Human movement activity classification approaches that use wearable sensors and mobile devices

Sahak Kaghyan; Hakob Sarukhanyan; David Akopian

doi:10.1117/12.2007868

7 March 2013 Human movement activity classification approaches that use wearable sensors and mobile devices

Sahak Kaghyan, Hakob Sarukhanyan, David Akopian

Proceedings Volume 8667, Multimedia Content and Mobile Devices; 86670O (2013) https://doi.org/10.1117/12.2007868
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

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.

Citation Download Citation

Sahak Kaghyan, Hakob Sarukhanyan, and 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

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