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}
}