Human-Machine Interaction (HMI) and Brain-Computer Interface (BCI) are evolving technologies that show the great potentials to extract and utilize humans’ intents in controlling smart machines. However, existing HMI and BCI technologies are limited in terms of (1) the number of Degrees- of-Freedom (DoF) to be controlled and (2) the ways the performance of BCI-enabled control systems are verified and validated. This study aimed to explore the solutions to addree both of above concerns; we proposed a hybrid control system that is capable of training, detecting, and interpreting humans’ intents, and utilizing humans’ intents in real-time controls of smart machines. More specifically, the system acquired brain signals in the form of Electroencephalography (EEG) by an Emotiv Epoc X and processed these signals to detect and extract humans’ intents in real-time machine controls. To cope with the frequency difference of humans’ thinking and machine motion controls, we developed a hybrid control module to fuse humans’ and machine's intelligence so that low-frequency humans’ intents could be used in real-time machine controls. The system was prototyped and verified experimentally. The system was verified to achieve the accuracy of over 90 % in recognizing humans’ intents and controlling a robot by the operator's intents with a satisfactory responding time and accuracy.

中文翻译：

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智能机器的人机协同控制 – 一种拟议的混合控制


人机交互 （HMI） 和脑机接口 （BCI） 是不断发展的技术，显示出提取和利用人类意图来控制智能机器的巨大潜力。然而，现有的 HMI 和 BCI 技术在 （1） 要控制的自由度 （DoF） 数量和 （2） 支持 BCI 的控制系统的性能验证和确认方式方面受到限制。本研究旨在探索解决上述两个问题的解决方案;我们提出了一种混合控制系统，该系统能够训练、检测和解释人类的意图，并利用人类的意图对智能机器进行实时控制。更具体地说，该系统通过 Emotiv Epoc X 以脑电图 （EEG） 的形式获取大脑信号，并处理这些信号，以在实时机器控制中检测和提取人类的意图。为了应对人类思维和机器运动控制的频率差异，我们开发了一种混合控制模块，将人和机器的智能融合在一起，使低频人类的意图可以用于实时机器控制。该系统进行了原型设计和实验验证。该系统经过验证，在识别人类意图和根据操作员的意图控制机器人方面实现了超过 90% 的准确率，响应时间和准确性令人满意。