An Imu-Based Wearable Ring For On-Surface Handwriting Recognition

Zhe-Ting Liu, Davy P. Y. Wong, Pai H. Chou
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引用次数: 3

Abstract

We propose a finger-worn, on-surface fingerwriting recognition system based on an inertial sensor. The acceleration and the angular velocity data from the finger are sent by Bluetooth (BLE) to a host computer for conversion into words. The motion data are segmented by a long short-term memory (LSTM) model before recognition by a Convolutional Neural Network (CNN) or an LSTM model. Experiment results show the proposed system achieves 1.05% CER and 7.28% WER, making it a viable system as a text input interface.
一种基于imu的可穿戴式手写识别环
提出了一种基于惯性传感器的手指佩戴式表面指纹识别系统。手指的加速度和角速度数据通过蓝牙(BLE)发送到主机,然后转换成文字。在使用卷积神经网络(CNN)或LSTM模型进行识别之前,先用LSTM模型对运动数据进行分割。实验结果表明,该系统的译码率为1.05%,译码率为7.28%,是一个可行的文本输入界面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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