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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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