Face Recognition-Based Smart Glass for Alzheimer’s Patients

Abstract

Alzheimer’s Disease (AD) is a neurodegenerative disorder that damages the human brain, leading to dementia. The most difficult challenge that an AD patient faces is forgetting people’s names. The study aims to assist AD patients with a moderate stage by designing a smart glass to identify a person. Basically, it depends on face recognition technology. The glass allows you to track the patient in case of aimless wandering, in addition to talking with the patient. The design was implemented by dividing the system into hardware and software. The hardware consists of the Raspberry Pi 4, Pi camera, ultrasonic sensor, and GPS module. Python coded the software to run a Viola-Jones-based face recognition algorithm. A Local Binary Pattern was used to extract features based on machine learning principles. The Support vector machine (SVM) and the K-Nearest Neighbors (K-NN) were employed as classifiers. A mobile application named “Forget Me Not” was developed to support the patient and the caregiver as well. Results demonstrated satisfaction with the design through capturing one thousand images of 250 people and training the system. Classification accuracy of 84.45% and 93.36% for the SVM and K-NN, respectively, was achieved. Furthermore, the mobile application facilitates the usage of glass. Thus, the study presents an assistance tool for AD patients to coexist with society.