Evidence map›Paper›PMID 34562921›Full record

ArticleBiosensors2021

Detection of the Complete ECG Waveform with Woven Textile Electrodes.

Katya Arquilla, Laura Devendorf, Andrea K Webb, Allison P Anderson

Abstract read
In one paragraph

Article in Biosensors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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.

Katya ArquillaSmead Aerospace Engineering Sciences, University of Colorado Boulder, Bouder, CO 80303, USA.ORCID 0000-0002-7406-1012
Laura DevendorfDepartment of Information Science, University of Colorado Boulder, Bouder, CO 80303, USA.
Andrea K WebbThe Charles Stark Draper Laboratory, Inc., Cambridge, MA 02139, USA.
Allison P AndersonSmead Aerospace Engineering Sciences, University of Colorado Boulder, Bouder, CO 80303, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable physiological monitoring systems are becoming increasingly prevalent in the push toward autonomous health monitoring and offer new modalities for playful and purposeful interaction within human computer interaction (HCI). Sensing systems that can be integrated into garments and, therefore, daily activities offer promising pathways toward ubiquitous integration. The electrocardiogram (ECG) signal is commonly monitored in healthcare and is increasingly utilized as a method of determining emotional and psychological state; however, the complete ECG waveform with the P, Q, R, S, and T peaks is not commonly used, due to the challenges associated with collecting the full waveform with wearable systems. We present woven textile electrodes as an option for garment-integrated ECG monitoring systems that are capable of capturing the complete ECG waveform. In this work, we present the changes in the peak detection performance caused by different sizes, patterns, and thread types with data from 10 human participants. These testing results provide empirically-derived guidelines for future woven textile electrodes, present a path forward for assessing design decisions, and highlight the importance of testing novel wearable sensor systems with more than a single individual.

Indexed as

ElectrocardiographyTextilesWearable Electronic DevicesElectrodesHumanse-textilessmart garmentstextile electrodeswearable sensor systems

Identifiers

PMID34562921
PMCPMC8471440

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.