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Open AccessSystematic Review
Stage-Wise IoT Solutions for Alzheimer’s Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies
by
Sanket Salvi
Sanket Salvi 1,*
,
Lalit Garg
Lalit Garg 2
and
Varadraj Gurupur
Varadraj Gurupur
Prof. Varadraj Gurupur received his Bachelor of Engineering from Mangalore University in 2002 and of [...]
Prof. Varadraj Gurupur received his Bachelor of Engineering from Mangalore University in 2002 and his Master of Science and Ph.D. from the University of Alabama at Birmingham in 2005 and 2010, respectively. He is an Associate Professor at the School of Global Health Management and Informatics at the University of Central
Florida. His core research is focused on software engineering decision support systems for healthcare and education. He receives research grants and holds several patents in health information management.
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.
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
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