Prototyping shape-sensing fabrics through physical simulation
Embedding sensors into fabrics can leverage substantial improvements in application areas like working safety, 3D modeling or health-care, for example to recognize the risk of developing skin ulcers. Finding a suitable setup and sensor combination for a shape-sensing fabric currently relies on the intuition of an application engineer. We introduce a novel approach: Simulating the shape-sensing fabric first and optimize the design to achieve better real-world implementations. In order to enable developers to easily prototype their shape-sensing scenario, we have implemented a framework that enables soft body simulation and virtual prototyping. To evaluate our approach, we investigate the design of a system detecting sleeping postures. We simulate potential designs first, and implement a bed cover consisting of 40 distributed acceleration sensors. The validity of our framework is confirmed by comparing the simulated and real evaluation results. We show that both approaches achieve similar performances, with an F-measure of 85% for the virtual prototype and 89% for the real-world implementation.