Nonlinear Strain Engineering via Meta-Material Substrates for Flexible Sensors With Simultaneously Enhanced...

Flexible strain sensors face an unresolved trade-off between sensitivity and sensing range. We present a meta-material-based sensor platform (meta-sensor) that overcomes this by engineering local strain input to the sensing element. A strain-stiffening curved spiral structure and a uniform-stiffness kirigami-patterned structure connected in series produce nonlinear strain partitioning: before mechanical transition, global strain concentrates at the sensor interface to amplify sensitivity; after transition, strain redistributes to extend sensing range. Integrating a kirigami crack-based sensor (maximum applied strain range of 50%) onto this composite substrate extends the operational range to 125% applied strain-a 2.5× range extension (from 50% to 125%) - while raising the mid-range response to ≈3.5× that of a wide-range reference sensor. The platform is validated in respiratory monitoring across rest and vigorous exercise, and knee rehabilitation tracking from early to late recovery. This meta-material substrate approach offers a generalizable, material-independent strategy for simultaneously achieving high sensitivity and wide sensing range.