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Multi-recursive Wavelet Neural Network for Proximity Capacitive Gesture Recognition Analysis and Implementation

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New Trends in Computer Technologies and Applications (ICS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1013))

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Abstract

This paper presents a multi-recursive wavelet neural network (MRWNN) with proximity capacitive gesture recognition. Recently, the capacitive sensor technologies have been developed for proximity methods that sensing electronic varies around sensor detection point, but the user gesture signals are time-variant. The MRWNN have multi layers recursive weight to record last signal variation, and we utilize microcontroller with MRWNN to identify algorithms and implement proximity capacitive gesture recognition. Moreover, we show MRWNN weight convergence analysis of the MRWNN signal identifier. In the experimental results, we show MRWNN can recognize patterns of different gesture signal accurately and reliably. In addition, we use wearable device combined with BLE (Bluetooth Low Energy) feedback output response immediately.

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Acknowledgment

This work was supported in part by the “Intelligent Recognition Industry Service Center” of Higher Education Sprout Project, Ministry of Education, Taiwan.

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Authors and Affiliations

  1. Internet of Things Laboratory, Chunghwa Telecom Laboratories, New Taipei City, Taiwan

    Chao-Ting Chu

  2. Department of Electrical Engineering, National Yunlin University of Science and Technology, Douliu, Taiwan

    Chian-Cheng Ho

Authors
  1. Chao-Ting Chu
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  2. Chian-Cheng Ho
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Corresponding author

Correspondence to Chao-Ting Chu .

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Editors and Affiliations

  1. National Yunlin University of Science and Technology, Douliu, Taiwan

    Chuan-Yu Chang

  2. National Yunlin University of Science and Technology, Douliu, Taiwan

    Chien-Chou Lin

  3. Southern Taiwan University of Science and Technology, Tainan, Taiwan

    Horng-Horng Lin

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Chu, CT., Ho, CC. (2019). Multi-recursive Wavelet Neural Network for Proximity Capacitive Gesture Recognition Analysis and Implementation. In: Chang, CY., Lin, CC., Lin, HH. (eds) New Trends in Computer Technologies and Applications. ICS 2018. Communications in Computer and Information Science, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-13-9190-3_53

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  • DOI: https://doi.org/10.1007/978-981-13-9190-3_53

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9189-7

  • Online ISBN: 978-981-13-9190-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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