Inferring complex textile shape from an integrated carbon black-infused ecoflex-based bend and stretch sensor array

We demonstrate how an array of custom-made strain and bend sensors could be integrated into a stretchable sleeve to infer the textile deformation. The angles and elongation measured by the sensors can be used by an optimisation-based algorithm to infer the textile geometrical model by minimising a loss function. We evaluated this on 4 shapes highlighting different body-part characteristics. We demonstrated that a 3.11 mm reconstruction error on complex geometries can be reduced up to 0.08 mm with the computation of angles. This proves the potential of the proposed prototype for capturing the shape of a body parts, muscle density measurement, body shape acquisition, the fabrication of orthoses and prostheses, or to perform movement sensing for human activity recognition, where it could be included in sports leggings for biomechanical analysis, or in everyday garments for motion and gesture sensing.