A Light Spot Humanoid Motion Paradigm Modulated by the Change of Brightness to Recognize the Stride Motion Frequency

Abstract

The steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) usually has the advantages of high information transfer rate (ITR) and no need for training. However, low frequencies, such as the human stride motion frequency, cannot easily induce SSVEP. To solve this problem, a light spot humanoid motion paradigm modulated by the change of brightness was designed in this study. The characteristics of the brain response to the motion paradigm modulated by the change of brightness were analyzed for the first time. The results showed that the designed paradigm could induce not only the high flicker frequency but also the modulation frequencies between the change of brightness and the motion in the primary visual cortex. Thus, the stride motion frequency can be recognized through the modulation frequencies by using the designed paradigm. Also, in an online experiment, this paradigm was employed to control a lower limb robot to achieve same frequency stimulation, which meant that the visual stimulation frequency was the same as the motion frequency of the robot. Also, canonical correlation analysis (CCA) was used to distinguish three different stride motion frequencies. The average accuracies of the classification in three walking speeds using the designed paradigm with the same and different high frequencies reached 87 and 95% respectively. Furthermore, the angles of the knee joint of the robot were obtained to demonstrate the feasibility of the electroencephalograph (EEG)-driven robot with same stimulation.

Keywords: brain–computer interface; motion modulated by the change of brightness; same frequency stimulation; steady-state visual evoked potential; stride motion frequency.

FIGURE 1

The light spot humanoid motion stimulus paradigm modulated by the change of brightness. (A) Are 20 green straw-hat LEDs and a hemispherical lampshade, and (B) is the moving process of the light spot human.

FIGURE 2

The EEG spectra when one subject stared at the high frequency flicker stimulations. (A) The high flicker frequency is 35 Hz, (B) the high flicker frequency is 45 Hz, (C) the high flicker frequency is 55 Hz, (D) the high flicker frequency is 65 Hz, (E) the high flicker frequency is 75 Hz, and (F) the high flicker frequency is 85 Hz.

FIGURE 3

The average SNRs of EEG data when subjects stared at the high frequency stimulations (35, 45, 55, 65, 75, and 85 Hz, respectively).

FIGURE 4

The EEG spectra when one subject stared at the light spot humanoid motion stimulations. (A) The flicker frequency F was 45 Hz and the motion frequency f was 0.2 Hz, (B) the flicker frequency F was 45 Hz and the motion frequency f was 0.4 Hz, (C) the flicker frequency F was 45 Hz and the motion frequency f was 0.6 Hz, (D) the flicker frequency F was 43 Hz and the motion frequency f was 0.2 Hz, (E) the flicker frequency F was 43 Hz and the motion frequency f was 0.4 Hz, (F) the flicker frequency F was 43 Hz and the motion frequency f was 0.6 Hz, (G) the flicker frequency F was 41 Hz and the motion frequency f was 0.2 Hz, (H) the flicker frequency F was 41 Hz and the motion frequency f was 0.4 Hz, (I) the flicker frequency F was 41 Hz and the motion frequency f was 0.6 Hz.

FIGURE 5

Confusion matrices for the stimulations at 5 s stimulus time among all the subjects. The color scale reveals the classification accuracies, the diagonals labeled with the correct classification accuracies.

FIGURE 6

The average classification accuracies among all the subjects with different stimulation durations.

FIGURE 7

Time domain of duty ratio of the PWM, time-frequency map of EEG data, and angles of knee joint of the lower limb robot. (A) The time domain of duty ratio of the PWM of LEDs in group 2 in three targets. (B) The time domain of duty ratio of the PWM of LEDs in group 3 in three targets. (C) The time-frequency map of EEG data during the online experiment and the color scale reveals the values of power spectrum. (D) The angles of left knee joint of the lower limb robot during the online experiment. (E) The angles of right knee joint of the lower limb robot during the experiment.