Ponencia
Evaluating Wearable Activity Recognition and Fall Detection Systems
Autor/es | Álvarez García, Juan Antonio
Soria Morillo, Luis Miguel Álvarez de la Concepción, Miguel Ángel Fernández Montes González, Alejandro Ortega Ramírez, Juan Antonio |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2014 |
Fecha de depósito | 2021-09-21 |
Publicado en |
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ISBN/ISSN | 1680-0737 |
Resumen | Activity recognition (AR) and fall detection (FD)
research areas are very related in assistance scenarios but
evolve independently. Evaluate them is not trivial and the lack
of FD real-world datasets implies a big issue. ... Activity recognition (AR) and fall detection (FD) research areas are very related in assistance scenarios but evolve independently. Evaluate them is not trivial and the lack of FD real-world datasets implies a big issue. A protocol that fuses AR and FD is proposed to achieve a large, open and growing dataset that could, potentially, provide an enhanced understanding of the activities and fall process and the information needed to design and evaluate high-performance systems. |
Agencias financiadoras | Junta de Andalucía Ministerio de Economía y Competitividad (MINECO). España |
Identificador del proyecto | P11-TIC-8052
TIN2013-46801-C4 |
Cita | Álvarez García, J.A., Soria Morillo, L.M., Álvarez de la Concepción, M.Á., Fernández Montes González, A. y Ortega Ramírez, J.A. (2014). Evaluating Wearable Activity Recognition and Fall Detection Systems. En MBEC 2014 : 6th European Conference of the International Federation for Medical and Biological Engineering (653-656), Dubrovnik, Croatia: SpringerLink. |
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