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Naishi Feng

Showing results (1-10 of 7) with videos related to

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International Journal of Neural Systems|October 25, 2021
Motor Intention Decoding from the Upper Limb by Graph Convolutional Network Based on Functional ConnectivityNaishi Feng, Fo Hu, Hong Wang, et al.
Journal of Neural Engineering|October 12, 2020
Decoding of voluntary and involuntary upper-limb motor imagery based on graph fourier transform and cross-frequency coupling coefficientsNaishi Feng, Fo Hu, Hong Wang, et al.
Computer Methods and Programs in Biomedicine|March 12, 2025
A comprehensive exploration of motion sickness process analysis from EEG signal and virtual realityNaishi Feng, Bin Zhou, Qianqian Zhang, et al.
International Journal of Neural Systems|December 28, 2020
Acrophobia Quantified by EEG Based on CNN Incorporating Granger CausalityFo Hu, Hong Wang, Qiaoxiu Wang, et al.
Bioengineering (Basel, Switzerland)|December 23, 2023
Synthesis of sEMG Signals for Hand Gestures Using a 1DDCGANMohamed Amin Gouda, Wang Hong, Daqi Jiang, et al.
Computer Methods and Programs in Biomedicine|May 14, 2020
Accurate recognition of lower limb ambulation mode based on surface electromyography and motion data using machine learningBin Zhou, Hong Wang, Fo Hu, et al.
Journal of Neural Engineering|August 15, 2022
Non-invasive dual attention TCN for electromyography and motion data fusion in lower limb ambulation predictionBin Zhou, Naishi Feng, Hong Wang, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
International Journal of Neural Systems|October 25, 2021
Motor Intention Decoding from the Upper Limb by Graph Convolutional Network Based on Functional ConnectivityNaishi Feng, Fo Hu, Hong Wang, et al.
Journal of Neural Engineering|October 12, 2020
Decoding of voluntary and involuntary upper-limb motor imagery based on graph fourier transform and cross-frequency coupling coefficientsNaishi Feng, Fo Hu, Hong Wang, et al.
Computer Methods and Programs in Biomedicine|March 12, 2025
A comprehensive exploration of motion sickness process analysis from EEG signal and virtual realityNaishi Feng, Bin Zhou, Qianqian Zhang, et al.
International Journal of Neural Systems|December 28, 2020
Acrophobia Quantified by EEG Based on CNN Incorporating Granger CausalityFo Hu, Hong Wang, Qiaoxiu Wang, et al.
Bioengineering (Basel, Switzerland)|December 23, 2023
Synthesis of sEMG Signals for Hand Gestures Using a 1DDCGANMohamed Amin Gouda, Wang Hong, Daqi Jiang, et al.
Computer Methods and Programs in Biomedicine|May 14, 2020
Accurate recognition of lower limb ambulation mode based on surface electromyography and motion data using machine learningBin Zhou, Hong Wang, Fo Hu, et al.
Journal of Neural Engineering|August 15, 2022
Non-invasive dual attention TCN for electromyography and motion data fusion in lower limb ambulation predictionBin Zhou, Naishi Feng, Hong Wang, et al.
Pageof 1