Özet
Wearable technologies are in pursuit of designing portable devices worn by people. In this paper, gesture recognition on a sleeve having a capacitive textile-based pressure sensor array has been developed. Machine learning models are generated to recognize a set of gestures by accumulating capacitance values read from a sensor array during the execution of gestures. The performance of the gesture recognition system is evaluated in the experiments conducted with human test subjects. Real-time gesture prediction is achieved using the trained model. The performed gestures and predicted data are collected and analyzed, resulting in accuracies up to 86'.
Orijinal dil | İngilizce |
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Ana bilgisayar yayını başlığı | EEITE 2024 - Proceedings of 2024 5th International Conference in Electronic Engineering, Information Technology and Education |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Elektronik) | 9798350372878 |
DOI'lar | |
Yayın durumu | Yayınlandı - 2024 |
Etkinlik | 5th International Conference in Electronic Engineering, Information Technology and Education, EEITE 2024 - Chania, Greece Süre: 29 May 2024 → 31 May 2024 |
Yayın serisi
Adı | EEITE 2024 - Proceedings of 2024 5th International Conference in Electronic Engineering, Information Technology and Education |
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???event.eventtypes.event.conference??? | 5th International Conference in Electronic Engineering, Information Technology and Education, EEITE 2024 |
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Ülke/Bölge | Greece |
Şehir | Chania |
Periyot | 29/05/24 → 31/05/24 |
Bibliyografik not
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