An embedded lightweight SSVEP-BCI electric wheelchair with hybrid stimulator
| Autor: | Ying Sun, Mingzhe Han, Yin Wenhan, Xinlei Chen, Jun Zhang, Shuai Wang, Rui Na, Chun Hu, Shuailei Zhang, Dezhi Zheng |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
Applied Mathematics Interface (computing) Process (computing) 020206 networking & telecommunications Functional requirement 02 engineering and technology Software portability Wheelchair Computational Theory and Mathematics Artificial Intelligence Signal Processing Personal computer 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Electrical and Electronic Engineering Statistics Probability and Uncertainty Energy (signal processing) Simulation Brain–computer interface |
| Zdroj: | Digital Signal Processing. 116:103101 |
| ISSN: | 1051-2004 |
| DOI: | 10.1016/j.dsp.2021.103101 |
| Popis: | Electric wheelchairs, as mobile auxiliary equipment, improve the quality of life and self-independence of the disabled. The brain-computer interface (BCI) is used to establish a direct connection between the brain and the wheelchair, which adopts the electroencephalogram (EEG) signal to control the wheelchair. Compared with other types of BCI, the steady-state visual evoked potentials (SSVEP)-BCI is more suitable to control the electric wheelchair due to the advantages of higher information transmission rate (ITR), higher signal-to-noise ratio (SNR), and less training. However, the existing SSVEP-BCI electric wheelchairs need to be equipped with at least one personal computer to drive the visual stimulator and process EEG signals in real-time. As a result, the electric wheelchair system is complicated, bulky, and limited in movement flexibility, so it is difficult to popularize in real-life scenarios. Therefore, to improve the portability and applicability of the SSVEP-BCI electric wheelchair, a lightweight SSVEP-BCI system is needed, which should be as light and energy-saving as possible while meeting functional requirements. This paper presents an embedded lightweight SSVEP-BCI electric wheelchair with a hybrid stimulator. A hybrid hardware-driven visual stimulator is designed, which combines the advantages of liquid crystal display (LCD) and light-emitting diode (LED) to achieve lower energy consumption than the traditional LCD stimulator. In addition, a lightweight BCI framework is designed to realize BCI program functions on the embedded platform for achieving similar performance as those on a personal computer. Experiments on real systems show that our embedded lightweight SSVEP-BCI electric wheelchair can be successfully operated by all eight subjects with a 93.9% average success rate of command operation. In addition, compared with the traditional LCD stimulator, the hybrid hardware-driven visual stimulator can save up to 27% of energy. |
| Databáze: | OpenAIRE |
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