Multimodal Flexible Sensor for the Detection of Pressing-Bending-Twisting Mechanical Deformations

Flexible sensors are increasingly significant in applications such as smart wearables and human-computer interactions. However, typical flexible sensors are spatially limited and can generally detect only one deformation mode. This study presents a novel multimodal flexible sensor that combines three sensing units: optoelectronics, ionic liquids, and conductive fabrics. It employs a sophisticated superposition and combination of the three sensing methods to achieve up to eight mechanical deformations, including pressing, bending, twisting, and combinations thereof, all within a very small sensor space. This sensor has excellent detection performance, high sensitivity (optoelectronics 4.312, ionic liquid 8.186, conductive fabric 2.438), a wide measurement range (pressing 0-75 kPa, bending 0-90°, and twisting 0-180°), and good consistency and repeatability. To address the signal coupling problem in multimode sensors, a deep learning method based on the Transformer is combined to provide precise decoupling of multimode signals and high-precision characterization of each mechanical deformation. Finally, the wrist joint experiments demonstrate the sensor's versatile uses in human-computer interaction.