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Functional MRI FABBER FABBER is a Bayesian model fitting tool intended for use in task modelling of ASL data.: FEAT Model-based FMRI analysis with straightforward but powerful GUI: data preprocessing (including slice timing correction, MCFLIRT motion correction and PRELUDE+FUGUE EPI unwarping); FILM GLM timeseries analysis with prewhitening; registration to structural and/or standard space ...
The parameters are Activity, Mobility, and Complexity. They are commonly used in the analysis of electroencephalography signals for feature extraction. The parameters are normalised slope descriptors (NSDs) used in EEG.
The method is a tool for investigating periodic structures in frequency spectra. The power cepstrum has applications in the analysis of human speech. The term cepstrum was derived by reversing the first four letters of spectrum. Operations on cepstra are labelled quefrency analysis (or quefrency alanysis [1]), liftering, or cepstral analysis.
The Hough transform (/ h ĘŚ f /) is a feature extraction technique used in image analysis, computer vision, pattern recognition, and digital image processing. [1] [2] The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.
MS-alone and multiMS-toolbox is a tool chain for mass spectrometry data peak extraction and statistical analysis. mzCloud Website: Web-based mass spectral database that comprises a collection of high and low resolution tandem mass spectrometry data acquired under a number of experimental conditions. MZmine Open source
Shogun, an open-source large-scale machine-learning toolbox that provides several SVM implementations (like libSVM, SVMlight) under a common framework and interfaces to Octave, MATLAB, Python, R; Waffles is a free-software collection of command-line tools designed for scripting machine-learning operations in automated experiments and processes.
EMG measures action potentials, called Motor Unit Action Potentials (MUAPs), created during muscle contraction. A few common uses are determining whether a muscle is active or inactive during movement (onset of activity), assessing the velocity of nerve conduction, and the amount of force generated during movement.
The time-frequency analysis have been applied in various applications like, disease detection from biomedical signals and images, vital sign extraction from physiological signals, brain-computer interface from brain signals, machinery fault diagnosis from vibration signals, interference mitigation in spread spectrum communication systems. [7] [8]