Ponencia
Hi-Res activity recognition system based on EEG and WoT
Autor/es | Soria Morillo, Luis Miguel
Álvarez, M.A. Ortega Ramírez, Juan Antonio Vergara, R. |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2013 |
Fecha de depósito | 2022-03-15 |
Publicado en |
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ISBN/ISSN | 978-84-697-0147-8 |
Resumen | Nowadays, the recognition of physical activity (PA)
is a well-known problem with many solutions. Sev eral kind of algorithms, using MEMS sensors, al low determine the most likely activity. Indeed,
these applications work ... Nowadays, the recognition of physical activity (PA) is a well-known problem with many solutions. Sev eral kind of algorithms, using MEMS sensors, al low determine the most likely activity. Indeed, these applications work well when physical activity is performed for long periods of time and steadily. However, indoors, these systems are not entirely suitable and have several problems. In this paper, thanks to the introduction of new context infor mation, such as EEG, and through communication between WoT based elements interface at home, it would be possible to perform a more accurate and low-level recognition. By using uPnP proto col and additional services, information from other smart housing elements with user device itself can be shared, enriching traditional systems based on ac-celerometry. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España Junta de Andalucía |
Identificador del proyecto | TIN2009-14378-C02-01
TIC-8052 |
Cita | Soria Morillo, L.M., Álvarez, M.A., Ortega Ramírez, J.A. y Vergara, R. (2013). Hi-Res activity recognition system based on EEG and WoT. En AITA 2013 : Workshop on Ambient Intelligence for Telemedicine and Automotive (7-11), Sevilla, España: Universidad de Sevilla. |
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