ASER Research on Self-Powered Sensors for Sign Language Interpretation got covered by multiple National Medias
In this work, a highly sensitive and facile fabricated self-powered triboelectric flex sensor (STFS) is presented which can efficiently detect the finger bending motion and monitor the hand gestures. Drawn inspiration from the highly sensitive human skin dermis-epidermis interlocked haptic performance, the fabricated STFS consists of randomly distributed microstructured (RDM) triboelectric layers imprinted from an emery paper through thermal embossing technology, achieving a high sensitivity of 0.77 VkPa−1 along with rapid rise time of 83 ms and high stability (>100,000 loading-unloading cycles). Also, the proposed flex sensor exhibits an ultrawide range of pressure detection from 0.2 kPa to 500 kPa. Moreover, a real-time application of sign language interpretation by detecting finger gestures and converting those gestures into voice and text through smartphone application is successfully demonstrated. This facile fabrication process paved a highly cost-effective, large scalable and time-efficient development of the self-powered flex sensor device with superior sensing properties, and high mechanical robustness for hand gesture monitoring and sign language interpretation system as well as human-machine interface application.
