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Handcrefted Feature Extraction approach for gesture classification of triboelectric signals

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Handcrafted-Feature-Extraction

Handcrafted Feature Extraction approach for gesture classification of triboelectric signals

Author of the code: Thiago Simoes Dias - tsimoesdias@gmail.com

Public Dataset Information We express our gratitude to the authors for making their dataset publicly available:

F. Wen, Z. Zhang, T. He, C. Lee for their work "AI-enabled sign language recognition and VR space bidirectional communication using triboelectric smart glove" published in Nature Communications, which provided valuable insights and data for this analysis. DOI: 10.1038/s41467-021-25637-w

F. Wen for sharing the source data and dataset of Fig. 2, Fig. 3, and Fig. 4 (2021). DOI: 10.7910/DVN/7KJWV3

Their contributions significantly enhance research in the field, and we acknowledge their efforts with appreciation.

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