Journal
NANO ENERGY
Volume 76, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.nanoen.2020.105029
Keywords
Near-field electrospinning (NFES); Polyvinylidene fluoride (PVDF); Nano /micro fibers (NMFs); Biomimetic hybrid self-powered sensors (BHSS); Long short-term memory (LSTM)
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Funding
- Ministry of Science and Technology, Taiwan [MOST 105-2221-E-008-049-MY3, MOST 108-2221-E-008-070-MY3]
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Near-field electrospinning (NFES) is a site addressable microfabrication process and is utilized to deposit the micro/nano polyvinylidene fluoride (PVDF) fibers arrays on printed circuit board nanofiber-based based piezoelectric sensor architectures. In addition, a biomimetic and flexible hybrid self-powered sensors (BHSS) was created by hybridizing both Cu - biomimetic Polydimethylsiloxane triboelectric sensors to enhance the energy-harvesting characteristic. The optimized BHSS had open-circuit voltage (V-OC) of 15 V and 115 nA of short-circuit current (I-SC) and a maximum average power density is 675 mu W m(-2) with a load of 10 M Omega. Furthermore, an intelligent glove and the force sensor with are successively confirmed that the developed BHSS has promising applications in wearable self-power sensor technology. The machine learning algorithm of Long Short-Term Memory (LSTM) in the context of gesture recognition was used and effectively distinguish five human actions satisfactorily. LSTM based real-time electrical signals of five gestures dataset with varying duration and complexity can achieve an overall classification rate of 82.3%.
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