Evidence map›Paper›PMID 34361264›Full record

ReviewMaterials (Basel, Switzerland)2021

Fatigue Testing of Wearable Sensing Technologies: Issues and Opportunities.

Andrea Karen Persons, John E Ball, Charles Freeman, David M Macias, Chartrisa LaShan Simpson, Brian K Smith, Reuben F Burch V

Abstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Article
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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.

Andrea Karen PersonsDepartment of Agricultural and Biological Engineering, Mississippi State University, 130 Creelman Street, Starkville, MS 39762, USA.
John E BallHuman Factors and Athlete Engineering, Center for Advanced Vehicular Systems, Mississippi State University, 200 Research Boulevard, Starkville, MS 39759, USA.ORCID 0000-0002-6774-4851
Charles FreemanSchool of Human Sciences, Mississippi State University, 255 Tracy Drive, Starkville, MS 39762, USA.
David M MaciasDepartment of Kinesiology, Mississippi State University, P.O. Box 6186, Starkville, MS 39762, USA.
Chartrisa LaShan SimpsonDepartment of Agricultural and Biological Engineering, Mississippi State University, 130 Creelman Street, Starkville, MS 39762, USA.
Brian K SmithDepartment of Industrial and Systems Engineering, Mississippi State University, 479-2 Hardy Road, Starkville, MS 39762, USA.
Reuben F Burch VHuman Factors and Athlete Engineering, Center for Advanced Vehicular Systems, Mississippi State University, 200 Research Boulevard, Starkville, MS 39759, USA.ORCID 0000-0003-2944-1945

Funding

National Science Foundation 1,827,652
6 · The paper itself

Abstract

Standards for the fatigue testing of wearable sensing technologies are lacking. The majority of published fatigue tests for wearable sensors are performed on proof-of-concept stretch sensors fabricated from a variety of materials. Due to their flexibility and stretchability, polymers are often used in the fabrication of wearable sensors. Other materials, including textiles, carbon nanotubes, graphene, and conductive metals or inks, may be used in conjunction with polymers to fabricate wearable sensors. Depending on the combination of the materials used, the fatigue behaviors of wearable sensors can vary. Additionally, fatigue testing methodologies for the sensors also vary, with most tests focusing only on the low-cycle fatigue (LCF) regime, and few sensors are cycled until failure or runout are achieved. Fatigue life predictions of wearable sensors are also lacking. These issues make direct comparisons of wearable sensors difficult. To facilitate direct comparisons of wearable sensors and to move proof-of-concept sensors from "bench to bedside", fatigue testing standards should be established. Further, both high-cycle fatigue (HCF) and failure data are needed to determine the appropriateness in the use, modification, development, and validation of fatigue life prediction models and to further the understanding of how cracks initiate and propagate in wearable sensing technologies.

Indexed as

cyclic softeningcyclic testingfatigue testingfatigue testing standardshigh-cycle fatiguehysteresislead failurelow-cycle fatiguestretch sensorwearables

Identifiers

PMID34361264
PMCPMC8347841

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.