Deep convolutional generative adversarial network-based emg data enhancement for hand motion classi fi cation

HIGHLIGHTS

• who: EMG et al. from the College of Telecommunication, Hangzhou Dianzi University, Hangzhou, China have published the article: Deep Convolutional Generative Adversarial Network-Based EMG Data Enhancement for Hand Motion Classi fi cation, in the Journal: (JOURNAL)
• what: It is difficult to obtain immense bio-signal datasets due to the following reasons. The dataset in this article is the target of one with sEMG signals, which is initially proposed by Fang et_al .
• how: The contributions of this study are as follows This article proposes a method for generating synthetic data. The result is . . .
  

   

  

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