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A hybrid sensor for motor tics recognition based on piezoelectric and triboelectric design and fabrication
Jie Wang, Chih Chia Chen, Chin Yau Shie, Tomi T. Li,
Yiin Kuen Fuh
機械工程學系
研究成果
:
雜誌貢獻
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期刊論文
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同行評審
18
引文 斯高帕斯(Scopus)
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Keyphrases
Recognition-based
100%
Triboelectricity
100%
Motor Tics
100%
Hybrid Sensor
100%
Poly(vinylidene fluoride-trifluoroethylene)
75%
Nanofibers
50%
Polydimethylsiloxane
25%
Energy Harvesting
25%
Deep Learning
25%
Recognition Rate
25%
Near-field Electrospinning
25%
Output Performance
25%
Triboelectric Nanogenerator
25%
Long Short-term Memory
25%
Recurrent Neural Network
25%
Signal Recognition
25%
Piezoelectric Nanogenerator
25%
Voltage Output
25%
Self-powered
25%
Recognition System
25%
Deep Learning Model
25%
Novel Hybrids
25%
Self-powered Sensor
25%
Wearable Electronics
25%
Biomechanical Energy
25%
Electrospinning Technique
25%
Thin-walled
25%
Self-sensing
25%
Tourette Syndrome
25%
Nanogenerator
25%
Smart Patch
25%
Electronic Products
25%
Flexible Printed Circuit Board
25%
Skin Patch
25%
Artificial Skin
25%
Plant Bionics
25%
Hybrid Modulation
25%
Piezoelectric Polymer
25%
Engineering
Piezoelectric
100%
Self-Powered
100%
Nanofiber
66%
Bionics
66%
Porosity
66%
Deep Learning Method
66%
Energy Harvesting
33%
Polydimethylsiloxane
33%
Output Voltage
33%
Triboelectric Nanogenerators
33%
Performance Output
33%
Recognition Rate
33%
Long Short-Term Memory
33%
Wearable Electronics
33%
Printed Circuit Board Substrate
33%
Electrospinning Process
33%
Electronic Product
33%
Flexible Printed Circuit Board
33%
Piezoelectric Polymer
33%
Recurrent Neural Network
33%
Chemical Engineering
Deep Learning Method
100%
Bionics
100%
Recurrent Neural Network
50%
Long Short-Term Memory
50%
Polydimethylsiloxane
50%
Material Science
Piezoelectricity
100%
Nanofiber
50%
Electronic Circuit
25%
Electrospinning
25%
Self-powered Sensor
25%