'Universidad de Sevilla - Secretariado de Recursos Audiovisuales y Nuevas Tecnologias'
Abstract
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.Ministerio de Economía y Competitividad TIN2009-14378-C02-01Junta de Andalucía TIC-805
