Detection of Human Impacts by an Adaptive Energy-Based Anisotropic Algorithm
Bibliographic Data
| ID | 15501799 |
|---|---|
| Authors | Manuel Prado-Velasco (0000-0003-2969-0423, Universidad de Sevilla, corresponding author), Rafael Marín (Multilevel Modeling and Emerging Technologies in Bioengineering (M2TB), University of Seville, Escuela Superior de Ingenieros, C. de los Descubrimientos s/n, Sevilla 41092, Spain), Rafael Ortíz‐Marín (0000-0003-0286-5369, Universidad de Sevilla), Gloria Del Rio Cidoncha (Universidad de Sevilla) |
| Year | 2013 |
| Volume | 10 |
| Issue | 10 |
| Pages | 4767-4789 |
| Publication date | 2013-10-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph10104767 |
| PMID | 24157505 |
| PMCID | PMC3823311 |
| OpenAlex | W2085379918 |
| Language | EN |
| References cited | 22 |
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
Agile software development · Algorithm · Data mining · Machine learning · Relevance (law · Reliability (semiconductor · Reliability engineering · Risk analysis (engineering · Robustness (evolution · Balance, Gait, and Falls Prevention · Computer Science · Context-Aware Activity Recognition Systems · Engineering · Gait Recognition and Analysis · Medicine · Artificial Intelligence
| Citation velocity | historical |
|---|---|
| Highly cited | No |