PowerGest: Self-Powered Gesture Recognition for Command Input and Robotic Manipulation
As human-computer interaction (HCI) advances, gesture recognition has emerged as a transformative technology for human-computer interaction. Traditional methods, often camera or glove-based, are restricted by various environmental conditions and user-specific demands, highlighting the need for more...
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| Veröffentlicht in: | Proceedings - International Conference on Parallel and Distributed Systems S. 528 - 535 |
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| Hauptverfasser: | , , , , , , , , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
10.10.2024
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| Schlagworte: | |
| ISSN: | 2690-5965 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | As human-computer interaction (HCI) advances, gesture recognition has emerged as a transformative technology for human-computer interaction. Traditional methods, often camera or glove-based, are restricted by various environmental conditions and user-specific demands, highlighting the need for more universal, non-intrusive, and sustainable solutions. Addressing this, we present PowerGest, a self-powered gesture recognition system based on a solar cell array. This innovative system leverages the dual functionalities of solar cells: energy harvesting and gesture sensing, providing an alternative to conventional methods. It integrates a designed low-powered data acquisition chip with a wireless transmission module and a user-friendly interface. PowerGest employs a series of signal processing methods and utilizes several machine learning algorithms, achieving over 97% accuracy for both numeric input and activity control gesture recognition tasks. With its broad applications in robotic control, text input, and more, PowerGest contributes to a more sustainable and intuitive HCI experience. Project demo: https://drive.google.com/drive/folders/10KEul8PAfvTUomi0JvZ8u411JyScCXQI?usp=sharing. |
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| ISSN: | 2690-5965 |
| DOI: | 10.1109/ICPADS63350.2024.00075 |