Triboelectrification based motion sensor for human-machine interfacing

Weiqing Yang, Jun Chen, Xiaonan Wen, Qingshen Jing, Jin Yang, Yuanjie Su, Guang Zhu, Wenzuo Wu, Zhong Lin Wang

Research output: Journal PublicationArticlepeer-review

131 Citations (Scopus)

Abstract

We present triboelectrification based, flexible, reusable, and skin-friendly dry biopotential electrode arrays as motion sensors for tracking muscle motion and human-machine interfacing (HMI). The independently addressable, self-powered sensor arrays have been utilized to record the electric output signals as a mapping figure to accurately identify the degrees of freedom as well as directions and magnitude of muscle motions. A fast Fourier transform (FFT) technique was employed to analyse the frequency spectra of the obtained electric signals and thus to determine the motion angular velocities. Moreover, the motion sensor arrays produced a short-circuit current density up to 10.71 mA/m2, and an open-circuit voltage as high as 42.6 V with a remarkable signal-to-noise ratio up to 1000, which enables the devices as sensors to accurately record and transform the motions of the human joints, such as elbow, knee, heel, and even fingers, and thus renders it a superior and unique invention in the field of HMI.

Original languageEnglish
Pages (from-to)7479-7484
Number of pages6
JournalACS applied materials & interfaces
Volume6
Issue number10
DOIs
Publication statusPublished - 28 May 2014
Externally publishedYes

Keywords

  • fast Fourier transform
  • human joints
  • human-machine interfacing
  • motion sensor
  • self-powered
  • triboelectrification

ASJC Scopus subject areas

  • Materials Science (all)

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