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Wearable stretch sensors have potential applications across many fields including medicine and sports, but the accuracy of the data produced by the sensors over repeated uses is largely unknown due to a paucity of high-cycle fatigue (HCF) studies on both the materials comprising the sensors and the signal produced by the sensors. To overcome these limitations, using human physiologically-based parameters, stretch sensors were subjected to quasi-static testing and HCF with simultaneous capture of the signal. The strain produced by the sensor was then compared to the strain produced by testing instrument, and the results suggest that the output from the stretch sensors is strongly correlated with output from the testing instrument under quasi-static conditions; however, this correlation deteriorates under fatigue conditions. Such deterioration may be the result of several factors, including a mismatch between the material response to fatiguing and the signal response to fatiguing. From a materials perspective, the shape of the stress-life curve for the polymers comprising the sensors conforms to the Rabinowitz-Beardmore model of polymer fatigue. Based on these results, consideration of the material properties of a stretch sensor are necessary to determine how accurate the output from the sensor will be for a given application.
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Fatigue Testing of Wearable Sensing Technologies: Issues and Opportunities
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.
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- Award ID(s):
- 1827652
- PAR ID:
- 10288387
- Date Published:
- Journal Name:
- Materials
- Volume:
- 14
- Issue:
- 15
- ISSN:
- 1996-1944
- Page Range / eLocation ID:
- 4070
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/ma14154070
