Evidence map›Paper›PMID 38179073›Full record

ArticleRoyal Society open science2024

Hearables: feasibility of recording cardiac rhythms from single in-ear locations.

Metin Yarici, Wilhelm Von Rosenberg, Ghena Hammour, Harry Davies, Pierluigi Amadori, Nico Ling, Yiannis Demiris, Danilo P Mandic

Open access · goldAbstract read
In one paragraph

Article in Royal Society open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

3 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. From Scalp to Ear-EEG: A Generalizable Transfer Learning Model for Automatic Sleep Scoring in Older People.IEEE journal of translational engineering in health and medicine · 2024
    Article
  3. 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

8 authors at 1 institution in 1 country.

Metin YariciDepartment of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.ORCID 0000-0002-3633-5211
Wilhelm Von RosenbergDepartment of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.
Ghena HammourDepartment of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.
Harry DaviesDepartment of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.
Pierluigi AmadoriDepartment of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.
Nico LingDepartment of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.
Yiannis DemirisDepartment of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.
Danilo P MandicDepartment of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.
Imperial College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ear is well positioned to accommodate both brain and vital signs monitoring, via so-called hearable devices. Consequently, ear-based electroencephalography has recently garnered great interest. However, despite the considerable potential of hearable based cardiac monitoring, the biophysics and characteristic cardiac rhythm of ear-based electrocardiography (ECG) are not yet well understood. To this end, we map the cardiac potential on the ear through volume conductor modelling and measurements on multiple subjects. In addition, in order to demonstrate real-world feasibility of in-ear ECG, measurements are conducted throughout a long-time simulated driving task. As a means of evaluation, the correspondence between the cardiac rhythms obtained via the ear-based and standard Lead I measurements, with respect to the shape and timing of the cardiac rhythm, is verified through three measures of similarity: the Pearson correlation, and measures of amplitude and timing deviations. A high correspondence between the cardiac rhythms obtained via the ear-based and Lead I measurements is rigorously confirmed through agreement between simulation and measurement, while the real-world feasibility was conclusively demonstrated through efficacious cardiac rhythm monitoring during prolonged driving. This work opens new avenues for seamless, hearable-based cardiac monitoring that extends beyond heart rate detection to offer cardiac rhythm examination in the community.

Indexed as

cardiac rhythmear electrocardiographyelectrocardiographic modellingelectrocardiographyhearableswearables

Identifiers

PMID38179073
PMCPMC10762432
OpenAlexW4390540085

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.