The power of controlling objects with mind has captivated a popular fascination to human beings.One possible path is to employ brain signal collecting technologies together with emerging programmable metasurfaces(PM),...The power of controlling objects with mind has captivated a popular fascination to human beings.One possible path is to employ brain signal collecting technologies together with emerging programmable metasurfaces(PM),whose functions or operating modes can be switched or customized via on-site programming or pre-defined software.Nevertheless,most of existing PMs are wire-connected to users,manually-controlled and not real-time.Here,we propose the concept of remotely mind-controlled metasurface(RMCM)via brainwaves.Rather than DC voltage from power supply or AC voltages from signal generators,the metasurface is controlled by brainwaves collected in real time and transmitted wirelessly from the user.As an example,we demonstrated a RMCM whose scattering pattern can be altered dynamically according to the user’s brain waves via Bluetooth.The attention intensity information is extracted as the control signal and a mapping between attention intensity and scattering pattern of the metasurface is established.With such a framework,we experimentally demonstrated and verified a prototype of such metasurface system which can be remotely controlled by the user to modify its scattering pattern.This work paves a new way to intelligent metasurfaces and may find applications in health monitoring,5G/6G communications,smart sensors,etc.展开更多
To listen to brain activity as a piece of music, we proposed the scale-free brainwave music(SFBM) technology, which could translate the scalp electroencephalogram(EEG) into music notes according to the power law of bo...To listen to brain activity as a piece of music, we proposed the scale-free brainwave music(SFBM) technology, which could translate the scalp electroencephalogram(EEG) into music notes according to the power law of both EEG and music. In the current study, this methodology was further extended to a musical ensemble of two channels. First, EEG data from two selected channels are translated into musical instrument digital interface(MIDI) sequences, where the EEG parameters modulate the pitch, duration, and volume of each musical note. The phase synchronization index of the two channels is computed by a Hilbert transform. Then the two MIDI sequences are integrated into a chorus according to the phase synchronization index. The EEG with a high synchronization index is represented by more consonant musical intervals, while the low index is expressed by inconsonant musical intervals. The brain ensemble derived from real EEG segments illustrates differences in harmony and pitch distribution during the eyes-closed and eyes-open states. Furthermore, the scale-free phenomena exist in the brainwave ensemble. Therefore, the scale-free brain ensemble modulated by phase synchronization is a new attempt to express the EEG through an auditory and musical way, and it can be used for EEG monitoring and bio-feedback.展开更多
A brainwave classification,which does not involve any limb movement and stimulus for character-writing applications,benefits impaired people,in terms of practical communication,because it allows users to command a dev...A brainwave classification,which does not involve any limb movement and stimulus for character-writing applications,benefits impaired people,in terms of practical communication,because it allows users to command a device/computer directly via electroencephalogram signals.In this paper,we propose a new framework based on Empirical Mode Decomposition(EMD)features along with theGaussianMixtureModel(GMM)andKernel Extreme Learning Machine(KELM)-based classifiers.For this purpose,firstly,we introduce EMD to decompose EEG signals into Intrinsic Mode Functions(IMFs),which actually are used as the input features of the brainwave classification for the character-writing application.We hypothesize that EMD along with the appropriate IMF is quite powerful for the brainwave classification,in terms of character applications,because of the wavelet-like decomposition without any down sampling process.Secondly,by getting motivated with shallow learning classifiers,we can provide promising performance for the classification of binary classes,GMM and KELM,which are applied for the learning of features along with the brainwave classification.Lastly,we propose a new method by combining GMMand KELM to fuse the merits of different classifiers.Moreover,the proposed methods are validated by using the volunteer-independent 5-fold cross-validation and accuracy as a standard measurement.The experimental results showed that EMD with the proper IMF achieved better results than the conventional discrete wavelet transform(DWT)feature.Moreover,we found that the EMD feature along with the GMM/KELM-based classifier provides the average accuracy of 77.40%and 80.10%,respectively,which could perform better than the conventional methods where we use DWT along with the artificial neural network classifier in order to get the average accuracy of 80.60%.Furthermore,we obtained the improved performance by combining GMM and KELM,i.e.,average accuracy of 80.60%.These outcomes exhibit the usefulness of the EMD feature combining with GMMand KELM based classif展开更多
