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Small and sensitive force sensors based on contact resistance
Small and sensitive force sensors are important components for various applications, such as wearable devices and the Internet of things (IoT) applications. A strain gauge is the most general type of force sensor; however, its miniaturization is limited because a structure is needed to form the stra...
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Published in: | Microelectronic engineering 2019-08, Vol.216, p.111058, Article 111058 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Small and sensitive force sensors are important components for various applications, such as wearable devices and the Internet of things (IoT) applications. A strain gauge is the most general type of force sensor; however, its miniaturization is limited because a structure is needed to form the strain. In this study, we investigated a new force measurement method based on contact electrical resistance that has the potential to be smaller than strain gauges. In this method, when force is applied to the back of a part with a curvature, the part deforms, and the contact electrical resistance between the curvature and a counter conductor surface increases. We evaluated the proposed method by applying static and dynamic forces between indium‑tin-oxide-coated glass and gold-coated rubber and measuring contact resistance. The experimental results demonstrated the reproducibility between nine cycles of loading and unloading, and the contact resistance fluctuated in the order of mN following the applied load at approximately 6 Hz. Therefore, we showed the efficacy of our proposed measurement method to measure applied static and dynamic forces.
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•Evaluated a new force measurement method based on contact electrical resistance.•Contact resistance had a reproducible relationship with an applied static load.•Contact resistance had a delayed response to changes in an applied dynamic load. |
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ISSN: | 0167-9317 1873-5568 |
DOI: | 10.1016/j.mee.2019.111058 |