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  • SPS
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    Length: 00:09:33
10 Jun 2021

With the widespread of Human-Cyber-Physical Systems (HCPS), the fine-grained human movement detection becomes more and more important. Especially for the slightly motions of human’s hands, they are not only bring abundant information, but also provide a new way for the interaction between users and systems. In this paper, we focus on the problem of how to detect the human’s typing motion, and designed a new system, named as Typing Wristband, to obtain the vibration of wrist using piezoelectric transducer (PZT). Then, a robust denoising, event detection and classification algorithms are proposed to deal with the signal collected by Typing Wristband and detect the typing motions. Typing Wristband can recognized the movements of 3 fingers and 9 keys with high accuracy. Furthermore, it is very cheap and can be embedded into existing smart devices, e.g. a smart watch, so that it supports the wireless sensing very well in practice. Both of the analysis and experimental results verify that our Typing Wristband has the better performance in terms of accuracy and convenience.

Chairs:
Chenshu Wu

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