Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges
Flexible high-deflection strain gauges have been demonstrated to be cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, particularly during dynamic motion. I...
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MDPI AG
2024-12-01
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| author | Alex M. Wonnacott Anton E. Bowden Ulrike H. Mitchell David T. Fullwood |
| author_facet | Alex M. Wonnacott Anton E. Bowden Ulrike H. Mitchell David T. Fullwood |
| author_sort | Alex M. Wonnacott |
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| description | Flexible high-deflection strain gauges have been demonstrated to be cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, particularly during dynamic motion. In addition to the non-linear viscoelastic behavior of the strain gauge material itself, the dynamic response of the sensors is even more difficult to capture due to spikes in the resistance during strain path changes. Hence, models for extracting strain from resistance measurements of the gauges most often only work well under quasi-static conditions. The present work develops a novel model that captures the complete dynamic strain–resistance relationship of the sensors, including resistance spikes, during cyclical movements. The forward model, which converts strain to resistance, comprises the following four parts to accurately capture the different aspects of the sensor response: a quasi-static linear model, a spike magnitude model, a long-term creep decay model, and a short-term decay model. The resulting sensor-specific model accurately predicted the resistance output, with an R-squared value of 0.90. Additionally, an inverse model which predicts the strain vs. time data that would result in the observed resistance data was created. The inverse model was calibrated for a particular sensor from a small amount of cyclic data during a single test. The inverse model accurately predicted key strain characteristics with a percent error as low as 0.5%. Together, the models provide new functionality for interpreting high-deflection strain sensors during dynamic strain measurement applications, including wearables sensors used for biomechanical modeling and analysis. |
| format | Article |
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| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-1264366ca9bc49ae9e8987fdbbb2b2b72025-08-20T02:01:19ZengMDPI AGSensors1424-82202024-12-012424819210.3390/s24248192Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain GaugesAlex M. Wonnacott0Anton E. Bowden1Ulrike H. Mitchell2David T. Fullwood3Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USADepartment of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USADepartment of Exercise Sciences, Brigham Young University, Provo, UT 84062, USADepartment of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USAFlexible high-deflection strain gauges have been demonstrated to be cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, particularly during dynamic motion. In addition to the non-linear viscoelastic behavior of the strain gauge material itself, the dynamic response of the sensors is even more difficult to capture due to spikes in the resistance during strain path changes. Hence, models for extracting strain from resistance measurements of the gauges most often only work well under quasi-static conditions. The present work develops a novel model that captures the complete dynamic strain–resistance relationship of the sensors, including resistance spikes, during cyclical movements. The forward model, which converts strain to resistance, comprises the following four parts to accurately capture the different aspects of the sensor response: a quasi-static linear model, a spike magnitude model, a long-term creep decay model, and a short-term decay model. The resulting sensor-specific model accurately predicted the resistance output, with an R-squared value of 0.90. Additionally, an inverse model which predicts the strain vs. time data that would result in the observed resistance data was created. The inverse model was calibrated for a particular sensor from a small amount of cyclic data during a single test. The inverse model accurately predicted key strain characteristics with a percent error as low as 0.5%. Together, the models provide new functionality for interpreting high-deflection strain sensors during dynamic strain measurement applications, including wearables sensors used for biomechanical modeling and analysis.https://www.mdpi.com/1424-8220/24/24/8192nanocompositesviscoelasticityhigh-deflection strain gaugesmodeling |
| spellingShingle | Alex M. Wonnacott Anton E. Bowden Ulrike H. Mitchell David T. Fullwood Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges Sensors nanocomposites viscoelasticity high-deflection strain gauges modeling |
| title | Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges |
| title_full | Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges |
| title_fullStr | Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges |
| title_full_unstemmed | Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges |
| title_short | Analyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges |
| title_sort | analyzing and modeling the dynamic electrical characteristics of nanocomposite large range strain gauges |
| topic | nanocomposites viscoelasticity high-deflection strain gauges modeling |
| url | https://www.mdpi.com/1424-8220/24/24/8192 |
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