Accelerometer vs. Electromyogram in Activity Recognition
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 ac…
Autorius
- Koskimaki, Heli
- Siirtola, Pekka
Leidėjas
- Ediciones Universidad de Salamanca (EspaÑa)
Tema
- Computación
- Informótica
- Computing
- Information Technology
- Computing
Skaitmeninis objektas tipas
- ArtÍculo
- Article
Data
- 2017-01-09T12:03:42Z
- 2017-01-09T12:03:42Z
- 2016-11-15
- 2016-11-15
- 2017-01-09
- 2017-01-09
Autorius
- Koskimaki, Heli
- Siirtola, Pekka
Leidėjas
- Ediciones Universidad de Salamanca (EspaÑa)
Tema
- Computación
- Informótica
- Computing
- Information Technology
- Computing
Skaitmeninis objektas tipas
- ArtÍculo
- Article
Data
- 2017-01-09T12:03:42Z
- 2017-01-09T12:03:42Z
- 2016-11-15
- 2016-11-15
- 2017-01-09
- 2017-01-09
Agregatorius
Šiame Skaitmeninis objektas esančios teisių pareikštys (jei nenurodyta kitaip)
- http://creativecommons.org/licenses/by-nc-nd/4.0/
Teisės
- info:eu-repo/semantics/openAccess
Sukūrimo data
- 2017-01-09T12:03:42Z
- 2017-01-09
Identifikatorius
- oai:gredos.usal.es:10366/132090
- ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 5 (2016)
- 2255-2863
- http://hdl.handle.net/10366/132090
Formatas
- application/pdf
Kalba
- eng
Teikianti šalis
- Spain
Kolekcijos pavadinimas
Pirmą kartą paskelbta Europeana
- 2017-07-07T14:05:34.056Z
Paskutinį kartą atnaujinta iš teikėjas
- 2017-07-07T14:05:34.056Z