The Role of Length Shift in Assessing Force and Resistivity for Optimized e-Textile Sensors

Wearable sensors are becoming increasingly ubiquitous, revolutionizing the way we extract meaningful data from human subjects and compliant objects, such as soft and collaborative robots. E-textiles have emerged as a cost-effective solution that offers an optimal balance between sensitivity and mechanical compliance. However, current evaluations of e-textiles designed to transduce force into electrical signals often overlook the impact of natural length variations caused by mechanical stretching. This factor can compromise long-term accuracy, underscoring the need for a more comprehensive characterization approach. This work introduces and validates a novel assessment protocol that simultaneously tracks resistivity, force, and length variations in a conductive thread during different electro mechanical tests. The measurement system incorporates Wheatstone bridges as a front end to optimize the dynamic range of resistive readings and load cell signals, while employing an image processing approach to ensure precise length tracking. The results indicate a progressive increase in length after multiple stretch-recovery cycles, demonstrating how resistance and resting length evolve over repeated mechanical interactions. This approach facilitates the development of textile-based sensors and resistivity models that account for length variations during mechanical work, improving accuracy, and expanding the range of potential applications.