Piezoelectric sensor based on graphene-doped PVDF nanofibers for sign language translation

Shuai Yang,Shengbo Sang,Hulin Zhang,Xiaojing Cui,Zhiyi Zhang,Rui Guo

doi:10.3762/bjnano.11.148

Shuai Yang, Shengbo Sang + Show 4 more

Open Access

https://doi.org/10.3762/bjnano.11.148

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Abstract

The tracking of body motion, such as bending or twisting, plays an important role in modern sign language translation. Here, a subtle flexible self-powered piezoelectric sensor (PES) made of graphene (GR)-doped polyvinylidene fluoride (PVDF) nanofibers is reported. The PES exhibits a high sensitivity to pressing and bending, and there is a stable correlation between bending angle and piezoelectric voltage. The sensitivity can be adjusted by changing the doping concentration of GR. Also, when the PES contacts a source of heat, a pyroelectric signal can be acquired. The positive correlation between temperature and signal can be used to avoid burns. The integrated sensing system based on multiple PESs can accurately recognize the action of each finger in real time, which can be effectively applied in sign language translation. PES-based motion-tracking applications have been effectively used, especially in human–computer interaction, such as gesture control, rehabilitation training, and auxiliary communication.

Highlights

Sign language, as a communication method that works based on gestures, plays an important role for people who are hearingimpaired or unable to speak
We propose a flexible self-powered piezoelectric sensor (PES) based on graphene (GR)-doped polyvinylidene fluoride (PVDF) nanofibers
To further study the performance of this piezoelectric material, a bending-induced piezoelectric model was constructed, and the calculated stress and potential distribution were obtained through finite element analysis, as shown in Figure 1c and Figure 1d

Summary

Introduction

As a communication method that works based on gestures, plays an important role for people who are hearingimpaired or unable to speak. Real-time translation systems based on gestures are gradually showing rich application prospects in sign language learning and daily communication. We propose a flexible self-powered piezoelectric sensor (PES) based on graphene (GR)-doped PVDF nanofibers.

Results

Conclusion