| dc.description.abstract | 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. However, capturing, analyzing, and reproducing these interactions pose significant challenges due to their pervasive, variable, and prolonged nature, as well as their unique character for each individual. Despite these challenges, it is essential to develop systems that can accurately capture and reproduce human-environment interactions for a wide range of applications, including human behavior studies, health monitoring, human-computer interactions, and robot imitation learning. This thesis focuses on developing seamlessly integrated, scalable manufactured sensing and actuating systems, as well as advanced computational pipelines to capture, analyze, and reproduce adaptive ubiquitous physical human-environment interactions. | |
