Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In many situations where ambulatory monitoring is needed, the electroencephalogram (EEG) and the electrocardiogram (ECG) are desired to be simultaneously used. Therefore, it would be desirable if one can acquire both EEG and ECG signals with a single measurement. One of the key techniques in such kind of application is to separate EEG and ECG using signal processing techniques. In our study,  have confirmed that by applying non-cephalic reference electrode in the EEG recording, it is possible to obtain ECG signals available for signal processing.  also improved the wavelet shrinkage algorithm by performing window operations in approximation level five of wavelet components to successfully separate the EEG components from the ECG signal. Our results shod that the improved normalized por spectrum re accurate in all frequency bands for the EEG components, while the R peak detection for the ECG re 100 % successful in this study.
['Motoki Sakai', 'Daming Wei']
I am writing a research paper on a idea Wavelet shrinkage applications of EEG-ECG-based human-computer interface
[{"from": "human", "value": "I am writing a research paper on a idea Wavelet shrinkage applications of EEG-ECG-based human-computer interface"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In many situations where ambulatory monitoring is needed, the electroencephalogram (EEG) and the electrocardiogram (ECG) are desired to be simultaneously used. Therefore, it would be desirable if one can acquire both EEG and ECG signals with a single measurement. One of the key techniques in such kind of application is to separate EEG and ECG using signal processing techniques. In our study,  have confirmed that by applying non-cephalic reference electrode in the EEG recording, it is possible to obtain ECG signals available for signal processing.  also improved the wavelet shrinkage algorithm by performing window operations in approximation level five of wavelet components to successfully separate the EEG components from the ECG signal. Our results shod that the improved normalized por spectrum re accurate in all frequency bands for the EEG components, while the R peak detection for the ECG re 100 % successful in this study."}]