EEG Calmness Index Establishment Using Computational of Z-Score
نویسندگان
چکیده
منابع مشابه
Antiretroviral therapy affects the z-score index of deviant cortical EEG rhythms in naïve HIV individuals
OBJECTIVE Here we tested the effect of combined antiretroviral therapy (cART) on deviant electroencephalographic (EEG) source activity in treatment-naïve HIV individuals. METHODS Resting state eyes-closed EEG data were recorded before and after 5 months of cART in 48 male HIV subjects, who were naïve at the study start. The EEG data were also recorded in 59 age- and sex-matched healthy subjec...
متن کاملReducing Inter-Laboratory Differences between Semen Analyses Using Z Score and Regression Transformations
Background Standardization of the semen analysis may improve reproducibility. We assessed variability between laboratories in semen analyses and evaluated whether a transformation using Z scores and regression statistics was able to reduce this variability. MaterialsAndMethods We performed a retrospective cohort study. We calculated between-laboratory coefficients of variation (CVB) for sperm c...
متن کاملLORETA Z Score Biofeedback
Today we are riding the crest of a wave of converging new neuroscience In the physics of source localization the forward solution is where a source inside a sphere determines the electrical potential on the surface as calculated using Maxwell's 1864 equations. In contrast, the inverse problem is where the sources are unknown and the location of the sources are estimated by measuring the electri...
متن کاملAnalysis of microarray data using Z score transformation.
High-throughput cDNA microarray technology allows for the simultaneous analysis of gene expression levels for thousands of genes and as such, rapid, relatively simple methods are needed to store, analyze, and cross-compare basic microarray data. The application of a classical method of data normalization, Z score transformation, provides a way of standardizing data across a wide range of experi...
متن کاملZ-Score Linear Discriminant Analysis for EEG Based Brain-Computer Interfaces
Linear discriminant analysis (LDA) is one of the most popular classification algorithms for brain-computer interfaces (BCI). LDA assumes Gaussian distribution of the data, with equal covariance matrices for the concerned classes, however, the assumption is not usually held in actual BCI applications, where the heteroscedastic class distributions are usually observed. This paper proposes an enha...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Engineering & Technology
سال: 2018
ISSN: 2227-524X
DOI: 10.14419/ijet.v7i4.11.20686