We observed the steady-state visually evoked potential(SSVEP) from a healthy subject using a compact quad-channel potassium spin exchange relaxation-free(SERF) optically pumped magnetometer(OPM). To this end, 30 s of ...We observed the steady-state visually evoked potential(SSVEP) from a healthy subject using a compact quad-channel potassium spin exchange relaxation-free(SERF) optically pumped magnetometer(OPM). To this end, 30 s of data were collected, and SSVEP-related magnetic responses with signal intensity ranging from 150 fT to 300 f T were observed for all four channels. The corresponding signal to noise ratio(SNR) was in the range of 3.5–5.5. We then used different channels to operate the sensor as a gradiometer. In the specific case of detecting SSVEP, we noticed that the short channel separation distance led to a strongly diminished gradiometer signal. Although not optimal for the case of SSVEP detection, this set-up can prove to be highly useful for other magnetoencephalography(MEG) paradigms that require good noise cancellation.Considering its compactness, low cost, and good performance, the K-SERF sensor has great potential for biomagnetic field measurements and brain-computer interfaces(BCI).展开更多
In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheel...In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheelchair prototype in five different positions including stop position. In this study four different flickering frequencies in low frequency region were used to elicit the SSVEPs and were displayed on a Liquid Crystal Display (LCD) monitor using Lab-VIEW. Four stimuli colors, green, red, blue and violet were used to investigate the color influence in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital region were segmented into 1 second window and features were extracted by using Fast Fourier Transform (FFT). One-Against-All (OAA), a popular strategy for multiclass SVM, is used to classify SSVEP signals. During stimuli color comparison SSVEP with violet color showed higher accuracy than that with green, red and blue stimuli.展开更多
Purpose: To investigate the variation of visual function in different eccentricities of the visual field in isometropic amblyopes.Method: The stimulus matrix containing 61 hexagons was generated on a monitor. The diam...Purpose: To investigate the variation of visual function in different eccentricities of the visual field in isometropic amblyopes.Method: The stimulus matrix containing 61 hexagons was generated on a monitor. The diameter of the entire stimulating field was approximately 13.6 deg of arc; the frame rate of the monitor was 67 Hz. Every hexagon of the display contained a number of black and white small hexagonal patches which reversed during stimulation. These hexagons were simultaneously but independently modulated in time by the controlling computer program. The flashed elements were selected differently on each frame according to a computer-generated binary pseudo-random time series (m-sequence); the response contributions from each of the individual stimulus elements could be extracted from the cross corre-ation function. Subjects were asked to maintain fixation at the center of the stimulus pattern while each of the hexagons of the display reversed. The VERB system extracted the local responses by展开更多
Addressing the vulnerability of contact-based keyboard password systems to disclosure,this paper proposes and validates the feasibility of a non-contact secure password system based on brain-computer interface(BCI)tec...Addressing the vulnerability of contact-based keyboard password systems to disclosure,this paper proposes and validates the feasibility of a non-contact secure password system based on brain-computer interface(BCI)technology that detects steady-state visual evoked potential(SSVEP)signals.The system first lets a testee look at a digital stimulus source flashing at a specific frequency,and uses a wearable dry electrode sensor to collect the SSVEP signal.Secondly,a canonical correlation analysis method is applied to analyze the frequency of the stimulus source that the testee is looking at,and feeds back a code result through headphones.Finally,after all password codes are input,the system makes a judgment and provides visual feedback to the testee.Experiments were conducted to test the accuracy of the system,where twelve stimulus target frequencies between 10-16Hz were selected within the easily recognizable flicker frequency range of human brain,and each of them was tested for 12 times.The results demonstrate that this SSVEP-BCI-based system is feasible,achieving an average accuracy rate of 97.2%,and exhibits promising applications in various domains such as financial transactions and identity recognition.展开更多
The brain-computer interface(BCI)technology has received lots of attention in the field of scientific research because it can help disabled people improve their quality of life.Steady-state visual evoked potential(SSV...The brain-computer interface(BCI)technology has received lots of attention in the field of scientific research because it can help disabled people improve their quality of life.Steady-state visual evoked potential(SSVEP)is the most researched BCI experimental paradigm,which offers the advantages of high signal-to-noise ratio and short training-time requirement by users.In a complete BCI system,the two most critical components are the experimental paradigm and decoding algorithm.However,a systematic combination of the SSVEP experimental paradigm and decoding algorithms is missing in existing studies.In the present study,the transient visual evoked potential,SSVEP,and various improved SSVEP paradigms are compared and analyzed,and the problems and development bottlenecks in the experimental paradigm are finally pointed out.Subsequently,the canonical correlation analysis and various improved decoding algorithms are introduced,and the opportunities and challenges of the SSVEP decoding algorithm are discussed.展开更多
