Next Article in Journal
Improved PPO Optimization for Robotic Arm Grasping Trajectory Planning and Real-Robot Migration
Previous Article in Journal
Pressure-Guided LSTM Modeling for Fermentation Quantification Prediction
Previous Article in Special Issue
Adapting Young Adults’ In-Shoe Motion Sensor Gait Models for Knee Evaluation in Older Adults: A Study on Osteoarthritis and Healthy Knees
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Systematic Review

Stage-Wise IoT Solutions for Alzheimer’s Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies

by
Sanket Salvi
1,*,
Lalit Garg
2 and
Varadraj Gurupur
1
1
Center for Decision Support Systems and Informatics, School of Global Health Management and Informatics, University of Central Florida, Orlando, FL 32816, USA
2
Department of Computer Information Systems, Faculty of Information Communication Technology, University of Malta, 2080 Msida, Malta
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(17), 5252; https://doi.org/10.3390/s25175252 (registering DOI)
Submission received: 12 June 2025 / Revised: 30 July 2025 / Accepted: 21 August 2025 / Published: 23 August 2025

Abstract

The Internet of Things (IoT) has emerged as a transformative technology in managing Alzheimer’s Disease (AD), offering novel solutions for early diagnosis, continuous patient monitoring, and assistive care. This review presents a comprehensive analysis of iot-enabled systems tailored to ad care, focusing on wearable biosensors, cognitive monitoring tools, smart home automation, and Artificial Intelligence (AI)-driven analytics. A systematic literature survey was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify, screen, and synthesize 236 relevant studies primarily published between 2020 and 2025 across IEEE Xplore, PubMed, Scopus and Web of Science. The inclusion criteria targeted peer-reviewed articles that proposed or evaluated iot-based solutions for ad detection, progression monitoring, or patient assistance. Key findings highlight the effectiveness of the iot in detecting behavioral and cognitive changes, enhancing safety through real-time alerts, and improving patient autonomy. The review also explores integration challenges such as data privacy, system interoperability, and clinical adoption. The study reveals critical gaps in real-world deployment, clinical validation, and ethical integration of iot-based systems for Alzheimer’s care. This study aims to serve as a definitive reference for researchers, clinicians, and developers working at the intersection of the iot and neurodegenerative healthcare.
Keywords: Internet of Things; Alzheimer’s disease monitoring; sleep disorder detection; wearable healthcare devices; artificial intelligence in healthcare; Remote Patient Monitoring; machine learning in healthcare; healthcare data privacy and ethics Internet of Things; Alzheimer’s disease monitoring; sleep disorder detection; wearable healthcare devices; artificial intelligence in healthcare; Remote Patient Monitoring; machine learning in healthcare; healthcare data privacy and ethics

Share and Cite

MDPI and ACS Style

Salvi, S.; Garg, L.; Gurupur, V. Stage-Wise IoT Solutions for Alzheimer’s Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies. Sensors 2025, 25, 5252. https://doi.org/10.3390/s25175252

AMA Style

Salvi S, Garg L, Gurupur V. Stage-Wise IoT Solutions for Alzheimer’s Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies. Sensors. 2025; 25(17):5252. https://doi.org/10.3390/s25175252

Chicago/Turabian Style

Salvi, Sanket, Lalit Garg, and Varadraj Gurupur. 2025. "Stage-Wise IoT Solutions for Alzheimer’s Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies" Sensors 25, no. 17: 5252. https://doi.org/10.3390/s25175252

APA Style

Salvi, S., Garg, L., & Gurupur, V. (2025). Stage-Wise IoT Solutions for Alzheimer’s Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies. Sensors, 25(17), 5252. https://doi.org/10.3390/s25175252

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop