Integrating soft sensor systems using conductive thread

Abstract

We are part of a growing community of researchers who are developing a new class of soft machines. By using mechanically soft materials (MPa modulus) we can design systems which overcome the bulk-mechanical mismatches between soft biological systems and hard engineered components. To develop fully integrated soft machines—which include power, communications, and control sub-systems—the research community requires methods for interconnecting between soft and hard electronics.Sensors based upon eutectic gallium alloys in microfluidic channels can be used to measure normal and strain forces, but integrating these sensors into systems of heterogeneous Young’s modulus is difficult due the complexity of finding a material which is electrically conductive, mechanically flexible, and stable over prolonged periods of time. Many existing gallium-based liquid alloy sensors are not mechanically or electrically robust, and have poor stability over time.We present the design and fabrication of a high-resolution pressure-sensor soft system that can transduce normal force into a digital output. In this soft system, which is built on a monolithic silicone substrate, a galinstan-based microfluidic pressure sensor is integrated with a flexible printed circuit board. We used conductive thread as the interconnect and found that this method alleviates problems arising due to the mechanical mismatch between conventional metal wires and soft or liquid materials.Conductive thread is low-cost, it is readily wetted by the liquid metal, it produces little bending moment into the microfluidic channel, and it can be connected directly onto the copper bond-pads of the flexible printed circuit board. We built a bridge-system to provide stable readings from the galinstan pressure sensor. This system gives linear measurement results between 500–3500 Pa of applied pressure.We anticipate that integrated systems of this type will find utility in soft-robotic systems as used for wearable technologies like virtual reality, or in soft-medical devices such as exoskeletal rehabilitation robots.