This study explored methods for improving the performance of Steady-State Visual Evoked Potential(SSVEP)-based Brain-Computer Interfaces(BCI), and introduced a new analytical method to quantitatively analyze and refle...This study explored methods for improving the performance of Steady-State Visual Evoked Potential(SSVEP)-based Brain-Computer Interfaces(BCI), and introduced a new analytical method to quantitatively analyze and reflect the characteristics of SSVEP. We focused on the effect of the pre-stimulation paradigm on the SSVEP dynamic models and the dynamic response process of SSVEP, and performed a comparative analysis of three pre-stimulus paradigms(black, gray, and white). Four dynamic models with different orders(second-and third-order)and with and without a zero point were used to fit the SSVEP envelope. The zero-pole analytical method was adopted to conduct quantitative analysis on the dynamic models, and the response characteristics of SSVEP were represented by zero-pole distribution characteristics. The results of this study indicated that the pre-stimulation paradigm affects the characteristics of SSVEP, and the dynamic models had good fitting abilities with SSVEPs under various types of pre-stimulation. Furthermore, the zero-pole characteristics of the models effectively characterize the damping coefficient, oscillation period, and other SSVEP characteristics. The comparison of zeros and poles indicated that the gray pre-stimulation condition corresponds to a lower damping coefficient, thus showing its potential to improve the performance of SSVEP-BCIs.展开更多
Steady-state visual evoked potential(SSVEP)-based brain-computer interfaces(BCIs)have been widely studied.Considerable progress has been made in the aspects of stimulus coding,electroencephalogram processing,and recog...Steady-state visual evoked potential(SSVEP)-based brain-computer interfaces(BCIs)have been widely studied.Considerable progress has been made in the aspects of stimulus coding,electroencephalogram processing,and recognition algorithms to enhance system performance.The properties of SSVEP have been demonstrated to be highly sensitive to stimulus luminance.However,thus far,there have been very few reports on the impact of background luminance on the system performance of SSVEP-based BCIs.This study investigated the impact of stimulus background luminance on SSVEPs.Specifically,this study compared two types of background luminance,i.e.,(1)black luminance[red,green,blue(rgb):(0,0,0)]and(2)gray luminance[rgb:(128,128,128)],and determined their effect on the classification performance of SSVEPs at the stimulus frequencies of 9,11,13,and 15 Hz.The offline results from nine healthy subjects showed that compared with the gray background luminance,the black background luminance induced larger SSVEP amplitude and larger signal-to-noise ratio,resulting in a better classification accuracy.These results suggest that the background luminance of visual stimulus has a considerable effect on the SSVEP and therefore has a potential to improve the BCI performance.展开更多
Brain–computer interface is a new form of interaction between humans and machines.This interaction helps the human brain control or operate external devices directly using electroencephalograph(EEG)signals.In this st...Brain–computer interface is a new form of interaction between humans and machines.This interaction helps the human brain control or operate external devices directly using electroencephalograph(EEG)signals.In this study,we first adopt a canonical correlation analysis method to find the stimulation frequency by calculating the correlation coefficient between the EEG data and multiple sets of harmonics with different frequencies.Then,we select the maximum correlation coefficient as the stimulus frequency and consequently identify steady-state visual evoked potentials.Afterward,we introduce power spectral density to adjust the stimulus frequency and a voting mechanism to reduce the false activation rate.Finally,we build a virtual household electrical appliance brain–computer control interface,which achieves over 72.84%accuracy for three classification problems.展开更多
Visual functions and nutrition metabolic characteristics werestudied in 8 subjects(16 eyes)with tobacco-toxic optic neuropathy(TTON).Their visual functions tested by psychophysical and electrophysiologicmethods showed...Visual functions and nutrition metabolic characteristics werestudied in 8 subjects(16 eyes)with tobacco-toxic optic neuropathy(TTON).Their visual functions tested by psychophysical and electrophysiologicmethods showed that:1.central vision diminished in 16 eyes,2.dyschromatopsias were found in 14 tested eyes,3.bilateral symmetricalcentral or cecocentral scotomas were the visual field characteristics in allcases,4.PVEP were severe abnormal in 3 spatial frequencies in all cases and56.3% of 15' checkboard ...展开更多
