ESP 32: Smart Support Empowering Alzheimer’s Patients

This paper explores the development of smart glasses equipped with an ESP32-CAM module and a supporting mobile application to enhance memory care for Alzheimer’s patients. Alzheimer’s patients often face challenges related to memory loss and disorientation, which can lead to confusion and emotional distress. The proposed system addresses these issues by combining wearable technology with visual recognition capabilities. The ESP32-CAM module, mounted on the glasses, captures images of the patient’s surroundings and recognizes familiar faces, locations, or objects through coded image recognition algorithms. The mobile application, connected via Wi-Fi or Bluetooth, processes this information and delivers real-time prompts to the patient through audio or visual cues in the glasses. These prompts help patients identify people and contextual information, assisting with recall and orientation and providing a greater sense of familiarity and reassurance. This paper aims to improve the quality of life for Alzheimer’s patients by enhancing their independence and reducing moments of confusion, ultimately supporting caregivers and improving patient well-being in memory care settings.

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Publication Details

Published
2025-03-26
DOI
https://doi.org/10.1109/icbsii65145.2025.11013049
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

ESP 32: Smart Support Empowering Alzheimer’s Patients

Anto P. Babu, Aloysious Alex, C R Alen Christy, Adityan Ramesh et al.
IoT and Edge/Fog Computing
article

ESP 32: Smart Support Empowering Alzheimer’s Patients

Anto P. Babu, Aloysious Alex, C R Alen Christy, Adityan Ramesh, Kh Hridhya, Siji Joseph
article en

Abstract

This paper explores the development of smart glasses equipped with an ESP32-CAM module and a supporting mobile application to enhance memory care for Alzheimer’s patients. Alzheimer’s patients often face challenges related to memory loss and disorientation, which can lead to confusion and emotional distress. The proposed system addresses these issues by combining wearable technology with visual recognition capabilities. The ESP32-CAM module, mounted on the glasses, captures images of the patient’s surroundings and recognizes familiar faces, locations, or objects through coded image recognition algorithms. The mobile application, connected via Wi-Fi or Bluetooth, processes this information and delivers real-time prompts to the patient through audio or visual cues in the glasses. These prompts help patients identify people and contextual information, assisting with recall and orientation and providing a greater sense of familiarity and reassurance. This paper aims to improve the quality of life for Alzheimer’s patients by enhancing their independence and reducing moments of confusion, ultimately supporting caregivers and improving patient well-being in memory care settings.

Openalex Percentile: Top 88%
IoT and Edge/Fog Computing
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