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A new effective wearable hand gesture recognition algorithm with 3-axis accelerometer

机译:具有3轴加速度计的新有效可穿戴手势识别算法

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In this paper, a new simple and effective hand gesture recognition algorithm with 3-axis accelerometer sensor is proposed. It is different from much of the previous work that in our algorithm the preprocessed 3-axis waveforms from accelerometer are directly used as the input features and a fast dynamic time warping(FastDTW) is used as the recognizer. Our proposed algorithm is device-independent in that it can be very easily implemented and portable on any other smart wearable device equipped with 3-axis accelerometer. The experimental results show that the proposed algorithm can perform 99% correct rate with 5 training samples for each gesture in our dataset, which consists of 160 test samples from 16 different gestures. Besides, our algorithm can be 8 times faster than standard dynamic time warping(DTW) algorithm without performance decline.
机译:本文提出了一种具有三轴加速度计传感器的新简单有效的手势识别算法。它与以前的大部分工作不同,在我们的算法中,来自加速度计的预处理3轴波形直接用作输入功能,并且使用快速动态的时间翘曲(FastDTW)作为识别器。我们所提出的算法是无关的,因为它可以非常容易地在配备3轴加速度计的任何其他智能可穿戴设备上实现和便携。实验结果表明,该算法可以为我们数据集中的每个手势进行99%的正确速率,其中每个手势有5个训练样本,由160个不同手势组成160个测试样本。此外,我们的算法可以比标准动态时间翘曲(DTW)算法快8倍,没有性能下降。

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