Comparative Analysis of Knitting Patterns for Wearable Resistive Strain Sensors in Joint Motion Measurements

E-textiles, particularly knitted resistive strain sensors, have been proposed for joint motion measurements. Although combining non-elastic conductive yarns with elastic non-conductive yarns has been shown to enhance the performance of the sensors, the specific integration parameters, particularly the knitting patterns, have yet to be thoroughly investigated. To address this gap, this paper provides a comparative analysis of plain weft-knitted patterns for resistive strain sensors, utilizing conductive silver-coated yarn and Lycra-based elastic yarn. The findings suggest that the plated knitting patterns, with conductive material on the knit side and elastic yarn on the purl side, enhance sensor performance. These sensors achieve a gauge factor of 14.616 during stretching and 13.300 during release, with effective working ranges from 0 to 40.3% in the stretch direction and 0 to 47.7% in the release direction, respectively. Taking elbow joint angle detection as an example, we demonstrate that performance degradation due to resistance drift during continuous strain can be effectively mitigated by employing relative resistance measurement rather than absolute ones and removing a linear trend from the data before feeding it into a machine learning model. This work offers valuable insights into how fabrication methods impact sensor characteristics and further the performance of joint angle measurements, and outlines directions for improvements.