A coloring and timing brain-computer interface for the nursing bed robot

The patient with a severely spinal injury needs an intention-controlled nursing bed (NB) robot to help the body actions. To recognize human intentions, the brain–computer interface (BCI) of the steady-state visual evoked potentials (SSVEPs) is usually used. For the BCI of the SSVEPs, the visual fatigue should be alleviated, and the intention recognition accuracy should be improved. Therefor this paper proposed a coloring and timing BCI (CT-BCI) to alleviate the visual fatigue, and find the optimal Wavelet vanishing moment parameter to improve the intention recognition accuracy. In addition, the intention coding and decoding are designed and implemented. Furthermore, the wireless communications are used among the CT-BCI and the robots in the internet of things. Experiments show that the proposed CT-BCI decreases the average evocation time for each intention by 0.8 s, and prolongs the eye non-fatigue duration by 5.45 s, and improves the intention recognition accuracy by 6.7% compared with the traditional BCI.