Activity recognition from accelerometer data

Authors:
Nishkam Ravi;Nikhil Dandekar;Preetham Mysore;Michael L. Littman
Affiliations:
Department of Computer Science, Rutgers University, Piscataway, NJ;Department of Computer Science, Rutgers University, Piscataway, NJ;Department of Computer Science, Rutgers University, Piscataway, NJ;Department of Computer Science, Rutgers University, Piscataway, NJ
Venue:
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
Year:
2005

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Abstract

Activity recognition fits within the bigger framework of context awareness. In this paper, we report on our efforts to recognize user activity from accelerometer data. Activity recognition is formulated as a classification problem. Performance of base-level classifiers and meta-level classifiers is compared. Plurality Voting is found to perform consistently well across different settings.