Background:Research suggests that the analysis of facial expressions by a healthy brain would take place approximately 170 ms after the presentation of a facial expression in the superior temporal sulcus and the fusif...Background:Research suggests that the analysis of facial expressions by a healthy brain would take place approximately 170 ms after the presentation of a facial expression in the superior temporal sulcus and the fusiform gyrus,mostly in the right hemisphere.Some researchers argue that a fast pathway through the amygdala would allow automatic and early emotional treatment around 90 ms after stimulation.This treatment would be done subconsciously,even before this stimulus is perceived and could be approximated by presenting the stimuli quickly on the periphery of the fovea.The present study aimed to identify the neural correlates of a peripheral and simultaneous presentation of emotional expressions through a frequency tagging paradigm.Methods:The presentation of emotional facial expressions at a specific frequency induces in the visual cortex a stable and precise response to the presentation frequency[i.e.,a steady-state visual evoked potential(ssVEP)]that can be used as a frequency tag(i.e.,a frequency-tag to follow the cortical treatment of this stimulus.Here,the use of different specific stimulation frequencies allowed us to label the different facial expressions presented simultaneously and to obtain a reliable cortical response being associated with(I)each of the emotions and(II)the different times of presentations repeated(1/0.170 ms=~5.8 Hz,1/0.090 ms=~10.8 Hz).To identify the regions involved in emotional discrimination,we subtracted the brain activity induced by the rapid presentation of six emotional expressions of the activity induced by the presentation of the same emotion(reduced by neural adaptation).The results were compared to the hemisphere in which attention was sought,emotion and frequency of stimulation.Results:The signal-to-noise ratio of the cerebral oscillations referring to the treatment of the expression of fear was stronger in the regions specific to the emotional treatment when they were presented in the subjects peripheral vision,unbeknownst to them.In addition,the peripheral emotional treatment of fear at 10.8 Hz was associated with greater activation within the Gamma 1 and 2 frequency bands in the expected regions(frontotemporal and T6),as well as desynchronization in the Alpha frequency bands for the temporal regions.This modulation of the spectral power is independent of the attentional request.Conclusions:These results suggest that the emotional stimulation of fear presented in the peripheral vision and outside the attentional framework elicit an increase in brain activity,especially in the temporal lobe.The localization of this activity as well as the optimal stimulation frequency found for this facial expression suggests that it is treated by the fast pathway of the magnocellular layers.展开更多
The radial contraction-expansion motion paradigm is a novel steady-state visual evoked experimental paradigm,and the electroencephalography(EEG)evoked potential is different from the traditional luminance modulation p...The radial contraction-expansion motion paradigm is a novel steady-state visual evoked experimental paradigm,and the electroencephalography(EEG)evoked potential is different from the traditional luminance modulation paradigm.The signal energy is concentrated chiefly in the fundamental frequency,while the higher harmonic power is lower.Therefore,the conventional steady-state visual evoked potential recognition algorithms optimizing multiple harmonic response components,such as the extended canonical correlation analysis(eCCA)and task-related component analysis(TRCA)algorithm,have poor recognition performance under the radial contraction-expansion motion paradigm.This paper proposes an extended binary subband canonical correlation analysis(eBSCCA)algorithm for the radial contraction-expansion motion paradigm.For the radial contraction-expansion motion paradigm,binary subband filtering was used to optimize the weighting coefficients of different frequency response signals,thereby improving the recognition performance of EEG signals.The results of offline experiments involving 13 subjects showed that the eBSCCA algorithm exhibits a better performance than the eCCA and TRCA algorithms under the stimulation of the radial contraction-expansion motion paradigm.In the online experiment,the average recognition accuracy of 13 subjects was 88.68%±6.33%,and the average information transmission rate(ITR)was 158.77±43.67 bits/min,which proved that the algorithm had good recognition effect signals evoked by the radial contraction-expansion motion paradigm.展开更多
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2016YFA0300600 and 2016YFA0301500)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant Nos.XDB07030000 and XDBS32000000)+1 种基金the National Natural Science Foundation of China(Grant Nos.11474347 and 31730039)the Fund from the Ministry of Science and Technology of China(Grant No.2015CB351701)
文摘We observed the steady-state visually evoked potential(SSVEP) from a healthy subject using a compact quad-channel potassium spin exchange relaxation-free(SERF) optically pumped magnetometer(OPM). To this end, 30 s of data were collected, and SSVEP-related magnetic responses with signal intensity ranging from 150 fT to 300 f T were observed for all four channels. The corresponding signal to noise ratio(SNR) was in the range of 3.5–5.5. We then used different channels to operate the sensor as a gradiometer. In the specific case of detecting SSVEP, we noticed that the short channel separation distance led to a strongly diminished gradiometer signal. Although not optimal for the case of SSVEP detection, this set-up can prove to be highly useful for other magnetoencephalography(MEG) paradigms that require good noise cancellation.Considering its compactness, low cost, and good performance, the K-SERF sensor has great potential for biomagnetic field measurements and brain-computer interfaces(BCI).
