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Wen J. Li
Researcher at City University of Hong Kong
Publications - 409
Citations - 7378
Wen J. Li is an academic researcher from City University of Hong Kong. The author has contributed to research in topics: Dielectrophoresis & Carbon nanotube. The author has an hindex of 39, co-authored 383 publications receiving 6348 citations. Previous affiliations of Wen J. Li include Hong Kong Applied Science and Technology Research Institute & The Chinese University of Hong Kong.
Papers
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Journal ArticleDOI
MEMS Accelerometer Based Nonspecific-User Hand Gesture Recognition
Ruize Xu,Shengli Zhou,Wen J. Li +2 more
TL;DR: A recognition algorithm based on sign sequence and template matching as presented in this paper can be used for nonspecific-users hand-gesture recognition without the time consuming user-training process prior to gesture recognition.
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A laser-micromachined multi-modal resonating power transducer for wireless sensing systems
TL;DR: In this article, the authors presented a vibration-induced power generator with total volume of ∼1 cm 3 which uses laser-micromachined springs to convert mechanical energy into useful electrical power by Faraday's law of induction.
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An integrated MEMS three-dimensional tactile sensor with large force range
TL;DR: In this article, an integrated three-dimensional tactile sensor with robust MEMS structure and soft contact surface suitable for robotic applications was developed, which includes 4×8 sensing cells each exhibiting an independent, linear response to the three components of forces applied on the cells.
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Fingertip‐skin‐inspired highly sensitive and multifunctional sensor with hierarchically structured conductive graphite/polydimethylsiloxane foams
Qijun Sun,Xin-Hua Zhao,Ye Zhou,Chi-Chung Yeung,Wei Wu,Shishir Venkatesh,Zong-Xiang Xu,Jonathan J. Wylie,Wen J. Li,Vellaisamy A. L. Roy +9 more
TL;DR: Wang et al. as mentioned in this paper designed a highly sensitive skin sensor with a linear response over a broad pressure range and multifunctional sensing capabilities, which can detect diverse stimuli, including textures, temperature, humidity, etc.
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Mobile Human Airbag System for Fall Protection Using MEMS Sensors and Embedded SVM Classifier
TL;DR: A mobile human airbag system designed for fall protection for the elderly and an embedded digital signal processing (DSP) system is developed for real-time fall detection.