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3D printed triboelectric nanogenerator as self-powered human-machine interactive sensor for breathing-based language expression

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Abstract

Human-machine interfaces (HMIs) are important windows for a human to communicate with the outside world. The current HMI devices such as cellphones, tablets, and computers can be used to help people with aphasia for language expression. However, these conventional HMI devices are not friendly to some particular groups who also lose their abilities of physical movements like in the intensive care unit (ICU) or vegetative patients to realize language expression. Herein, we report a breath-driven triboelectric nanogenerator (TENG) acting as a HMI sensor for language expression through human breathing without voice controls or manual operations. The TENG is integrated within a mask and fabricated via a three-dimensional (3D) printing method. When wearing the mask, the TENG can produce responsive electric signals corresponding to the airflow from breathing, which is capable of recognizing human breathing types with different intensities, lengths, and frequencies. On the basis of the breathing recognition ability, a breathing-based language expressing system is further developed through introducing the Morse code as a communication protocol. Compared with conventional language expressing devices, this system can extract subjective information of a person from breathing behaviors and output corresponding language text, which is not relying on voices or physical movements. This research for the first time introduces the self-powered breathing-based language expressing method to the field of HMI technology by using a 3D printed TENG, and could make HMI interactions become more friendly and fascinating.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 62074137) and the Key Research, Development, and Promotion Program of Henan Province (No. 202102210004).

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Author notes

  1. Pengcheng Zhu and Baosen Zhang contributed equally to this work.

Authors and Affiliations

  1. Key Laboratory of Materials Physics, Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou, 450001, China

    Pengcheng Zhu, Baosen Zhang, Hongyi Wang, Yiheng Wu, Hengjun Cao, Liubing He, Chaoyue Li, Xuepeng Luo, Xing Li & Yanchao Mao

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  1. Pengcheng Zhu
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Correspondence to Yanchao Mao.

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3D printed triboelectric nanogenerator as self-powered human-machine interactive sensor for breathing-based language expression

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Zhu, P., Zhang, B., Wang, H. et al. 3D printed triboelectric nanogenerator as self-powered human-machine interactive sensor for breathing-based language expression. Nano Res. 15, 7460–7467 (2022). https://doi.org/10.1007/s12274-022-4339-x

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  • DOI: https://doi.org/10.1007/s12274-022-4339-x

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