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A Novel Human Computer Interface based on Electrooculogram Signal for Smart Assistive Robots

机译:基于眼电图信号的新型智能辅助机器人人机界面

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Assistive robots play an increasingly important role in the lives of people with disabilities. More and more research efforts are being focused on using Electrooculogram (EOG) signals in driving assistive robots. This paper presents a novel human computer interface based on EOG signal for controlling assistive robots. Firstly, this paper introduces the generation mechanism of EOG, collection method and experimental scheme. Then analyzes the principle of autoregressive spectral entropy feature extraction algorithm, procedures and extraction results in detailed. Next applies the support vector machine based on multi-classifier model to identify the EOG signal with three-dimensional feature vectors. Finally, a deterministic finite state machine which uses the support vector machine recognition result as a symbol input sequences is designed to express the transfer rule of different control commands. The experimental result shows that the sequence of the EOG signal made by the user can be correctly identified and output the corresponding command.
机译:辅助机器人在残疾人的生活中扮演着越来越重要的角色。越来越多的研究工作集中在在驾驶辅助机器人中使用眼电图(EOG)信号。本文提出了一种基于EOG信号的新型人机界面,用于控制辅助机器人。首先介绍了EOG的产生机理,收集方法和实验方案。然后详细分析了自回归谱熵特征提取算法的原理,步骤和提取结果。接下来应用基于多分类器模型的支持向量机来识别具有三维特征向量的EOG信号。最后,设计了一种将支持向量机识别结果用作符号输入序列的确定性有限状态机,以表示不同控制命令的传递规则。实验结果表明,可以正确识别用户发出的EOG信号序列,并输出相应的命令。

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