Alzheimer assistant: a mobile application using Machine Learning

Nahla ALJOJO1, Reem ALOTAIBI2, Basma ALHARBI3, Areej ALSHUTAYRI3, Amani Tariq JAMAL4,
Ameen BANJAR1, Mashael KHAYYAT1, Azida ZAINOL5, Abrar AL-ROQY1,
Rahaf AL-MAGRABI1, Taghreed KHALAWI1, Sarah AL-HARTHI1

1 College of Computer Science and Engineering, Information system and Technology Department,
University of Jeddah, Jeddah, Saudi Arabia
nmaljojo@uj.edu.sa, abanjar@uj.edu.sa, mkhayyat@uj.edu.sa, Abfa95@hotmail.com,
rahafalmagrabi@gmail.com, To0ota.kh.2020@gmail.com, alharthisarah97@gmail.com
2 Information Technology Department, Faculty of Computing & Information Technology,
King Abdulaziz University, Jeddah, Saudi Arabia
ralotibi@kau.edu.sa
3 Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering,
University of Jeddah, Jeddah, Saudi Arabia
bmalharbi@uj.edu, aoalshutayri@uj.edu.sa
4 Computer Science Department, Faculty of Computing & Information Technology,
King Abdulaziz University, Jeddah, Saudi Arabia
Atjamal@kau.edu.sa
5 Department of Software Engineering, College of Computer Science and Engineering,
University of Jeddah, Jeddah, Saudi Arabia
azzainol@uj.edu.sa

Abstract: Alzheimer’s disease is a condition characterized by a progressive symptomatic decline over several years. It causes memory loss and affects daily task performance. Memory loss leads to challenges including remembering people’s names, faces, places, or other information. In Saudi Arabia, the prevalence rate for Alzheimer’s disease is increasing and, accordingly, warrants attention and address. Thus, the objective of this work is to support Alzheimer’s patients with mild (early-stage) and moderate (middle-stage) conditions to remain involved in society and continue to live independently. We propose a mobile application which utilizes facial recognition technology and location detection using Google maps. The application aims to improve daily communication, enhancing their ability to perform daily tasks by the embedding of a notification feature. It has location detection to maintain the safety of Alzheimer’s patients, and help prevent them from getting lost by tracking their location. Results have shown that the application has benefited those living with the symptoms of Alzheimer’s, and significantly support their daily lives. Therefore, this work highlights the importance of employing artificial intelligence (AI)-based features, i.e., face recognition in this specific case when developing healthcare applications which can have a significant impact on the community.

Keywords: Machine Learning, Mobile Application, Alzheimer’s disease, face recognition.

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CITE THIS PAPER AS:
Nahla ALJOJO, Reem ALOTAIBI, Basma ALHARBI, Areej ALSHUTAYRI, Amani Tariq JAMAL, Ameen BANJAR, Mashael KHAYYAT, Azida ZAINOL, Abrar AL-ROQY, Rahaf AL-MAGRABI, Taghreed KHALAWI, Sarah AL-HARTHI, Alzheimer assistant: a mobile application using Machine Learning, Romanian Journal of Information Technology and Automatic Control, ISSN 1220-1758, vol. 30(4), pp. 7-26, 2020. https://doi.org/10.33436/v30i4y202001