文摘In recent years, Brain Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) have received much attention. This study tries to develop a SSVEP based BCI system that can control a wheelchair prototype in five different positions including stop position. In this study four different flickering frequencies in low frequency region were used to elicit the SSVEPs and were displayed on a Liquid Crystal Display (LCD) monitor using Lab-VIEW. Four stimuli colors, green, red, blue and violet were used to investigate the color influence in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital region were segmented into 1 second window and features were extracted by using Fast Fourier Transform (FFT). One-Against-All (OAA), a popular strategy for multiclass SVM, is used to classify SSVEP signals. During stimuli color comparison SSVEP with violet color showed higher accuracy than that with green, red and blue stimuli.
文摘Purpose: To investigate the variation of visual function in different eccentricities of the visual field in isometropic amblyopes.Method: The stimulus matrix containing 61 hexagons was generated on a monitor. The diameter of the entire stimulating field was approximately 13.6 deg of arc; the frame rate of the monitor was 67 Hz. Every hexagon of the display contained a number of black and white small hexagonal patches which reversed during stimulation. These hexagons were simultaneously but independently modulated in time by the controlling computer program. The flashed elements were selected differently on each frame according to a computer-generated binary pseudo-random time series (m-sequence); the response contributions from each of the individual stimulus elements could be extracted from the cross corre-ation function. Subjects were asked to maintain fixation at the center of the stimulus pattern while each of the hexagons of the display reversed. The VERB system extracted the local responses by
基金Supported by Innovative Talents Training Project in the Basic Educational Stage of Beijing(“Soaring Program”Instrument and Student Training in Aerospace Field,Under No.631306)。
文摘Addressing the vulnerability of contact-based keyboard password systems to disclosure,this paper proposes and validates the feasibility of a non-contact secure password system based on brain-computer interface(BCI)technology that detects steady-state visual evoked potential(SSVEP)signals.The system first lets a testee look at a digital stimulus source flashing at a specific frequency,and uses a wearable dry electrode sensor to collect the SSVEP signal.Secondly,a canonical correlation analysis method is applied to analyze the frequency of the stimulus source that the testee is looking at,and feeds back a code result through headphones.Finally,after all password codes are input,the system makes a judgment and provides visual feedback to the testee.Experiments were conducted to test the accuracy of the system,where twelve stimulus target frequencies between 10-16Hz were selected within the easily recognizable flicker frequency range of human brain,and each of them was tested for 12 times.The results demonstrate that this SSVEP-BCI-based system is feasible,achieving an average accuracy rate of 97.2%,and exhibits promising applications in various domains such as financial transactions and identity recognition.
