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Titolo
Accelerometer vs. Electromyogram in Activity Recognition
Autor(es)
Soggetto
Computación
Informótica
Computing
Information Technology
Fecha de publicación
2016-11-15
Editore
Ediciones Universidad de Salamanca (EspaÑa)
Citación
ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 5 (2016)
Resumen
In this study, information from wearable sensors is used to recognize human activities. Commonly the approaches are based on accelerometer data while in this study the potential of electromyogram (EMG) signals in activity recognition is studied. The electromyogram data is used in two different scenarios: 1) recognition of completely new activities in real life and 2) to recognize the individual activities. In this study, it was shown that in gym settings electromyogram signals clearly outperforms the accelerometer data in recognition of completely new sets of gym movements from streaming data even though the sensors would not be positioned directly to the muscles trained. Nevertheless, in recognition of individual activities the EMG itself does not provide enough information to recognize activities accurately.
URI
ISSN
2255-2863
Aparece en las colecciones
- ADCAIJ, Vol.5, n.3 [10]