Abstract
Brain-controlled wheelchair (BCW) has the potential to improve the quality of life for people with motor disabilities. A lot of training is necessary for users to learn and improve BCW control ability and the performances of BCW control are crucial for patients in daily use. In consideration of safety and efficiency, an indoor simulated training environment is built up in this paper to improve the performance of BCW control. The indoor simulated environment mainly realizes BCW implementation, simulated training scenario setup, path planning and recommendation, simulated operation, and scoring. And the BCW is based on steady-state visual evoked potentials (SSVEP) and the filter bank canonical correlation analysis (FBCCA) is used to analyze the electroencephalography (EEG). Five tasks include individual accuracy, simple linear path, obstacles avoidance, comprehensive steering scenarios, and evaluation task are designed, 10 healthy subjects were recruited and carried out the 7-days training experiment to assess the performance of the training environment. Scoring and command-consuming are conducted to evaluate the improvement before and after training. The results indicate that the average accuracy is 93.55% and improves from 91.05% in the first stage to 96.05% in the second stage (p = 0.001). Meanwhile, the average score increases from 79.88 in the first session to 96.66 in the last session and tend to be stable (p < 0.001). The average number of commands and collisions to complete the tasks decreases significantly with or without the approximate shortest path (p < 0.001). These results show that the performance of subjects in BCW control achieves improvement and verify the feasibility and effectiveness of the proposed simulated training environment.
Highlights
A brain-computer interface (BCI) provides a new communication and control channel between the human brain and the external world without depending on peripheral nerves and muscles, which helps users interact with an external environment directly (Wolpaw et al, 2002; Naseer and Hong, 2015)
Brain-controlled wheelchair (BCW) is a particular device based on BCI, which is able to provide assistance and potentially improve the quality of life for people who have no ability to control a wheelchair by conventional interfaces due to some diseases, such as motor neuron diseases, total paralysis, stroke, etc. (Rebsamen et al, 2010)
Gentiletti et al (2009) designed a simulation platform based on P300 and verified the practicability through wheelchair control, and Herweg et al (2016) reported a virtual environment for wheelchair control based on P300 as well
Summary
A brain-computer interface (BCI) provides a new communication and control channel between the human brain and the external world without depending on peripheral nerves and muscles, which helps users interact with an external environment directly (Wolpaw et al, 2002; Naseer and Hong, 2015). Simulated Training Environment for BCW brain signals in BCI systems such as electroencephalography (EEG) (Abiri et al, 2019), functional near-infrared spectroscopy (Khan and Hong, 2017; Hong et al, 2018), functional magnetic resonance imaging (Sitaram et al, 2008), and magnetoencephalography (Mellinger et al, 2007). Brain-controlled wheelchair (BCW) is a particular device based on BCI, which is able to provide assistance and potentially improve the quality of life for people who have no ability to control a wheelchair by conventional interfaces due to some diseases, such as motor neuron diseases, total paralysis, stroke, etc. According to reports by Leeb et al (2007), a tetraplegic is able to control movements of the wheelchair through EEG in a virtual environment. In terms of the simulated systems based on SSVEP-based BCI or hybrid BCI, Bi et al (2014) applied SSVEP-based BCI to control a simulated vehicle and Li et al (2018) combined hybrid BCI with computer vision to build a simulated driving system
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