A de-noising method for electrocardiogram (ECG) based on ensemble empirical mode decomposition (EEMD) and wavelet threshold de-noising theory is proposed in our school. We decomposed noised ECG signals with the proposed method using the EEMD and calculated a series of intrinsic mode functions (IMFs). Then we selected IMFs and reconstructed them to realize the de-noising for ECG. The processed ECG signals were filtered again with wavelet transform using improved threshold function. In the experiments, MIT-BIH ECG database was used for evaluating the performance of the proposed method, contrasting with de-noising method based on EEMD and wavelet transform with improved threshold function alone in parameters of signal to noise ratio (SNR) and mean square error (MSE). The results showed that the ECG waveforms de-noised with the proposed method were smooth and the amplitudes of ECG features did not attenuate. In conclusion, the method discussed in this paper can realize the ECG de-noising and meanwhile keep the characteristics of original ECG signal.
Ballistocardiogram (BCG) signal is a physiological signal, reflecting heart mechanical status. It can be measured without any electrodes touching subject's body surface and can realize physiological monitoring ubiquitously. However, BCG signal is so weak that it would often be interferred by superimposed noises. For measuring BCG signal effectively, we proposed an approach using joint time-frequency distribution and empirical mode decomposition (EMD) for BCG signal de-noising. We set up an adaptive optimal kernel for BCG signal and extracted BCG signals components using it. Then we de-noised the BCG signal by combing empirical mode decomposition with it. Simulation results showed that the proposed method overcome the shortcomings of empirical mode decomposition for the signals with identical frequency content at different times, realized the filtering for BCG signal and also reconstructed the characteristics of BCG.
ObjectiveTo investigate clinical features and progress in women with catamenial epilepsy. MethodsThe data obtained from retrospective study in 20 patients with catamenial epilepsy and reviewing published study of catamenial epilepsy. ResultsSeizures of all cases were relatived with the menstrual cycle. Seizures that only occured perimenstrually in 7 cases, 13 cases experienced exacerbation during this time. Only 2 of the 20 cases pointed to generalized sizures.12 of 18 cases which were partial seizures identified with complex partial seizures. Of 17 patients who had EEG results, 1 showed mild abnormal waves, 1 showed slow waves, 1 showed sharp waves, 1 showed spike and slow wave complex, 2 showed generalized polyspike and slow wave complex, 11 showed focal sharp waves,spike waves and spike and slow wave complex. All patients accepted 1 or more AEDs treatment.1 patient seizure free for 2 years after menopause, 2 cases of treatment were unclear, 5 cases had positive outcomes(4 cases seizure free for 1 and more years,1 case for 6 months), 12 cases were poorly controlled, especially 9 cases were refractory epilepsy. ConclusionIt is found that catamenial epilepsy more commonly in facal and the rate of refractory epilepsy is higher. Treatment of catamenial epilepsy power with more samples, multi-center clinical trials.