Knit structure impacts sensor signals and joint angle accuracy
Knit-Structure Effects on Electromechanical Metrics and Their Correlation with Joint-Angle Estimation Error in Knitted Strain Sensors
Human-Computer Interaction
Summary
Measuring joint movement using stretchy knitted sensors could help in sports and rehab, but it’s unclear how the knit design affects accuracy. The authors tested different stitches and sizes to see which properties of the sensors influence how well they track bending. They found that some measures, like how sensitive the sensor is and its normal resistance, depend on the knit pattern and relate to how well joint angles are estimated. This means simple stretch tests can help weed out bad designs, but for best results, sensors must be tested in real bending conditions.
What this means in practice
- •For wearable device engineers: Select knitting designs and stitch sizes that optimize sensor accuracy in wearable joint motion monitors by screening with tension tests.
- •For rehabilitation equipment makers: Improve joint bending sensors in rehab devices by focusing on gauge factor and resistance patterns linked to prediction errors.
Authors
Annika Eloranta, Zhuchenyang Liu, Iiro Naulapaa, Iida Arvola, Yao Zhang, Anna-Mari Leppisaari, Lulu Xu, Yu Xiao
Abstract
Knitted resistive strain sensors show strong promise for joint motion sensing in sports and rehabilitation, but the linkage between sensor design and in situ performance remains unclear. We investigate how knit structure and machine settings (e.g., stitch size) shape electromechanical properties and which metrics predict sensing performance during bending. Sensors spanning seven common knit structures at two stitch sizes were fabricated, characterized under uniaxial cyclic tension, and evaluated on a joint emulating bending rig. Joint-angle estimation was assessed with machine learning models, and correlations with electromechanical metrics were analyzed. Experimental results show that, among six common metrics, gauge factor and baseline resistance are largely set by knit structure, while working range, linear range, hysteresis, and cyclic stability vary only modestly across designs. Gauge factor correlates negatively and baseline resistance positively with joint-angle estimation error, mainly in lower-sensitivity designs, whereas the other metrics have weak or no predictive value. These results support using uniaxial tensile tests to screen out weak designs, while underscoring the need for joint-relevant evaluation and application-specific metrics to identify top performers.