Quantifying the Human Perception: Development and Characterization of Textile-Based Capacitive Strain and Pressure Sensors

Abstract

In the research field of smart textiles, one main goal concerns quantifying environmental forces acting on the wearer's body since textiles, acting as the boundary between the two, are an excellent way of integrating sensors. Integrating strain and pressure sensors into wearables promises a simple way of monitoring a person's posture and forces acting on their body. Sensors relying on a capacitive measuring principle are highly suitable for this, as they are less sensitive to changes in temperature than resistive or inductive types. In this paper, textile-based capacitive sensors are produced by braiding conductive yarns with and without an electrically insulating TPU sheath. The produced sensors are analyzed in cyclic strain and compression tests. Moreover, their behavior under changing temperatures is tested to prove their resilience against environmental changes. To extend their capabilities from an integral measurement to a localized assessment of the strain, time-domain-reflectometry (TDR) is employed. Finally, the sensors are integrated into a flexible actuated bending beam, and their adoption for soft robotics is discussed. Strain is tested cyclically, showing good long-term stability. Pressure sensitivity is measured in a static compression test under increasing force. TDR is used to localize strain in two discreet sections of the sensor. Although strain could not be quantified through TDR, characteristic points in the measured response signal indicating the position of the strain were identified. Textile-based capacitive sensors are suitable for strain up to 10 % and pressure up to 8 N. The determined gauge factors are satisfactory, with strain sensors inherently having a higher gauge factor than pressure sensors. Furthermore, they display good long-term stability and no adverse reaction to changes in temperature. TDR is proven to provide localization of strain in flexible sensors.