Soft Material and Algorithmic Innovations for the Improvement of Existing and the Development of Future Wearable Devices

 Wearable electronic devices are growing in popularity because of their potential to portably interface with the human body and provide continuous user-specific sensing and feedback in new and unregulated environments. However, the algorithmic shortcomings and the rigid, bulky, or tethered form factors of wearable devices often cause them to be difficult to use and adapt poorly to various body types and environments, which limits their adoption. To unlock the full potential of wearable devices to be easy-to-use, portable, and accurate across users and environments, both material and algorithmic innovations are needed to develop wearable devices that are smarter and softer. To develop smarter wearable devices, studies have investigated novel integration strategies, sensor fusion algorithms, and the application of machine learning to improve wearable device usability and the robustness of on-body sensing methods. To develop softer wearable devices, studies have investigated new electrically, magnetically, and thermally responsive soft material architectures to enable new approaches toward sensing and actuation. In this dissertation, I consider these approaches and commonly utilized components for wearable devices such as inertial and magnetic sensors, magnetic materials, and optical sensors, and investigate algorithmic and material approaches to improve the usability, form factor, and adaptability of technology for wearable devices. This dissertation focuses on the introduction and investigation of (1) an auto-establishing kinematic framework for a network of wireless inertial sensors, (2) a magnetically responsive elastomer thin film that has two configurations of deformation in response to the state of an electropermanent magnet, and (3) a soft deformable magnetic ring system that can be used to measure normal and shear displacement on rigid and compliant substrates. Together, this work explores algorithmic and soft material innovations to take steps toward improving wearable device technology and further encourage their widespread adoption.