Comprehensive review of vision-based fall detection systems
Resumen: Vision-based fall detection systems have experienced fast development over the last years. To determine the course of its evolution and help new researchers, the main audience of this paper, a comprehensive revision of all published articles in the main scientific databases regarding this area during the last five years has been made. After a selection process, detailed in the Materials and Methods Section, eighty-one systems were thoroughly reviewed. Their characterization and classification techniques were analyzed and categorized. Their performance data were also studied, and comparisons were made to determine which classifying methods best work in this field. The evolution of artificial vision technology, very positively influenced by the incorporation of artificial neural networks, has allowed fall characterization to become more resistant to noise resultant from illumination phenomena or occlusion. The classification has also taken advantage of these networks, and the field starts using robots to make these systems mobile. However, datasets used to train them lack real-world data, raising doubts about their performances facing real elderly falls. In addition, there is no evidence of strong connections between the elderly and the communities of researchers.
Idioma: Inglés
DOI: 10.3390/s21030947
Año: 2021
Publicado en: Sensors 21, 3 (2021), 947 [50 pp]
ISSN: 1424-8220

Factor impacto JCR: 3.847 (2021)
Categ. JCR: CHEMISTRY, ANALYTICAL rank: 29 / 87 = 0.333 (2021) - Q2 - T2
Categ. JCR: INSTRUMENTS & INSTRUMENTATION rank: 19 / 64 = 0.297 (2021) - Q2 - T1
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 95 / 277 = 0.343 (2021) - Q2 - T2

Factor impacto CITESCORE: 6.4 - Engineering (Q1) - Physics and Astronomy (Q1) - Biochemistry, Genetics and Molecular Biology (Q2)

Factor impacto SCIMAGO: 0.803 - Analytical Chemistry (Q1) - Biochemistry (Q1) - Instrumentation (Q1) - Information Systems (Q1) - Electrical and Electronic Engineering (Q1)

Tipo y forma: Review (Published version)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.


Exportado de SIDERAL (2023-05-18-15:09:03)


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 Record created 2021-03-09, last modified 2023-05-19


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