Intelligent Textiles for Physical Human-Environment Interactions

Abstract

Physical human-environment interaction is a fundamental aspect of our daily lives, involving the constant use of our sensory and motor systems to extract, process, and communicate information. Capturing, modeling, and augmenting these physical interactions are crucial for enhancing human well-being and promoting intelligent system designs. However, the pervasive and diverse nature of these interactions poses challenges that require scalable and adaptable systems. To address these challenges, I adopt an integrated approach that combines digital fabrication and machine learning techniques. The approach involves developing a digital design and fabrication pipeline to integrate sensing and actuation capabilities into textile-based platforms, and capturing diverse datasets on human-environment interactions to enable intelligent and adaptive applications. The dissertation showcases past and ongoing works on intelligent textile-based sensing and actuating platforms that embody this approach, including tactile sensing garments, an intelligent carpet for human pose estimation, programmable textile-based actuators for assistive wearables, and smart gloves for adaptive tactile interaction transfer. Moving forward, I aim to explore applications of the developed systems in healthcare, robotics, and human behaviors intervention, and expand to diverse sensing and actuation modalities.