ABSTRACT
Objective To study spatial attention processing characteristics in patients with unilateral spatial neglect (USN)by comparing the patients with right USN and behavioral findings of event-related potential (ERP)in normal subjects and the amplitude and latency of P1,N1 and P300. Methods Ten consecutive patients with USN (USN group)after right-hemisphere stroke admitted to the Department of Rehabilitation Medicine,Xuanwu Hospital,Capital Medical University from April 2012 to April 2013 were enrolled retrospectively. Age-and sex-matched 10 normal subjects with the USN group were selected. ERP was used to document the electroencephalogram changes of two groups of subjects when performing visual Oddball pattern tasks. The response time and accuracy of target stimuli in both groups appearing on the left (left target)and right (right target)were analyzed and compared. The amplitude and latency of all ERP components (P1,N1,P300)on the left and right target stimuli were analyzed by repeated measurement of multivariate analysis of variance. The pathogenesis of USN after stroke was investigated. Results In the USN group,the accuracy of target stimuli on left side and right side was lower than that in the normal group (left target:17. 7 ± 7. 5% vs. 98. 5 ± 7. 5%,P＜0. 01;right target:88. 5 ± 2. 0% vs. 99. 0 ± 2. 0 %,P＝0. 002). There was no significant difference in P1 amplitude between the two groups (F ＝1. 104,P ＝0. 307). When the target stimulus appeared on the left side,the N1 amplitude on the right hemisphere of the USN group was lower than that of the normal group (-0. 3 ± 1. 1 μV vs. -5. 8 ± 1. 1 μV;P＝0. 001), when the target stimulus appeared on the right side,the N1 amplitude of USN group was lower than that of the normal group (-1. 8 ± 1. 0 μV vs. -6. 0 ± 1. 0 μV;F＝9. 799,P＝0. 006). The P300 amplitude of left target of the USN group was lower than that of the normal group (1. 0 ± 1. 1 μV vs. 7. 2 ± 1. 1 μV;P＝0. 001). Compared with the normal group,the latency of each wave of P1 (right hemisphere)(136. 7 ± 3. 8 ms vs. 122. 1 ± 3. 8 ms;P ＝0. 013),N1 (179. 7 ± 2. 0 ms vs. 172. 8 ± 2. 0 ms;F ＝5. 775,P ＝0. 027),and P300 (490 ± 12 ms vs. 402 ± 12 ms;F＝27. 310,P＜0. 01]in the USN group was prolonged. Conclusion During the spatial attention processing in patients with USN,regardless of the stimuli from the left and right,its information processing had been damaged to a certain degree.
ABSTRACT
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 denoising. 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.
Subject(s)
Humans , Algorithms , Ballistocardiography , Methods , Monitoring, PhysiologicABSTRACT
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 denoising and meanwhile keep the characteristics of original ECG signal.
Subject(s)
Humans , Algorithms , Electrocardiography , Signal Processing, Computer-Assisted , Wavelet AnalysisABSTRACT
Objective To explore disinfection efficacy of anerdian using swab and spray disinfection methods.Methods Hands of 30 subjects were randomly divided into the swab group and the spray group.The samples of before and after disinfection in each group were collected separately and observed their disinfection effect.Results The number of bacteria showed no significant difference between the two groups.The passing rate of disinfection reached 100％.The time of disinfection in the spray group was (2.58±0.32)s,significantly less than that in the swab group,(12.26±1.48)s,however,the drying time in the spray group was (42.37±1.79)s,significant longer than that in the swab group,(26.24±1.46)s.A subject hand disinfection used 0.5ml 0.2％ anerdian in the spray group,and 0.75ml 0.2％ anerdian and two cotton buds was used in the swab group.Conclusions There is identical disinfection efficacy between spray and swab methods.Spray disinfection method has short operating time,less use of disinfectant without using cotton buds,it is able to replace swab disinfection and will play an important role to reduce medical waste and health care costs.