4.6 Article

A self-powered intelligent glove for real-time human-machine gesture interaction based on piezoelectric effect of T-ZnO/PVDF film

Journal

JOURNAL OF PHYSICS D-APPLIED PHYSICS
Volume 55, Issue 19, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.1088/1361-6463/ac5192

Keywords

self-powered; intelligent glove; piezoelectric effect; wearable electronics; gesture recognition

Funding

  1. National Natural Science Foundation of China [11674048]
  2. Sichuan Science and Technology Program [2021YFG0140]

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This study presents a self-powered intelligent glove based on piezoelectric motion sensor arrays for real-time gesture recognition. The system can be comfortably worn on the hand and wirelessly transmit gesture signals to smartphones for recognition and translation. This research contributes to the development of human-machine interaction systems.
In the emerging field of human-machine interaction, intelligent gesture recognition techniques have great application prospects. The traditional use of rigid and over-sized power units has restrained the development of wearable gesture recognition systems. Here, we present a self-powered intelligent glove based on piezoelectric motion sensor arrays for real-time gesture recognition. The system can be confortably worn on human hands, and mainly consists of three parts: a flexible piezoelectric motion sensor based on T-ZnO/PVDF film (T-ZnO, tetrapod ZnO nanostructures), a signal processing module for analyzing the sensing information, and a Bluetooth unit for wireless communication. The system can work without external power, and the piezoelectric output can act as both the energy source of the system and the sensing signal. The working mechanism can be attributed to the piezoelectric effect of T-ZnO/PVDF composites and with flexion and extension of the fingers, a series of pulse signals can be generated and converted into specific corresponding codes. The sensing signal can be wirelessly transmitted to smartphones through the Bluetooth unit, and the phone can recognize the codes corresponding to sign language actions and translate them. This work can potentially promote the development of the next generation of human-machine interaction systems and expand the scope of self-powered techniques and wearable electronics.

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