首页> 外文会议>International Conference on Advances in Electrical Engineering >Hardware and software implementation of real time electrooculogram (EOG) acquisition system to control computer cursor with eyeball movement
【24h】

Hardware and software implementation of real time electrooculogram (EOG) acquisition system to control computer cursor with eyeball movement

机译:实时眼电图(EOG)采集系统的硬件和软件实现,可通过眼球运动来控制计算机光标

获取原文

摘要

Human computer interface (HCI) is an emerging technology of neuroscience and artificial intelligence. Development of HCI system using bio signal e.g. Electrooculogram (EOG), Electromyogram (EMG), Electroencephalogram (EEG), Functional near-infrared spectroscopy (fNIRS) etc. are attracted more and more attention of researchers all over the world in recent years because through this it is possible to get acquainted with advanced technologies of artificial intelligence. This paper presents the design and implementation of a fully functional Electrooculogram (EOG) based human computer interface. In this work we have designed and implemented necessary hardware and software for EOG signal acquisition along with controlling hardware such as wheelchair, robotic arm, mobile robot etc., and move computer mouse cursor simultaneously using EOG signal. This interface has three portion: EOG signal acquisition and amplification, analog to digital conversion, and real time hardware and mouse cursor movement. Eye movement is detected by measuring potential difference between cornea and retina using five Ag-Agcl disposable electrodes. Frequency range of EOG signal is considered as 0.3 to 15Hz, so this frequency range is taken using an active high and low pass filter so that accurate EOG signal can be achieved. The analog output of the EOG signal from filter is converted into digital signal by using an Arduino. Arduino serialize the EOG data for calibration and provides a threshold reference point which is used for controlling Hardware. The Classification module e.g. Support Vector machine (SVM) and Linear Discriminant Analysis (LDA) classify live data with respect to the horizontal and vertical data. This works as a binary classifier and choose optimal hyper-plane between two variables. According to each update on the eye position, cursor automatically accelerated in particular direction. PyMouse module in python is used for this task. Eye gesture based Hardware like robot, wheelchair etc. control and mouse cursor movement are the principle outcome of this research work.
机译:人机界面(HCI)是神经科学和人工智能的新兴技术。利用生物信号开发HCI系统,例如近年来,眼电图(EOG),肌电图(EMG),脑电图(EEG),功能近红外光谱(fNIRS)等吸引了越来越多的研究者关注,因为通过它可以结识人工智能的先进技术。本文介绍了基于全功能眼电图(EOG)的人机界面的设计和实现。在这项工作中,我们设计并实现了用于EOG信号采集的必要硬件和软件,以及控制硬件(如轮椅,机械臂,移动机器人等),并使用EOG信号同时移动计算机鼠标光标。该界面包括三个部分:EOG信号采集和放大,模数转换以及实时硬件和鼠标光标移动。通过使用五个Ag-Agcl一次性电极测量角膜和视网膜之间的电位差来检测眼睛的运动。 EOG信号的频率范围被认为是0.3到15Hz,因此使用有源高通和低通滤波器可以获取此频率范围,从而可以实现准确的EOG信号。来自滤波器的EOG信号的模拟输出通过使用Arduino转换为数字信号。 Arduino将EOG数据序列化以进行校准,并提供用于控制硬件的阈值参考点。分类模块例如支持向量机(SVM)和线性判别分析(LDA)根据水平和垂直数据对实时数据进行分类。这用作二进制分类器,并在两个变量之间选择最佳超平面。根据眼睛位置的每次更新,光标会自动朝特定方向加速。 python中的PyMouse模块用于此任务。基于眼手势的硬件(如机器人,轮椅等)的控制和鼠标光标的移动是这项研究工作的主要成果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号