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Web System for Detection, Control, and Prevention of Alzheimer's Evolution (SIDECPA)

  • Naranjo Sanchez, Bertha Alice (PI)
  • Mora Saltos, Nelson Salomon (Col)
  • Bermeo Flores, Jack Andres (Student)
  • Tinoco Arichavala, Maria Jose (Student)
  • Vega Bravo, Daniel Enrique (Student)
  • Idrovo Llaguno, Jamileth Cristina (Student)
  • Pilla Salinas, Ramon Ulpiano (Student)
  • Suque Cercado, Angel Steven (Student)
  • Aguilar Paladines, Washington Eduardo (Student)
  • Jimpikit Cunambe, Lida Gabriela (Student)

Project Details

Description

This project addresses the critical lack of assistance services, treatment, and technological support for Alzheimer's patients in Guayaquil, Ecuador, where specialized centers comparable to those in Quito do not exist. The core problem lies in the inaccessibility of in-person therapies for low-income individuals and the absence of technological alternatives for disease detection and prevention. The proposed solution is the development of an automated tool accessible via web and mobile platforms. This tool aims to fulfill three key functions: facilitating Alzheimer's detection through neurologically validated automated tests, enabling the monitoring of disease progression in mild to moderate stages, and providing specific therapies for memory exercises. The ultimate goal is to offer an accessible alternative to help slow the rapid advancement of Alzheimer's. The system development will follow the Rational Unified Process (RUP) methodology, encompassing the phases of Initiation (defining scope and validation with the Medical College), Elaboration (detailed requirements analysis and architecture definition), Construction (design and source code implementation), and Transition (final delivery to users).<br/><br/><b>Goal</b>: <br/>The main objective of this project is to investigate and develop an automated tool, accessible via web and mobile devices, to contribute to the early detection of Alzheimer's, control its progressive advancement in mild to moderate patients, and offer therapies that exercise memory, aiming to slow down the progression of the disease.<br/><br/><b>Research lines</b>: <br/>Artificial intelligence
StatusFinished
Effective start/end date23/03/184/08/21

Keywords

  • Alzheimer's
  • Early detection
  • Memory therapy
  • Automated tool
  • Accessibility
  • Progression monitoring
  • Digital health
  • Mobile devices

CACES Knowledge Areas

  • 316A Software and Applications Development and Analysis

Categorías UNESCO

  • Software and application development and analysis