Naïve手势识别的贝叶斯分类器

Proceedings of the 3rd International Conference on Applied Engineering Pub Date : 1900-01-01 DOI:10.5220/0010352601100114

Imanuel Simatupang, D. Pamungkas, S. K. Risandriya

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引用次数: 1

摘要

:本文提供了使用Naïve贝叶斯方法识别手指的五种手势。利用肌电信号(EMG)识别手指运动。一个肌环被用来获取信号。系统的平均成功率约为90.61%。为了验证结果，将系统的输出用于控制移动机器人。实验结果表明，该系统能够控制机器人的运动。

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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Naïve Bayes Classifier for Hand Gestures Recognition

: This paper provides recognizing the five gestures of the fingers using Naïve Bayes method. The electromyography signal (EMG) is utilized to recognize the fingers movement. A myo armband is used to obtain the signal. The average success rate of the system is about 90.61%. To verify the results, the outputs of the system are used to control a mobile robot. The results show that the system is able to control the movement of the robot.

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Proceedings of the 3rd International Conference on Applied Engineering

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