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7 March 2013Human movement activity classification approaches that use wearable sensors and mobile devices
Sahak Kaghyan,1 Hakob Sarukhanyan,2 David Akopian3
1Armenian-Russian (Slavonic) Univ. (Armenia) 2Institute for Informatics and Automation Problems (Armenia) 3The Univ. of Texas at San Antonio (United States)
Cell phones and other mobile devices become part of human culture and change activity and lifestyle patterns. Mobile
phone technology continuously evolves and incorporates more and more sensors for enabling advanced applications.
Latest generations of smart phones incorporate GPS and WLAN location finding modules, vision cameras, microphones,
accelerometers, temperature sensors etc. The availability of these sensors in mass-market communication devices creates
exciting new opportunities for data mining applications. Particularly healthcare applications exploiting build-in sensors
are very promising. This paper reviews different approaches of human activity recognition.
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Sahak Kaghyan, Hakob Sarukhanyan, David Akopian, "Human movement activity classification approaches that use wearable sensors and mobile devices," Proc. SPIE 8667, Multimedia Content and Mobile Devices, 86670O (7 March 2013); https://doi.org/10.1117/12.2007868