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Towards robust activity recognition for everyday life: Methods and evaluation

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3 Author(s)
Attila Reiss ; Department of Augmented Vision, German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany ; Didier Stricker ; Gustaf Hendeby

The monitoring of physical activities under realistic, everyday life conditions - thus while an individual follows his regular daily routine - is usually neglected or even completely ignored. Therefore, this paper investigates the development and evaluation of robust methods for everyday life scenarios, with focus on the task of aerobic activity recognition. Two important aspects of robustness are investigated: dealing with various (unknown) other activities and subject independency. Methods to handle these issues are proposed and compared, a thorough evaluation simulates usual everyday scenarios of the usage of activity recognition applications. Moreover, a new evaluation technique is introduced (leave-one-other-activity-out) to simulate when an activity recognition system is used while performing a previously unknown activity. Through applying the proposed methods it is possible to design a robust physical activity recognition system with the desired generalization characteristic.

Published in:

2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops

Date of Conference:

5-8 May 2013