Artículo
Detection of human impacts by an adaptive energy-based anisotropic algorithm
Autor/es | Prado-Velasco, Manuel
Ortiz Marín, Rafael Río Cidoncha, María Gloria del |
Departamento | Universidad de Sevilla. Departamento de Ingeniería Gráfica |
Fecha de publicación | 2013-10-10 |
Fecha de depósito | 2016-12-30 |
Publicado en |
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Resumen | Boosted by health consequences and the cost of falls in the elderly, this work
develops and tests a novel algorithm and methodology to detect human impacts that will
act as triggers of a two-layer fall monitor. The two ... Boosted by health consequences and the cost of falls in the elderly, this work develops and tests a novel algorithm and methodology to detect human impacts that will act as triggers of a two-layer fall monitor. The two main requirements demanded by socio-healthcare providers—unobtrusiveness and reliability—defined the objectives of the research. We have demonstrated that a very agile, adaptive, and energy-based anisotropic algorithm can provide 100% sensitivity and 78% specificity, in the task of detecting impacts under demanding laboratory conditions. The algorithm works together with an unsupervised real-time learning technique that addresses the adaptive capability, and this is also presented. The work demonstrates the robustness and reliability of our new algorithm, which will be the basis of a smart falling monitor. This is shown in this work to underline the relevance of the results. |
Agencias financiadoras | Ministerio de Industria y Comercio. España European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER) |
Cita | Prado-Velasco, M., Ortiz Marín, R. y Rio Cidoncha, G.d. (2013). Detection of human impacts by an adaptive energy-based anisotropic algorithm. International Journal of Environmental Research and Public Health, 10 (10), 4767-4789. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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ijerph-10-04767.pdf | 3.355Mb | [PDF] | Ver/ | |