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SmartTextileGlove: Capturing Complex Hand Movements and Object Interactions Using Machine Learning Powered Stretchable Smart Textile Gloves

Published in Nature Machine Intelligence, 2024 [Link]

System requirements

  • Graphical user interface: Microsoft Visual Studio C# 2017
  • Device firmware: Segger 5.34
  • Xcode 14.1
  • Unity 2021.2.10.f1
  • Python >= 3.9 (package dependencies can be found in Codes/Python/requirements.txt)

Repository overview

  • Codes/
    • iOS software developed using Swift (iOS/)
    • Data acquisition software developed in C# (Data grapher/)
    • Unity demo software (Unity/)
    • Python codes (Python/)
    • Firmware codes developed using C (Firmware/)
    • Data downloader software developed using python (Data receiver/)
  • Dataset/
    • Project page: https://feel.ece.ubc.ca/SmartTextileGlove/
      • Dataset collected from five subjects for different applications (Raw data/)
      • Power consumption data for costume-made data acquisition board (PCB Power consumption/)
      • Source data from sensor characteristis (Sensor characteristics/)
      • Output data for click detection (Click detection/)

Bibtex

If you find this code useful in your research, please cite:

@article{tashakori2024capturing,
  title={Capturing complex hand movements and object interactions using machine learning-powered stretchable smart textile gloves},
  author={Tashakori, Arvin and Jiang, Zenan and Servati, Amir and Soltanian, Saeid and Narayana, Harishkumar and Le, Katherine and Nakayama, Caroline and Yang, Chieh-ling and Wang, Z Jane and Eng, Janice J and others},
  journal={Nature Machine Intelligence},
  pages={1--13},
  year={2024},
  publisher={Nature Publishing Group UK London}
}