4.7 Article

Development of MMG sensors using PVDF piezoelectric electrospinning for lower limb rehabilitation exoskeleton

Journal

SENSORS AND ACTUATORS A-PHYSICAL
Volume 301, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.sna.2019.111708

Keywords

Mechanomyography (MMG); Electromyography (EMG); Lower limb rehabilitation exoskeleton (LLRE); Piezoelectric; Polyvinylidene difluoride (PVDF); Near-field electrospinning technology

Funding

  1. Ministry of Science and Technology, Taiwan
  2. MOST [106-2221-E-110-032-MY3]

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In this study, a new type of fiber-based mechanomyography (MMG) sensor was developed and used as a motion on/off trigger sensor for a lower limb rehabilitation exoskeleton (LLRE). Piezoelectric material, polyvinylidene difluoride (PVDF), was applied to fabricate a MMG sensor, using the near-field electro-spinning technology to electrically spin PVDF fibers to similar to 5-10 mu m in diameter. PVDF fibers attached on an interdigitated (IDT) electrode with different pole pairs and interspaces were packaged into a MMG sensor. This MMG sensor was stuck on the thigh muscles to detect and acquire human motion intention signal, then trigger the controller and actuate the LLRE. The LLRE multi-axis control system included a master and four slave controllers. The master controller released the command signal to control the slave controllers via controller area network (CAN). A multi-axis control system was developed to actuate the joints of hips and knees of both legs by the LLRE. In the study, commercial electromyography (EMG) sensors were also to compare with the as-made MMG sensors. Results showed that the maximum signal amplitude of the commercail EMG sensor was about similar to 0.2 V, whereas the MMG sensor was about similar to 2.8 V. The signal-to-noise ratio (SNR) of EMG was about similar to 4, while that of MMG was about similar to 25. From physiological signals captured from the MMG sensor for the human walking with the LLRE, this new sensor improved the sensitivity in driving the LLRE. (C) 2019 Elsevier B.V. All rights reserved.

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