A reliable and unobtrusive quantification of changes in cortical activity during short-term memory task can be used to evaluate the efficacy of interfaces and to provide real-time user-state information. In this article, we investigate changes in electroencephalogram signals in short-term memory with respect to the baseline activity. The electroencephalogram signals have been analyzed using 9 linear and nonlinear/dynamic measures. We applied statistical Wilcoxon examination and Davis-Bouldian criterion to select optimal discriminative features. The results show that among the features, the permutation entropy significantly increased in frontal lobe and the occipital second lower alpha band activity decreased during memory task. These 2 features reflect the same mental task; however, their correlation with memory task varies in different intervals. In conclusion, it is suggested that the combination of the 2 features would improve the performance of memory based neurofeedback systems.
This study is conducted with the aim of validating the Saadat non-invasive blood pressure (NIBP) module accuracy and reliability against direct intra arterial pressure measurement (IBP) according to the ANSI/AAMI SP10-2002 guidelines. Measurement and comparison procedure were done in a static population of 19 adult patients with brachial catheterized arterial line with total measurements of 195 under supervision of a highly experienced cardiovascular anesthesiologist in accordance with the ANSI/AAMI SP10-2002 regulation. Data analysis was performed based on the protocol criteria. In order to represent relationships between the test device and the reference method, Bland-Altman graphical plotting method was used. The mean ± SD differences between the readings of Saadat NIBP device and IBP as the reference method for systolic, diastolic and map pressures were: -0.9 ± 6.95 mmHg for systolic, 2.57 ± 7.79 mmHg for Diastolic, and 3.89 ± 7.06 mmHg for Map. The Saadat NIBP module fulfilled the ANSI/AAMI SP10-2002 requirement that is the mean ± SD of lower than 5 ± 8 mmHg.
Glioblastoma Multiform (GBM) is the most common cause of cancer death in both men and women. Bevacizumab is a recent therapy for stopping the tumor growth. The purpose of this paper is to present our reproducibility study of predicting response of the brain tumors to Bevacizumab treatment. This method allows physicians to select most effective treatment plans. We take two image series of patients before and after the treatment. After constructing Eigen images, we extract their statistical histogram features and then use regression analysis to develop a predictive model. Predictive models of response are developed with large regression coefficients (maximum R2=0.8). This method is dependent on the operator. To decrease the operator's role, this method is repeated four times for each patient. Then, the average of the achieved results is used for regression analysis. As a result, the regression coefficient increases (maximum R 2 =0.86). The result of this approach is compared to that of a previous work at the University of Tehran showing excellent reproducibility of the proposed method.
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