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ORCID: https://orcid.org/0000-0002-8764-2289 and Gómez Aguilera, Enrique Javier
ORCID: https://orcid.org/0000-0001-6998-1407
(2013).
Dysfunctional 3D model based on structural and neuropsychological information.
En: "International Conference on Recent Advances in Neurorehabilitation (ICRAN 2013)", 07/03/2013 - 08/03/2013, Valencia, Spain. pp. 175-178.
| Título: | Dysfunctional 3D model based on structural and neuropsychological information |
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| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | International Conference on Recent Advances in Neurorehabilitation (ICRAN 2013) |
| Fechas del Evento: | 07/03/2013 - 08/03/2013 |
| Lugar del Evento: | Valencia, Spain |
| Título del Libro: | International Conference on Recent Advances in Neurorehabilitation (ICRAN 2013) |
| Fecha: | 2013 |
| Materias: | |
| ODS: | |
| Escuela: | E.T.S.I. Telecomunicación (UPM) |
| Departamento: | Tecnología Fotónica [hasta 2014] |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
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Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module.
| ID de Registro: | 26365 |
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| Identificador DC: | https://oa.upm.es/26365/ |
| Identificador OAI: | oai:oa.upm.es:26365 |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 25 May 2014 11:58 |
| Ultima Modificación: | 02 Jul 2025 07:46 |
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