Stable epidermal electronic device with strain isolation induced by in situ Joule heating

Epidermal electronics play increasingly important roles in human-machine interfaces. However, their efficient fabrication while maintaining device stability and reliability remains an unresolved challenge. Here, a facile in situ Joule heating method is proposed for fabricating stable epidermal electronics on a polyvinyl alcohol (PVA) substrate. Benefitting from the precise control of heating locations, the crystallization and enhanced rigidity of PVA are restricted to desired areas, leading to strain isolation of the active regions. As a result, the electronic device can be conformably attached to skin while showing negligible degradation in device performance during deformation. Based on this method, a flexible surface electromyography (sEMG) sensor with outstanding stability and highly comfortable wearability is demonstrated, showing high accuracy (91.83%) for human hand gesture recognition. These results imply that the fabrication method proposed in this research is a facile and reliable approach for the fabrication of epidermal electronics.

Highly Robust and Wearable Facial Expression Recognition via Deep-Learning-Assisted, Soft Epidermal Electronics

The facial expressions are a mirror of the elusive emotion hidden in the mind, and thus, capturing expressions is a crucial way of merging the inward world and virtual world. However, typical facial expression recognition (FER) systems are restricted by environments where faces must be clearly seen for computer vision, or rigid devices that are not suitable for the time-dynamic, curvilinear faces. Here, we present a robust, highly wearable FER system that is based on deep-learning-assisted, soft epidermal electronics. The epidermal electronics that can fully conform on faces enable high-fidelity biosignal acquisition without hindering spontaneous facial expressions, releasing the constraint of movement, space, and light. The deep learning method can significantly enhance the recognition accuracy of facial expression types and intensities based on a small sample. The proposed wearable FER system is superior for wide applicability and high accuracy. The FER system is suitable for the individual and shows essential robustness to different light, occlusion, and various face poses. It is totally different from but complementary to the computer vision technology that is merely suitable for simultaneous FER of multiple individuals in a specific place. This wearable FER system is successfully applied to human-avatar emotion interaction and verbal communication disambiguation in a real-life environment, enabling promising human-computer interaction applications.