A novel dual-core optical fiber made from stretchable materials offers a flexible approach to optomechanical sensing, researchers report. It can distinguish and measure complex mechanical movement using only a single sensor and the changing colors of light, which the researchers demonstrated by incorporating their sensor into a stretchable glove. In the glove, it successfully detected various complex finger movements and pressing gestures in real time. Distributed fiber-optic sensor (DFOS) systems are used to observe various physical attributes, such as strain, pressure, vibration and temperatures. However, current systems, which are often based on non-stretchable silica-based optical fibers, are generally restricted to monitoring rigid objects and limited by their ability to measure only a single attribute without large complex optical sensors and/or advanced computation. As a result, DFOS systems are incompatible with fields like soft robotics or biomedicine. Hedan Bai and colleagues developed a stretchable DFOS sensor system consisting of two stretchy polyurethane optic fiber cores, molded and wrapped together in a silicone coating - one clear core and one interspersed with several discrete areas containing differentcolored chromatic dyes. When undeformed, white light passing through each of SLIMS dual cores remains white. However, deformations along its length - bends, stretches or presses - result in geometric changes in the optical path of the light, which influences the color light output from the dyed core, shifting it towards the dye color in the region where the deformation occurred. Different types and magnitude of deformation result in a specific chromatic pattern in the light between the two cores. By measuring the color and intensity of the light output from each of the adjacent cores, the location, magnitude and type of deformation can be determined. To further demonstrate SLIMS multimodal sensing abilities, Bai et al. incorporated the system into a stretchable glove, which could detect and accurately reconstruct various complex finger movements and presses simultaneously and in real-time using only a single sensor.