Neurexan is a multicomponent natural medicinal product?used?for?stress-related?symptoms such as nervous restlessness and insomnia. The present study?investigated?the?efficacy?of Neurexan on stress-induced changes of b...Neurexan is a multicomponent natural medicinal product?used?for?stress-related?symptoms such as nervous restlessness and insomnia. The present study?investigated?the?efficacy?of Neurexan on stress-induced changes of brainwave frequencies?using quantitative analysis of spectral EEG power. Thirty healthy male and female volunteers were tested in a randomized, placebo controlled cross-over trial under conditions of relaxation and experimental stress-in-?duction. Recording of the EEG was performed over four hours after drug administration. Data was?analyzed using the proprietary fast dynamic EEG technology Neurocode-Tracking. Quantitative EEG revealed a task dependent increase of beta2 power as a surrogate parameter of stress induced anxiety. The elevated frontotemporal beta2 power was ameliorated by intake of Neurexan during the second and third hour after administration. This indicates that Neurexan is effectively helping subjects to better cope with task-related stress situations.展开更多
Purpose:To investigate the intervention effiects of using traditional Chinese Guqin music and Chinese Calligraphy handwriting(CCH)for patients with Primary Insomnia.Methods:A total of ninety patients were assigned to ...Purpose:To investigate the intervention effiects of using traditional Chinese Guqin music and Chinese Calligraphy handwriting(CCH)for patients with Primary Insomnia.Methods:A total of ninety patients were assigned to control group,Guqin group,and calligraphy group for 8 weeks.For 5 days a week,patients’heart rate variability(HRV)and frontal midline(FZ)electroencephalographic signals were recorded in a clinic during interventional period while either listening to Guqin music or writing calligraphy.Patients in the control group remained in rest condition.Results:For the Guqin group,the higher low-frequency-range HRV of coherence was found with marginal significance(P=0.055),and heart rate was significantly reduced(P<0.05)during Hie 4^th week in listening to Guqin music compared to the prerest period.For listening to Guqin music or calligraphy intervention,FZδ,FZθ,and FZα waves in the 8^th week compared to the 0^th week(Pre Intervention)showed a significantly enhanced effect(.P<0.05).Between the three groups,for heart rate and FZδ and FZθ waves,calligraphy group showed significantly increased heart rate than the Guqin group(P<0.001)and the control group(P=0.004);increased FZδ wave than die Guqin group(P<0.001)and the control group(P<0.001);and increased FZθ wave than the Guqin group(P=0.024)and the control group(P=0.008)respectively.Conclusion:Positive intervention effects on 11RV coherence of Guqin music;FZδ,FZθ,and FZα waves of Guqin music and calligraphy proved that Guqin music together with calligraphy training helping to promote physical and mental health,thereby it contributes to the clinical application of TCM Psychology for patients with insomnia syndrome.展开更多
Brain waves measured by EEG are created by very complex interactions of large number of neurons.Brainwaves are in five frequency bands–Delta(0.5–4 Hz),Theta(4-8 Hz),Alpha(8-12 Hz),Beta(12-40 Hz),and Gamma(40-100 Hz)...Brain waves measured by EEG are created by very complex interactions of large number of neurons.Brainwaves are in five frequency bands–Delta(0.5–4 Hz),Theta(4-8 Hz),Alpha(8-12 Hz),Beta(12-40 Hz),and Gamma(40-100 Hz).As we become more conscious our brainwave frequency increases.Hence,our consciousness is a function of brain wave frequency and is given by brain wave frequency multiplied by consciousness constant Consciere C.This is similar to any other physical constant like Gravitational constant G,Planck Constant h,etc.When our brain is dead,we have no consciousness.展开更多
基金National Natural Science Foundation of China under Grant Nos.61971435,62101588,62101589National Key Research and Development Program of China(Grant No.:SQ2017YFA0700201)+1 种基金C.-W.Q.is supported by a grant(R-261-518-004-720|A-0005947-16-00)from Advanced Research and Technology Innovation Centre(ARTIC)in National University of Singapore.
