Evidence map›Paper›PMID 32899770›Full record

ArticleSensors (Basel, Switzerland)2020

Integration and Testing of a Three-Axis Accelerometer in a Woven E-Textile Sleeve for Wearable Movement Monitoring.

Menglong Li, Russel Torah, Helga Nunes-Matos, Yang Wei, Steve Beeby, John Tudor, Kai Yang

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 32 citations in OpenAlex.

  1. Review
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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

7 authors at 2 institutions in 1 country.

Menglong LiSchool of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK.ORCID 0000-0002-9207-8993
Russel TorahSchool of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK.ORCID 0000-0002-5598-2860
Helga Nunes-MatosSchool of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK.
Yang WeiSchool of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.ORCID 0000-0001-6195-8595
Steve BeebySchool of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK.ORCID 0000-0002-0800-1759
John TudorSchool of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK.ORCID 0000-0003-1179-9455
Kai YangSchool of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK.
University of Southampton · GBNottingham Trent University · GB

Funding

Engineering and Physical Sciences Research Council EP/S001654/1
6 · The paper itself

Abstract

This paper presents a method to integrate and package an accelerometer within a textile to create an electronic textile (e-textile). The smallest commercially available accelerometer sensor (2 mm × 2 mm × 0.95 mm) is used in the e-textile and is fully integrated within the weave structure of the fabric itself, rendering it invisible to the wearer. The e-textile forms the basis of a wearable woven sleeve which is applied to arm and knee joint bending angle measurement. The integrated e-textile based accelerometer sensor system is used to identify activity type, such as walking or running, and count the total number of steps taken. Performance was verified by comparing measurements of specific elbow joint angles over the range of 0° to 180° with those obtained from a commercial bending sensor from Bend Labs and from a custom-built goniometer. The joint bending angles, measured by all three sensors, show good agreement with an error of less than ~1% of reading which provides a high degree of confidence in the e-textile sensor system. Subsequently, knee joint angles were measured experimentally on three subjects with each being tested three times on each of three activities (walking, running and climbing stairs). This allowed the minimum and maximum knee joint angles for each activity to be determined. This data is then used to identify activity type and perform step counting.

Indexed as

AccelerometryTextilesWearable Electronic DevicesHumansMovementWalkingelectronic textiles (e-textiles)joint bending angle monitoringwearable accelerometerwearable movement sensing

Identifiers

PMID32899770
PMCPMC7571150
OpenAlexW3083154738

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.