finger vein is one of the most fitting biometric for identifying individuals. in this paper a new method for finger vein recognition is proposed. first the veins are extracted from finger vein images by using entropy based thresholding. in finger vein images the veins are appeared as dark lines. the method extracts veins as well, but the images are noisy, that means in addition to the veins the...

A major challenge in electroencephalogram (EEG)based brain–computer interfaces (BCIs) is the inherent nonstationarities in the EEG data. Variations of the signal properties from intra and inter sessions often lead to deteriorated BCI performances, as features extracted by methods such as common spatial patterns (CSP) are not invariant against the changes. To extract features that are robust and...

PURPOSE To design a contrast sensitivity perimetry (CSP) protocol that decreases variability in glaucomatous defects while maintaining good sensitivity to glaucomatous loss. METHODS Twenty patients with glaucoma and 20 control subjects were tested with a CSP protocol implemented on a monitor-based testing station. In the protocol 26 locations were tested over the central visual field with Gab...

We present a novel multitask learning framework called multitask generalized eigenvalue program (MTGEP), which jointly solves multiple related generalized eigenvalue problems (GEPs). This framework is quite general and can be applied to many eigenvalue problems in machine learning and pattern recognition, ranging from supervised learning to unsupervised learning, such as principal component ana...

As an emerging technology, brain-computer interfaces (BCIs) bring us new communication interfaces which translate brain activities into control signals for devices like computers, robots, and so forth. In this study, we propose a semisupervised support vector machine (SVM) algorithm for brain-computer interface (BCI) systems, aiming at reducing the time-consuming training process. In this algor...

Dimension reduction methods are often applied in machine learning and data mining problems. Linear subspace methods are the commonly used ones, such as principal component analysis (PCA), Fisher’s linear discriminant analysis (FDA), common spatial pattern (CSP), et al. In this paper, we describe a novel feature extraction method for binary classification problems. Instead of finding linear subs...

Objectives: Acetaminophen (APAP) toxicity is known to be common and potentially fatal. This study aims to investigate the protective effects of hydroalcoholic extract, remaining from Crocus sativus petals (CSP) against APAP-induced hepatotoxicity by measuring the blood parameters and studying the histopathology of liver in male rats. Materials and Methods: Wister rats (24) were randomly assigne...

We present an offline analysis of a large set of BCI experiments, focusing on common spatial filters and patterns (CSP). First, we show that it is possible to infer from the CSP filters whether the cross-validation error of LDA-classified EEG data preprocessed by this CSP will be high or low and predict thus the future performance of the feedback sessions following the calibration. Our test is ...