Evidence map›Paper›PMID 40431777›Full record

ReviewSensors (Basel, Switzerland)2025

Are Wearable ECG Devices Ready for Hospital at Home Application?

Jorge Medina-Avelino, Ricardo Silva-Bustillos, Juan A Holgado-Terriza

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
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

3 authors.

Jorge Medina-AvelinoSoftware Engineering Department, Research Centre for Information and Communication Technologies (CITIC-UGR), University of Granada, 18071 Granada, Spain.ORCID 0000-0003-1682-7953
Ricardo Silva-BustillosDepartment of Computing Sciences University of Villanova, Villanova, PA 19085, USA.ORCID 0000-0001-9390-3388
Juan A Holgado-TerrizaSoftware Engineering Department, Research Centre for Information and Communication Technologies (CITIC-UGR), University of Granada, 18071 Granada, Spain.ORCID 0000-0002-8031-1276

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing focus on improving care for high-cost patients has highlighted the potential of Hospital at Home (HaH) and remote patient monitoring (RPM) programs to optimize patient outcomes while reducing healthcare costs. This paper examines the role of wearable devices with electrocardiogram (ECG) capabilities for continuous cardiac monitoring, a crucial aspect for the timely detection and management of various cardiac conditions. The functionality of current wearable technology is scrutinized to determine its effectiveness in meeting clinical needs, employing a proposed ABCD guide (accuracy, benefit, compatibility, and data governance) for evaluation. While smartwatches show promise in detecting arrhythmias like atrial fibrillation, their broader diagnostic capabilities, including the potential for monitoring corrected QT (QTc) intervals during pharmacological interventions and approximating multi-lead ECG information for improved myocardial infarction detection, are also explored. Recent advancements in machine learning and deep learning for cardiac health monitoring are highlighted, alongside persistent challenges, particularly concerning signal quality and the need for further validation for widespread adoption in older adults and Hospital at Home settings. Ongoing improvements are necessary to overcome current limitations and fully realize the potential of wearable ECG technology in providing optimal care for high-risk patients.

Indexed as

ElectrocardiographyWearable Electronic DevicesArrhythmias, CardiacAtrial FibrillationHome Care ServicesHospitalsHumansMonitoring, PhysiologicTelemedicineartificial intelligencecardiac healthpatient outcomesremote patient monitoringwearable devices

Identifiers

PMID40431777
PMCPMC12114646

What OpenQuestion holds

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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.