通过实现肌电模块,扩展与智能眼镜的非触摸交互

Tomasz Kocejko, Krzysztof Czuszyński, J. Rumiński, A. Bujnowski, A. Poliński, J. Wtorek
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引用次数: 0

摘要

在本文中,我们建议利用颞肌收缩来完成某些动作。方法:记录“点击”、“双击”、“点击-按住”和“不动作”三种动作中任一动作对应的一组肌肉收缩。记录一定数量的信号后,计算出5个参数的集合。这些参数作为神经网络的输入矩阵。采用包含200个神经元的二层前馈神经网络,根据输入矩阵对手势进行分类。结果:使用由43个样本组成的数据集对网络进行训练,然后在34个样本数据集上对网络进行测试。所有来自测试集的手势都被正确分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending touch-less interaction with smart glasses by implementing EMG module
In this paper we propose to use temporal muscle contraction to perform certain actions. Method: The set of muscle contractions corresponding to one of three actions including “single-click”, “double-click” “click-n-hold” and “non-action” were recorded. After recording certain amount of signals, the set of five parameters was calculated. These parameters served as an input matrix for the neural network. Two-layer feedforward neural network with one hidden layer of 200 neurons was applied to classify gestures based on the input matrix. Results: The network was trained using the dataset consisted of 43 samples and then tested on the 34 samples dataset. All gestures from the test set were correctly classified.
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