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Implementation of an evaluation platform for Alzheimer patients based on Egocentric Sequences Description

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dc.contributor Bolaños Solà, Marc
dc.contributor Radeva, Petia
dc.creator Soler Solé, Sergi
dc.date 2018-01-19T11:58:10Z
dc.date 2018-01-19T11:58:10Z
dc.date 2017-01-30
dc.date.accessioned 2024-12-16T10:26:04Z
dc.date.available 2024-12-16T10:26:04Z
dc.identifier http://hdl.handle.net/2445/119160
dc.identifier.uri http://fima-docencia.ub.edu:8080/xmlui/handle/123456789/20467
dc.description Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2017, Director: Marc Bolaños Solà i Petia Radeva
dc.description Numerous international population-based studies have been conducted to document the frequency of MCI, estimating its prevalence to be between 15% and 20% in persons 60 years and older, making it a common condition encountered by clinicians[17]. This number is predicted to increase to 75.6 million in 2030, and 135.5 million in 2050[14], leading to deep social and economical costs. The most common dementia type is Alzheimer (between 50% and 70% of the cases) and its early detection can greatly affect the recovery of the patient. That is why it is important to have tools for its early diagnosis and follow-up. Serious games, with an increasing popularity, are a good way to MCI as an early stage of Alzheimer and improve the memory capacities of the patients. These video games focusing on different stages of the illness can help doctors to document and check the progress of the illness. This work aims on developing a software for patients with MCI, which is the lack of memory and other human characteristics like reasoning and language. These individuals usually progress to Alzheimer disease, but if detected early, in some cases they can also remain stable or even recover with time. To help them to exercise their memory, we propose that our program uses their own experiences caught by a wearable camera. This software will provide images of the patient’s life in order to do exercises that will evaluate their ability to remember and reason about the scenes they visualize. With these tests, the doctors will be able to see the evolution of the patients, and help them to diagnose and track the illness. In this project, we additionally work on an application, for the first time, of Deep Neural Networks for the automatic generation of descriptions of egocentric sequences. This will serve as the first step to automate the evaluation process by automatically comparing the subjective descriptions provided by the patients to the objective ones generated by our system.
dc.format 42 p.
dc.format application/pdf
dc.language eng
dc.rights memòria: cc-by-nc-sa (c) Sergi Soler Solé, 2017
dc.rights codi: GPL (c) Sergi Soler Solé, 2017
dc.rights http://creativecommons.org/licenses/by-sa/3.0/es
dc.rights http://www.gnu.org/licenses/gpl-3.0.ca.html
dc.rights info:eu-repo/semantics/openAccess
dc.source Treballs Finals de Grau (TFG) - Enginyeria Informàtica
dc.subject Malaltia d'Alzheimer
dc.subject Trastorns de la memòria
dc.subject Programari
dc.subject Treballs de fi de grau
dc.subject Desenvolupament de programari d'aplicació
dc.subject Xarxes neuronals (Informàtica)
dc.subject Alzheimer's disease
dc.subject Memory disorders
dc.subject Computer software
dc.subject Bachelor's theses
dc.subject Development of application software
dc.subject Neural networks (Computer science)
dc.title Implementation of an evaluation platform for Alzheimer patients based on Egocentric Sequences Description
dc.type info:eu-repo/semantics/bachelorThesis


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