A self-powered multifunctional dressing for active infection prevention and accelerated wound healing.

Interruption of the wound healing process due to pathogenic infection remains a major health care challenge. The existing methods for wound management require power sources that hinder their utilization outside of clinical settings. Here, a next generation of wearable self-powered wound dressing is developed, which can be activated by diverse stimuli from the patient's body and provide on-demand treatment for both normal and infected wounds. The highly tunable dressing is composed of thermocatalytic bismuth telluride nanoplates (Bi2Te3 NPs) functionalized onto carbon fiber fabric electrodes and triggered by the surrounding temperature difference to controllably generate hydrogen peroxide to effectively inhibit bacterial growth at the wound site. The integrated electrodes are connected to a wearable triboelectric nanogenerator (TENG) to provide electrical stimulation for accelerated wound closure by enhancing cellular proliferation, migration, and angiogenesis. The reported self-powered dressing holds great potential in facilitating personalized and user-friendly wound care with improved healing outcomes.

A smart glove with integrated triboelectric nanogenerator for self-powered gesture recognition and language expression.

Flexible electronics with great functional characteristics have proved to be a stepping stone in the field of wearable devices. Amongst all, gesture-sensing techniques have been widely studied for human-machine interfaces. In this paper, we propose a self-powered gesture-sensing system attached to the back of the hands, which has the capability of distinguishing hand gestures by measuring the triboelectric nanogenerator output signal. By attaching the sensor on the back of the hand, we can sense the displacement of tendons to detect the gestures. In addition, humidity resistance and durability of the device were tested and validated. Furthermore, we have established a set of rules to define the relationship between gestures and corresponding English letters. Therefore, the proposed sensor can further serve as an electronic sign language translator by converting gestures into words. Finally, we can integrate this system into gloves to enhance the applicability and utility. Overall, we have developed a real-time self-powered back-of-hand sensing system which can recognize various hand gestures.