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.

Can a highly accurate multi-class SSMVEP BCI induce sensory-motor rhythm in the sensorimotor area?

“…These frequencies could be used to do classification. Our recent study explored the characteristics of brain response to a light spot humanoid motion stimulus modulated by the change of brightness, where the main peaks were at F, F-f, F + f (F: the high flicker frequency, f: stride frequency) [48]. The participants likely had difficulty in distinguishing the left and right feet in this study.…”

Enhancing Detection of SSMVEP Induced by Action Observation Stimuli Based on Task-Related Component Analysis

“…EEG induced by the flicker stimulus containing dual frequencies revealed the underlying nonlinearity [27][28][29]. A similar phenomenon occurred in the EEG induced by the motion stimulus with dual frequencies [21]. Even though the frequencies induced by different stimuli with dual frequencies are not the same, all the induced frequencies are among m × F ± n × f .…”

“…Furthermore, not only the stimulus frequency but also modulated frequencies were induced by the stimulus with multi-frequencies. Thus, the template signals utilizing CCA were difficult to manually select and optimize [12,21]. Yet mc-TRCA is a data-driven approach, so that there is no need to select optimal template signals.…”

“…Currently, CCA is still the main identification method for SSMVEP. The reference signals were constructed from sine-cosine signals containing all the induced frequencies [9,11,21]. And it required manual optimization of reference signals to achieve high identification accuracy.…”