Control of a 2-DoF robotic arm using a P300-based brain-computer interface
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2019
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| _version_ | 1866909434441105408 |
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| author | Garakani, Golnoosh Ghane, Hamed Menhaj, Mohammad Bagher |
| author_facet | Garakani, Golnoosh Ghane, Hamed Menhaj, Mohammad Bagher |
| contents | In this study, a novel control algorithm for a P-300 based brain-computer interface is fully developed to control a 2-DoF robotic arm. Eight subjects including 5 men and 3 women, perform a 2-dimensional target tracking task in a simulated environment. Their EEG signals from visual cortex are recorded and P-300 components are extracted and evaluated to perform a real-time BCI based controller. The volunteer's intention is recognized and will be decoded as an appropriate command to control the cursor. The final goal of the system is to control a simulated robotic arm in a 2-dimensional space for writing some English letters. The results show that the system allows the robot end-effector to move between arbitrary positions in a point-to-point session with the desired accuracy. This model is tested on and compared with Dataset II of the BCI Competition. The best result is obtained with a multi-class SVM solution as the classifier, with a recognition rate of 97 percent, without pre-channel selection. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_1901_01422 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | Control of a 2-DoF robotic arm using a P300-based brain-computer interface Garakani, Golnoosh Ghane, Hamed Menhaj, Mohammad Bagher Human-Computer Interaction Robotics Systems and Control Signal Processing In this study, a novel control algorithm for a P-300 based brain-computer interface is fully developed to control a 2-DoF robotic arm. Eight subjects including 5 men and 3 women, perform a 2-dimensional target tracking task in a simulated environment. Their EEG signals from visual cortex are recorded and P-300 components are extracted and evaluated to perform a real-time BCI based controller. The volunteer's intention is recognized and will be decoded as an appropriate command to control the cursor. The final goal of the system is to control a simulated robotic arm in a 2-dimensional space for writing some English letters. The results show that the system allows the robot end-effector to move between arbitrary positions in a point-to-point session with the desired accuracy. This model is tested on and compared with Dataset II of the BCI Competition. The best result is obtained with a multi-class SVM solution as the classifier, with a recognition rate of 97 percent, without pre-channel selection. |
| title | Control of a 2-DoF robotic arm using a P300-based brain-computer interface |
| topic | Human-Computer Interaction Robotics Systems and Control Signal Processing |
| url | https://arxiv.org/abs/1901.01422 |