Evidence map›Paper›PMID 39589984›Full record

ReviewBiosensors2024

Advances in Cardiovascular Wearable Devices.

Sheikh Muhammad Asher Iqbal, Mary Ann Leavitt, Imadeldin Mahgoub, Waseem Asghar

Abstract readReview
In one paragraph

Review in Biosensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. 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

4 authors.

Sheikh Muhammad Asher IqbalDepartment of Electrical Engineering & Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA.
Mary Ann LeavittChristine E. Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL 33431, USA.ORCID 0000-0002-1407-070X
Imadeldin MahgoubDepartment of Electrical Engineering & Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA.ORCID 0000-0002-4461-7307
Waseem AsgharDepartment of Electrical Engineering & Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA.ORCID 0000-0003-0458-8430

Funding

NSF CAREER Award 1942487
6 · The paper itself

Abstract

Cardiovascular diseases are a leading cause of death worldwide. They mainly include coronary artery disease, rheumatic heart disease, andcerebrovascular disease, and. Cardiovascular diseases can be better managed and diagnosed using wearable devices. Wearable devices, in comparison to traditional cardiovascular diagnostic tools, are not only inexpensive but also have the potential to provide continuous real-time monitoring. This paper reviews some of the recent advances in cardiovascular wearable devices. It discusses traditional implantable devices for cardiovascular diseases as well as wearable devices. The different types of wearable devices are categorized based on different technologies, namely using galvanic contact, photoplethysmography (PPG), and radio frequency (RF) waves. It also highlights the use of artificial intelligence (AI) in cardiovascular disease diagnostics as well as future perspectives on cardiovascular devices.

Indexed as

Cardiovascular DiseasesPhotoplethysmographyWearable Electronic DevicesArtificial IntelligenceHumanscardiovascularimplantable devicestelehealth monitoringwearable devices

Identifiers

PMID39589984
PMCPMC11591746

What Socratic 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 Socratic graph.