文摘The power of controlling objects with mind has captivated a popular fascination to human beings.One possible path is to employ brain signal collecting technologies together with emerging programmable metasurfaces(PM),whose functions or operating modes can be switched or customized via on-site programming or pre-defined software.Nevertheless,most of existing PMs are wire-connected to users,manually-controlled and not real-time.Here,we propose the concept of remotely mind-controlled metasurface(RMCM)via brainwaves.Rather than DC voltage from power supply or AC voltages from signal generators,the metasurface is controlled by brainwaves collected in real time and transmitted wirelessly from the user.As an example,we demonstrated a RMCM whose scattering pattern can be altered dynamically according to the user’s brain waves via Bluetooth.The attention intensity information is extracted as the control signal and a mapping between attention intensity and scattering pattern of the metasurface is established.With such a framework,we experimentally demonstrated and verified a prototype of such metasurface system which can be remotely controlled by the user to modify its scattering pattern.This work paves a new way to intelligent metasurfaces and may find applications in health monitoring,5G/6G communications,smart sensors,etc.
基金Project supported by the National Natural Science Foundation of China(Nos.81201159,91232725,and 81330032)the China Postdoctoral Science Foundation(No.2014M550607)
文摘To listen to brain activity as a piece of music, we proposed the scale-free brainwave music(SFBM) technology, which could translate the scalp electroencephalogram(EEG) into music notes according to the power law of both EEG and music. In the current study, this methodology was further extended to a musical ensemble of two channels. First, EEG data from two selected channels are translated into musical instrument digital interface(MIDI) sequences, where the EEG parameters modulate the pitch, duration, and volume of each musical note. The phase synchronization index of the two channels is computed by a Hilbert transform. Then the two MIDI sequences are integrated into a chorus according to the phase synchronization index. The EEG with a high synchronization index is represented by more consonant musical intervals, while the low index is expressed by inconsonant musical intervals. The brain ensemble derived from real EEG segments illustrates differences in harmony and pitch distribution during the eyes-closed and eyes-open states. Furthermore, the scale-free phenomena exist in the brainwave ensemble. Therefore, the scale-free brain ensemble modulated by phase synchronization is a new attempt to express the EEG through an auditory and musical way, and it can be used for EEG monitoring and bio-feedback.
基金the SUT research and development fund,and in part by the National Natural Science Foundation of China under Grant 61771333All subjects gave their informed consent for inclusion before they participated in the study.The study was conducted in accordance with the Declaration of Helsinki and the protocol was approved by the Ethics Committee of Suranaree University of Technology(License EC-61-14 COA No.16/2561).