基金supported by the National Natural Science Foundation of China(Grant Nos.U20A20191,61727807,82071912,12104049)the Beijing Municipal Science&Technology Commission(Grant No.Z201100007720009)+4 种基金the Fundamental Research Funds for the Central Universities(Grant No.2021CX11011)the China Postdoctoral Science Foundation(Grant No.2020TQ0040)the National Key Research and Development Program of China(Grant No.2020YFC2007305)the BIT Research and Innovation Promoting Project(Grant No.2022YCXZ026)the Ensan Foundation(Grant No.2022026)。
文摘The brain-computer interface(BCI)technology has received lots of attention in the field of scientific research because it can help disabled people improve their quality of life.Steady-state visual evoked potential(SSVEP)is the most researched BCI experimental paradigm,which offers the advantages of high signal-to-noise ratio and short training-time requirement by users.In a complete BCI system,the two most critical components are the experimental paradigm and decoding algorithm.However,a systematic combination of the SSVEP experimental paradigm and decoding algorithms is missing in existing studies.In the present study,the transient visual evoked potential,SSVEP,and various improved SSVEP paradigms are compared and analyzed,and the problems and development bottlenecks in the experimental paradigm are finally pointed out.Subsequently,the canonical correlation analysis and various improved decoding algorithms are introduced,and the opportunities and challenges of the SSVEP decoding algorithm are discussed.
基金supported by the Key Research and Development Program of Guangdong Province (No. 2018B030339001)the National Key Research and Development Program of China (No. 2017YFB1002505)the National Natural Science Foundation of China (No. 61431007)
文摘This study explored methods for improving the performance of Steady-State Visual Evoked Potential(SSVEP)-based Brain-Computer Interfaces(BCI), and introduced a new analytical method to quantitatively analyze and reflect the characteristics of SSVEP. We focused on the effect of the pre-stimulation paradigm on the SSVEP dynamic models and the dynamic response process of SSVEP, and performed a comparative analysis of three pre-stimulus paradigms(black, gray, and white). Four dynamic models with different orders(second-and third-order)and with and without a zero point were used to fit the SSVEP envelope. The zero-pole analytical method was adopted to conduct quantitative analysis on the dynamic models, and the response characteristics of SSVEP were represented by zero-pole distribution characteristics. The results of this study indicated that the pre-stimulation paradigm affects the characteristics of SSVEP, and the dynamic models had good fitting abilities with SSVEPs under various types of pre-stimulation. Furthermore, the zero-pole characteristics of the models effectively characterize the damping coefficient, oscillation period, and other SSVEP characteristics. The comparison of zeros and poles indicated that the gray pre-stimulation condition corresponds to a lower damping coefficient, thus showing its potential to improve the performance of SSVEP-BCIs.
基金This work was supported in part by National Natural Science Foundation of China(Grant No.62171473)Beijing Science and Technology Program(Grant No.Z201100004420015)Fundamental Research Funds for the Central Universities of China(Grant No.FRF-TP-20-017A1).
文摘Steady-state visual evoked potential(SSVEP)-based brain-computer interfaces(BCIs)have been widely studied.Considerable progress has been made in the aspects of stimulus coding,electroencephalogram processing,and recognition algorithms to enhance system performance.The properties of SSVEP have been demonstrated to be highly sensitive to stimulus luminance.However,thus far,there have been very few reports on the impact of background luminance on the system performance of SSVEP-based BCIs.This study investigated the impact of stimulus background luminance on SSVEPs.Specifically,this study compared two types of background luminance,i.e.,(1)black luminance[red,green,blue(rgb):(0,0,0)]and(2)gray luminance[rgb:(128,128,128)],and determined their effect on the classification performance of SSVEPs at the stimulus frequencies of 9,11,13,and 15 Hz.The offline results from nine healthy subjects showed that compared with the gray background luminance,the black background luminance induced larger SSVEP amplitude and larger signal-to-noise ratio,resulting in a better classification accuracy.These results suggest that the background luminance of visual stimulus has a considerable effect on the SSVEP and therefore has a potential to improve the BCI performance.
文摘Brain–computer interface is a new form of interaction between humans and machines.This interaction helps the human brain control or operate external devices directly using electroencephalograph(EEG)signals.In this study,we first adopt a canonical correlation analysis method to find the stimulation frequency by calculating the correlation coefficient between the EEG data and multiple sets of harmonics with different frequencies.Then,we select the maximum correlation coefficient as the stimulus frequency and consequently identify steady-state visual evoked potentials.Afterward,we introduce power spectral density to adjust the stimulus frequency and a voting mechanism to reduce the false activation rate.Finally,we build a virtual household electrical appliance brain–computer control interface,which achieves over 72.84%accuracy for three classification problems.
基金This study was supported by Zhongshan ophthalmic Center,SUMS.
