Evidence map›Paper›PMID 40367504›Full record

SynthesisJMIR aging2025

Advancing Remote Monitoring for Patients With Alzheimer Disease and Related Dementias: Systematic Review.

Mohmmad Arif Shaik, Fahim Islam Anik, Md Mehedi Hasan, Sumit Chakravarty, Mary Dioise Ramos, Mohammad Ashiqur Rahman, Sheikh Iqbal Ahamed, Nazmus Sakib

Abstract readSystematic Review
In one paragraph

Synthesis in JMIR aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Observational
  8. Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Mohmmad Arif ShaikDepartment of Electrical and Computer Engineering, Kennesaw State University, Kennesaw, GA, United States.ORCID https://orcid.org/0009-0001-2730-9038
Fahim Islam AnikDepartment of Mechanical Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh.ORCID https://orcid.org/0000-0002-6121-266X
Md Mehedi HasanDepartment of Electrical and Computer Engineering, Kennesaw State University, Kennesaw, GA, United States.ORCID https://orcid.org/0009-0000-4373-7684
Sumit ChakravartyDepartment of Electrical and Computer Engineering, Kennesaw State University, Kennesaw, GA, United States.ORCID https://orcid.org/0000-0001-8108-8726
Mary Dioise RamosLouisiana State University Health Sciences Center (LSUHSC) New Orleans, School of Nursing, Louisiana State University, New Orleans, United States.ORCID https://orcid.org/0000-0002-9371-2925
Mohammad Ashiqur RahmanDepartment of Electrical and Computer Engineering, Florida International University, Miami, FL, United States.ORCID https://orcid.org/0000-0002-2963-7430
Sheikh Iqbal AhamedDepartment of Computer Science, Marquette University, Milwaukee, WI, United States.ORCID https://orcid.org/0000-0001-5385-7647
Nazmus SakibDepartment of Electrical and Computer Engineering, Kennesaw State University, Kennesaw, GA, United States.ORCID https://orcid.org/0000-0002-7008-1120

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUsing remote monitoring technology in the context of Alzheimer disease (AD) care presents exciting new opportunities to lessen caregiver stress and improve patient care quality. The application of wearables, environmental sensors, and smart home systems designed specifically for patients with AD represents a promising interdisciplinary approach that integrates advanced technology with health care to enhance patient safety, monitor health parameters in real time, and provide comprehensive support to caregivers.

objectiveThe objectives of this study included evaluating the effectiveness of various remote sensing technologies in enhancing patient outcomes and identifying strategies to alleviate the burden on health care professionals and caregivers. Critical elements such as regulatory compliance, user-centered design, privacy and security considerations, and the overall efficacy of relevant technologies were comprehensively examined. Ultimately, this study aimed to propose a comprehensive remote monitoring framework tailored to the needs of patients with AD and related dementias.

methodsGuided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, we conducted a systematic review on remote monitoring for patients with AD and related dementias. Our search spanned 4 major electronic databases-Google Scholar, PubMed, IEEE Xplore, and DBLP on February 20, 2024, with an updated search on May 18, 2024.

resultsA total of 31 publications met the inclusion criteria, highlighting 4 key research areas: existing remote monitoring technologies, balancing practicality and empathy, security and privacy in monitoring, and technology design for AD care. The studies revealed a strong focus on various remote monitoring methods for capturing behavioral, physiological, and environmental data yet showed a gap in evaluating these methods for patient and caregiver needs, privacy, and usability. The findings also indicated that many studies lacked robust reference standards and did not consistently apply critical appraisal criteria, underlining the need for comprehensive frameworks that better integrate these essential considerations.

conclusionsThis comprehensive literature review of remote monitoring technologies for patients with AD provides an understanding of remote monitoring technologies, trends, and gaps in the current research and the significance of novel strategies for remote monitoring to enhance patient outcomes and reduce the burden among health professionals and caregivers. The proposed remote monitoring framework aims to inspire the development of new interdisciplinary research models that advance care for patients with AD.

Indexed as

Alzheimer DiseaseDementiaRemote Sensing TechnologyCaregiversHumansMonitoring, PhysiologicTelemedicineAlzheimerAlzheimer diseaseartificial intelligencecaregiverdementiafall detectionremote monitoring

Identifiers

PMID40367504
PMCPMC12120371

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.