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An FPGA-Based Brain-Computer Interface for Wireless Electric Wheelchairs

机译:用于无线电动轮椅的基于FPGA的脑电脑界面

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A wireless EEG-based brain-computer interface (BCI) and an FPGA-based system to control electric wheelchairs through a Bluetooth interface was proposed in this paper for paralyzed patients. Paralytic patients can not move freely and only use wheelchairs in their daily life. Especially, people getting motor neuron disease (MND) can only use their eyes and brain to exercise their willpower. Therefore, real-time EEG and winking signals can help these patients effectively. However, current BCI systems are usually complex and have to send the brain waves to a personal computer or a single-chip microcontroller to process the EEG signals. In this paper, a simple BCI system with two channels and an FPGA-based circuit for controlling DC motor can help paralytic patients easily to drive the electric wheelchair. The proposed BCI system consists of a wireless physiological with two-channel acquisition module and an FPGA-based signal processing unit. Here, the physiological signal acquisition module and signal processing unit were designed for extracting EEG and winking signals from brain waves which can directly transformed into control signals to drive the electric wheelchairs. The advantages of the proposed BCI system are low power consumption and compact size so that the system can be suitable for the paralytic patients. The experimental results showed feasible action for the proposed BCI system and drive circuit with a practical operating in electric wheelchair applications.
机译:本文提出了一种基于无线EEG的脑电脑接口(BCI)和基于FPGA的系统,用于通过蓝牙接口控制电动轮椅,用于瘫痪患者。麻痹患者不能自由移动,只在日常生活中使用轮椅。特别是,获得运动神经元疾病(MND)的人只能使用他们的眼睛和大脑来锻炼他们的意志力。因此,实时脑电图和眨眼信号可以有效地帮助这些患者。然而,当前的BCI系统通常是复杂的,并且必须将大脑波发送到个人计算机或单片体微控制器以处理EEG信号。在本文中,具有两个通道的简单BCI系统和用于控制DC电机的FPGA电路可以帮助瘫痪患者轻松驱动电动轮椅。所提出的BCI系统包括与双通道采集模块和基于FPGA的信号处理单元的无线生理学。这里,设计了生理信号采集模块和信号处理单元,用于从脑波提取脑电图和眨眼信号,该脑波可以直接转换为控制信号以驱动电动轮椅。所提出的BCI系统的优点是功耗低,尺寸紧凑,因此系统可以适用于瘫痪患者。实验结果表明,建议的BCI系统和电动车辆在电动轮椅应用中采用实用操作的可行动作。

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