文摘Visual functions and nutrition metabolic characteristics werestudied in 8 subjects(16 eyes)with tobacco-toxic optic neuropathy(TTON).Their visual functions tested by psychophysical and electrophysiologicmethods showed that:1.central vision diminished in 16 eyes,2.dyschromatopsias were found in 14 tested eyes,3.bilateral symmetricalcentral or cecocentral scotomas were the visual field characteristics in allcases,4.PVEP were severe abnormal in 3 spatial frequencies in all cases and56.3% of 15' checkboard ...
文摘Background:Research suggests that the analysis of facial expressions by a healthy brain would take place approximately 170 ms after the presentation of a facial expression in the superior temporal sulcus and the fusiform gyrus,mostly in the right hemisphere.Some researchers argue that a fast pathway through the amygdala would allow automatic and early emotional treatment around 90 ms after stimulation.This treatment would be done subconsciously,even before this stimulus is perceived and could be approximated by presenting the stimuli quickly on the periphery of the fovea.The present study aimed to identify the neural correlates of a peripheral and simultaneous presentation of emotional expressions through a frequency tagging paradigm.Methods:The presentation of emotional facial expressions at a specific frequency induces in the visual cortex a stable and precise response to the presentation frequency[i.e.,a steady-state visual evoked potential(ssVEP)]that can be used as a frequency tag(i.e.,a frequency-tag to follow the cortical treatment of this stimulus.Here,the use of different specific stimulation frequencies allowed us to label the different facial expressions presented simultaneously and to obtain a reliable cortical response being associated with(I)each of the emotions and(II)the different times of presentations repeated(1/0.170 ms=~5.8 Hz,1/0.090 ms=~10.8 Hz).To identify the regions involved in emotional discrimination,we subtracted the brain activity induced by the rapid presentation of six emotional expressions of the activity induced by the presentation of the same emotion(reduced by neural adaptation).The results were compared to the hemisphere in which attention was sought,emotion and frequency of stimulation.Results:The signal-to-noise ratio of the cerebral oscillations referring to the treatment of the expression of fear was stronger in the regions specific to the emotional treatment when they were presented in the subjects peripheral vision,unbeknownst to them.In addition,the peripheral emotional treatment of fear at 10.8 Hz was associated with greater activation within the Gamma 1 and 2 frequency bands in the expected regions(frontotemporal and T6),as well as desynchronization in the Alpha frequency bands for the temporal regions.This modulation of the spectral power is independent of the attentional request.Conclusions:These results suggest that the emotional stimulation of fear presented in the peripheral vision and outside the attentional framework elicit an increase in brain activity,especially in the temporal lobe.The localization of this activity as well as the optimal stimulation frequency found for this facial expression suggests that it is treated by the fast pathway of the magnocellular layers.
基金This work is granted by National Natural Science Foundation of China(Grant Nos.62006024,62071057)the Fundamental Research Funds for the Central Universities(BUPT Project No.2019XD17)Aeronautical Science Foundation of China(NO.2019ZG073001).
文摘The radial contraction-expansion motion paradigm is a novel steady-state visual evoked experimental paradigm,and the electroencephalography(EEG)evoked potential is different from the traditional luminance modulation paradigm.The signal energy is concentrated chiefly in the fundamental frequency,while the higher harmonic power is lower.Therefore,the conventional steady-state visual evoked potential recognition algorithms optimizing multiple harmonic response components,such as the extended canonical correlation analysis(eCCA)and task-related component analysis(TRCA)algorithm,have poor recognition performance under the radial contraction-expansion motion paradigm.This paper proposes an extended binary subband canonical correlation analysis(eBSCCA)algorithm for the radial contraction-expansion motion paradigm.For the radial contraction-expansion motion paradigm,binary subband filtering was used to optimize the weighting coefficients of different frequency response signals,thereby improving the recognition performance of EEG signals.The results of offline experiments involving 13 subjects showed that the eBSCCA algorithm exhibits a better performance than the eCCA and TRCA algorithms under the stimulation of the radial contraction-expansion motion paradigm.In the online experiment,the average recognition accuracy of 13 subjects was 88.68%±6.33%,and the average information transmission rate(ITR)was 158.77±43.67 bits/min,which proved that the algorithm had good recognition effect signals evoked by the radial contraction-expansion motion paradigm.