Yunjian Guo, Kunpeng Li, Wei Yue, Nam-Young Kim, Yang Li, Guozhen Shen, Jong-Chul Lee
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A Rapid Adaptation Approach for Dynamic Air-Writing Recognition Using Wearable Wristbands with Self-Supervised Contrastive Learning
Highlights
Utilizing self-supervised learning, the proposed wearable wristband with a four-channel sensing array and wireless transmission module is developed for tracking air-writing and dynamic gestures.
The model can learn prior features from unlabeled signals of random wrist movements, significantly reducing the dependency on extensive labeled data for training.
The wristband system rapidly adapts to multiple scenarios after fine-tuning using few-shot data, enhancing user interaction through natural and intuitive communication.
期刊介绍:
Nano-Micro Letters is a peer-reviewed, international, interdisciplinary, and open-access journal published under the SpringerOpen brand.
Nano-Micro Letters focuses on the science, experiments, engineering, technologies, and applications of nano- or microscale structures and systems in various fields such as physics, chemistry, biology, material science, and pharmacy.It also explores the expanding interfaces between these fields.
Nano-Micro Letters particularly emphasizes the bottom-up approach in the length scale from nano to micro. This approach is crucial for achieving industrial applications in nanotechnology, as it involves the assembly, modification, and control of nanostructures on a microscale.