Encoding of multi-modal emotional information via personalized skin-integrated wireless facial interface.

Human affects such as emotions, moods, feelings are increasingly being considered as key parameter to enhance the interaction of human with diverse machines and systems. However, their intrinsically abstract and ambiguous nature make it challenging to accurately extract and exploit the emotional information. Here, we develop a multi-modal human emotion recognition system which can efficiently utilize comprehensive emotional information by combining verbal and non-verbal expression data.

Digital Mechanical Metamaterial: Encoding Mechanical Information with Graphical Stiffness Pattern for Adaptive Soft Machines.

Inspired by the adaptive features exhibited by biological organisms like the octopus, soft machines that can tune their shape and mechanical properties have shown great potential in applications involving unstructured and continuously changing environments. However, current soft machines are far from achieving the same level of adaptability as their biological counterparts, hampered by limited real-time tunability and severely deficient reprogrammable space of properties and functionalities. As a steppingstone toward fully adaptive soft robots and smart interactive machines, an encodable multifunctional material that uses graphical stiffness patterns is introduced here to in situ program versatile mechanical capabilities without requiring additional infrastructure.