• 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.

中文翻译：

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一种使用具有自监督对比学习功能的可穿戴腕带进行动态 air-writing 识别的快速适应方法

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  利用自我监督学习，开发了具有四通道传感阵列和无线传输模块的可穿戴腕带，用于跟踪空中书写和动态手势。

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  该模型可以从手腕随机运动的未标记信号中学习先前的特征，从而显着减少对大量标记数据的依赖以进行训练。

• 
  腕带系统使用少量镜头数据进行微调后，可快速适应多种场景，通过自然直观的通信增强用户交互。