{"id":218,"date":"2023-07-27T10:10:10","date_gmt":"2023-07-27T10:10:10","guid":{"rendered":"https:\/\/open.ieec.uned.es\/e-health\/?p=218"},"modified":"2023-07-27T10:10:10","modified_gmt":"2023-07-27T10:10:10","slug":"human-stability-assessment-and-fall-detection-based-on-dynamic-descriptors","status":"publish","type":"post","link":"https:\/\/open.ieec.uned.es\/e-health\/human-stability-assessment-and-fall-detection-based-on-dynamic-descriptors\/","title":{"rendered":"Human stability assessment and fall detection based on dynamic descriptors"},"content":{"rendered":"\n

Recientemente han aprobado para publicaci\u00f3n en la revista \u00abIET Image Processing<\/em>\u00ab, indexada en JCR, el art\u00edculo titulado \u00abHuman stability assessment and fall detection based on dynamic descriptors<\/strong>\u00ab. Este trabajo es fruto de una tesis doctoral realizada dentro del programa de Doctorado en Tecnolog\u00edas Industriales, y dirigida por Sergio Mart\u00edn (Profesor Titular de la UNED) y V\u00edctor Rodr\u00edguez Ontiveros (investigador colaborador de la Universidad de Zaragoza).<\/p>\n\n\n\n

Aqu\u00ed os dejamos el abstract por si os resulta de inter\u00e9s:<\/p>\n\n\n\n

Both fall detection and fall prevention systems use an array of different technologies to<\/em> achieve their goals, contributing this way to better life conditions for the elderly<\/em> community. The artificial vision is one of these technologies and, within this field, it has<\/em> gained momentum over the course of the last few years with the incorporation of<\/em> different neural network architectures. These architectures, although different, share a<\/em> common characteristic, they are used to extract static or kinematic descriptors from<\/em> images and video clips that, properly processed, will determine if a fall has taken place<\/em> or if a patient\u2019s gait fulfils the characteristics associated to frequent fallers\u2019 ones.<\/em> However, these descriptors are inferred from datasets recorded by young volunteers or<\/em> actors who simulate falls, and the differences between these falls and the real ones are<\/em> well documented. This way, concerns about system performances in the wild, out of<\/em> laboratory environments, are raised.<\/em><\/p>\n\n\n\n

This work aims to reframe the problem of fall detection and approach it as a stability<\/em>\u00a0assessment task. To do it, for the first time to the best of our knowledge, we propose<\/em>\u00a0the introduction of human dynamic stability descriptors used in other fields. These new<\/em>\u00a0descriptors are determined by using the information provided by a neural network able<\/em>\u00a0to estimate the body center of mass and the feet projections onto the ground plane, as<\/em>\u00a0well as the feet contact status with the ground.<\/em><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

The theory behind this new approach and its validity is studied in this article with very<\/em> promising results, as it is able to match or over exceed the performances of previous<\/em> systems using kinematic or static descriptors in laboratory conditions and, given the<\/em> independence of this system performances from fall dataset information, it has the<\/em> potential to behave better than systems based on other approaches in real world<\/em> environments.<\/em><\/p>\n\n\n\n

Y aqu\u00ed os dejamos la referencia por si quer\u00e9is citarla:<\/p>\n\n\n\n

  • J. Gutierrez, S. Martin, V. Rodriguez. Human stability assessment and fall detection based on dynamic descriptors. IET Image Processing. 00, 1\u2013 19 (2023), Wiley. Print ISSN: 1751-9659. EISSN: 1751-9667. https:\/\/doi.org\/10.1049\/ipr2.12847<\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"

    Recientemente han aprobado para publicaci\u00f3n en la revista \u00abIET Image Processing\u00ab, indexada en JCR, el art\u00edculo titulado \u00abHuman stability assessment and fall detection based on dynamic descriptors\u00ab. Este trabajo es fruto de una tesis doctoral…<\/p>\n","protected":false},"author":1,"featured_media":219,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/posts\/218"}],"collection":[{"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/comments?post=218"}],"version-history":[{"count":1,"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/posts\/218\/revisions"}],"predecessor-version":[{"id":220,"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/posts\/218\/revisions\/220"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/media\/219"}],"wp:attachment":[{"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/media?parent=218"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/categories?post=218"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/open.ieec.uned.es\/e-health\/wp-json\/wp\/v2\/tags?post=218"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}