure with location data
Author :
Hay, Simon ; Rassia, Stamatina Th ; Beresford, Alastair R.
Author_Institution :
Comput. Lab., Univ. of Cambridge, Cambridge, UK
fYear :
2010
fDate :
March 29 2010-April 2 2010
Firstpage :
304
Lastpage :
309
Abstract :
Human inactivity has been associated with the incidence of a number of health conditions and chronic diseases, while our increasing energy consumption is a well-documented problem. A Personal Energy Meter might help identify areas for improvement in our lifestyles that would benefit both our personal health and the global environment. As one strand of this, we explore the possibility of estimating our own energy expenditure from movement traces provided by location systems. This technique offers a number of advantages over accepted accelerometer-based devices.We validate a model which we then apply to analyse the physical activity and working patterns of a total of 60 individuals spread across two separate offices.
Keywords :
accelerometers; diseases; health care; accelerometer-based devices; chronic diseases; energy consumption; health conditions; human inactivity; location data; movement traces; personal energy expenditure estimation; personal energy meter; personal health; physical activity; working patterns; Biomedical measurements; Diseases; Energy measurement; Extraterrestrial measurements; Humans; Laboratories; Medical services; Monitoring; Pervasive computing; Watthour meters; biomedical measurements; energy measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Communications Workshops (PERCOM Workshops), 2010 8th IEEE International Conference on
Conference_Location :
Mannheim
Print_ISBN :
978-1-4244-6605-4
Electronic_ISBN :
978-1-4244-6606-1
Type :
conf
DOI :
10.1109/PERCOMW.2010.5470650
Filename :
5470650
Link To Document :
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