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Accelerometer-based Human Activity Recognition and the Impact of the Sample Size

Abstract

The presented study focused on the recognition of eight user activities (e.g. walking, lying, climbing stairs) basing on the measurements from an accelerometer embedded in a mobile device. It is assumed that the device is carried in a specific location of the user’s clothing. Three types of classifiers were tested on different sizes of the samples. The influence of the time window (the duration of a single trial) on selected activities and methods was investigated. A comparison with existing methods from the literature is presented.

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Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:
Advances in Neural Networks, Fuzzy Systems and Artificial Intelligence strony 130 - 135
Language:
English
Publication year:
2014
Bibliographic description:
Harasimowicz A., Dziubich T., Brzeski A.: Accelerometer-based Human Activity Recognition and the Impact of the Sample Size// Advances in Neural Networks, Fuzzy Systems and Artificial Intelligence/ ed. Jerzy Balicki : WSEAS Press, 2014, s.130-135
Verified by:
Gdańsk University of Technology

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