一种基于imu的可穿戴式手写识别环

2020 International Symposium on VLSI Design, Automation and Test (VLSI-DAT) Pub Date : 2020-08-01 DOI:10.1109/VLSI-DAT49148.2020.9196479

Zhe-Ting Liu, Davy P. Y. Wong, Pai H. Chou

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引用次数: 3

摘要

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。

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

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.

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2020 International Symposium on VLSI Design, Automation and Test (VLSI-DAT)

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