articleJul 9, 2005Closed access

Activity recognition from accelerometer data

Rutgers, The State University of New Jersey

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 classifica-tion problem. Performance of base-level classifiers and meta-level classifiers is compared. Plurality Voting is found to perform consistently well across different set-tings.

Citation impact

1,372
total citations
FWCI
14.65
Percentile
100%
References
19
Citations per year

Authors

4

Topics & keywords

Keywords
  • Activity recognition
  • Accelerometer
  • Computer science
  • Context (archaeology)
  • Voting
  • Machine learning
  • Artificial intelligence
  • Pattern recognition (psychology)
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