文摘A brainwave classification,which does not involve any limb movement and stimulus for character-writing applications,benefits impaired people,in terms of practical communication,because it allows users to command a device/computer directly via electroencephalogram signals.In this paper,we propose a new framework based on Empirical Mode Decomposition(EMD)features along with theGaussianMixtureModel(GMM)andKernel Extreme Learning Machine(KELM)-based classifiers.For this purpose,firstly,we introduce EMD to decompose EEG signals into Intrinsic Mode Functions(IMFs),which actually are used as the input features of the brainwave classification for the character-writing application.We hypothesize that EMD along with the appropriate IMF is quite powerful for the brainwave classification,in terms of character applications,because of the wavelet-like decomposition without any down sampling process.Secondly,by getting motivated with shallow learning classifiers,we can provide promising performance for the classification of binary classes,GMM and KELM,which are applied for the learning of features along with the brainwave classification.Lastly,we propose a new method by combining GMMand KELM to fuse the merits of different classifiers.Moreover,the proposed methods are validated by using the volunteer-independent 5-fold cross-validation and accuracy as a standard measurement.The experimental results showed that EMD with the proper IMF achieved better results than the conventional discrete wavelet transform(DWT)feature.Moreover,we found that the EMD feature along with the GMM/KELM-based classifier provides the average accuracy of 77.40%and 80.10%,respectively,which could perform better than the conventional methods where we use DWT along with the artificial neural network classifier in order to get the average accuracy of 80.60%.Furthermore,we obtained the improved performance by combining GMM and KELM,i.e.,average accuracy of 80.60%.These outcomes exhibit the usefulness of the EMD feature combining with GMMand KELM based classif
文摘Neurexan is a multicomponent natural medicinal product?used?for?stress-related?symptoms such as nervous restlessness and insomnia. The present study?investigated?the?efficacy?of Neurexan on stress-induced changes of brainwave frequencies?using quantitative analysis of spectral EEG power. Thirty healthy male and female volunteers were tested in a randomized, placebo controlled cross-over trial under conditions of relaxation and experimental stress-in-?duction. Recording of the EEG was performed over four hours after drug administration. Data was?analyzed using the proprietary fast dynamic EEG technology Neurocode-Tracking. Quantitative EEG revealed a task dependent increase of beta2 power as a surrogate parameter of stress induced anxiety. The elevated frontotemporal beta2 power was ameliorated by intake of Neurexan during the second and third hour after administration. This indicates that Neurexan is effectively helping subjects to better cope with task-related stress situations.
文摘Purpose:To investigate the intervention effiects of using traditional Chinese Guqin music and Chinese Calligraphy handwriting(CCH)for patients with Primary Insomnia.Methods:A total of ninety patients were assigned to control group,Guqin group,and calligraphy group for 8 weeks.For 5 days a week,patients’heart rate variability(HRV)and frontal midline(FZ)electroencephalographic signals were recorded in a clinic during interventional period while either listening to Guqin music or writing calligraphy.Patients in the control group remained in rest condition.Results:For the Guqin group,the higher low-frequency-range HRV of coherence was found with marginal significance(P=0.055),and heart rate was significantly reduced(P<0.05)during Hie 4^th week in listening to Guqin music compared to the prerest period.For listening to Guqin music or calligraphy intervention,FZδ,FZθ,and FZα waves in the 8^th week compared to the 0^th week(Pre Intervention)showed a significantly enhanced effect(.P<0.05).Between the three groups,for heart rate and FZδ and FZθ waves,calligraphy group showed significantly increased heart rate than the Guqin group(P<0.001)and the control group(P=0.004);increased FZδ wave than die Guqin group(P<0.001)and the control group(P<0.001);and increased FZθ wave than the Guqin group(P=0.024)and the control group(P=0.008)respectively.Conclusion:Positive intervention effects on 11RV coherence of Guqin music;FZδ,FZθ,and FZα waves of Guqin music and calligraphy proved that Guqin music together with calligraphy training helping to promote physical and mental health,thereby it contributes to the clinical application of TCM Psychology for patients with insomnia syndrome.
文摘Brain waves measured by EEG are created by very complex interactions of large number of neurons.Brainwaves are in five frequency bands–Delta(0.5–4 Hz),Theta(4-8 Hz),Alpha(8-12 Hz),Beta(12-40 Hz),and Gamma(40-100 Hz).As we become more conscious our brainwave frequency increases.Hence,our consciousness is a function of brain wave frequency and is given by brain wave frequency multiplied by consciousness constant Consciere C.This is similar to any other physical constant like Gravitational constant G,Planck Constant h,etc.When our brain is dead,we have no consciousness.
