scholarly journals Dimensionality Reduction and Channel Selection of Motor Imagery Electroencephalographic Data

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Naeem ◽  
Clemens Brunner ◽  
Gert Pfurtscheller

The performance of spatial filters based on independent components analysis (ICA) was evaluated by employing principal component analysis (PCA) preprocessing for dimensional reduction. The PCA preprocessing was not found to be a suitable method that could retain motor imagery information in a smaller set of components. In contrast, 6 ICA components selected on the basis of visual inspection performed comparably (61.9%) to the full range of 22 components (63.9%). An automated selection of ICA components based on a variance criterion was also carried out. Only 8 components chosen this way performed better (63.1%) than visually selected components. A similar analysis on the reduced set of electrodes over mid-central and centro-parietal regions of the brain revealed that common spatial patterns (CSPs) and Infomax were able to detect motor imagery activity with a satisfactory accuracy.

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1499-1506 ◽  
Author(s):  
Yangwu Zhang ◽  
Guohe Li ◽  
Heng Zong

Dimensionality reduction, including feature extraction and selection, is one of the key points for text classification. In this paper, we propose a mixed method of dimensionality reduction constructed by principal components analysis and the selection of components. Principal components analysis is a method of feature extraction. Not all of the components in principal component analysis contribute to classification, because PCA objective is not a form of discriminant analysis (see, e.g. Jolliffe, 2002). In this context, we present a function of components selection, which returns the useful components for classification by the indicators of the performances on the different subsets of the components. Compared to traditional methods of feature selection, SVM classifiers trained on selected components show improved classification performance and a reduction in computational overhead.


HortScience ◽  
2010 ◽  
Vol 45 (8) ◽  
pp. 1205-1210 ◽  
Author(s):  
Mark K. Ehlenfeldt ◽  
James J. Polashock ◽  
Allan W. Stretch ◽  
Matthew Kramer

Mummy berry disease of blueberry has two distinct phases: a blighting phase that infects emerging shoots and leaves early in the spring and a flower infection phase that ultimately leads to infected (mummified) fruit. Cultivated blueberry (Vaccinium spp.) genotypes that are resistant to one phase are not necessarily resistant to the other phase. The resistance of cultivated blueberry (Vaccinium spp.) genotypes to each phase of the disease is different. A large number of cultivars were screened for resistance to each phase. Cultivar standards (cultivars with well-documented responses to the disease) were used in the screening to evaluate long-term variation and aid comparisons across years. Using nine standards for the blight phase, 125 cultivars were tested and ranked for relative resistance using a ranking system based on resampling and principal component analysis. Similarly, using six standards for the flower/fruit infection stage, 110 blueberry cultivars were tested and ranked for relative resistance. Cultivar rankings show that lowbush cultivars and other types possessing high percentages of lowbush germplasm are generally more resistant to both phases of the disease. Among highbush cultivars, Bluejay is reliably resistant to both phases. Documentation of resistance to each phase will allow selection of cultivars for planting in affected areas and will facilitate the development of breeding strategies to produce cultivars with superior resistance.


1997 ◽  
Vol 15 (1) ◽  
pp. 69-98 ◽  
Author(s):  
Edwin C. Hantz ◽  
Kelley G. Kreilick ◽  
William Kananen ◽  
Kenneth P. Swartz

The event-related evoked potential (ERP) responses to sentence endings that either confirm or violate syntactic/semantic constraints have been extensively studied. Very little is known, however, about the corresponding situation with respect to music. The current study investigates the brain- wave (ERP) responses to perceived phrase closure. ERPs are a potentially valid measure of how language-like or uniquely musical the perception of phrase closure is. In our study, highly trained musicians (N= 16) judged whether or not novel musical phrases were closed (melodically or harmonically). Three stimulus series consisted of seven- note tunes with four possible endings: closed (tonic note or tonic chord), open/ diatonic (dominant chord or a member thereof), open/ chromatic (a chromatic note or chord outside the key of the melody), or open/white noise (a nonmusical control). One series included melodies alone, a second series included melodies harmonized, and a third series included melodies in which the melodic contexts were disrupted rather than the endings. In the recorded ERPs, a statistically significant negative drift in the waveforms occurred over the course of the context series, indicating anticipation of closure. The drift-corrected poststimulus waveforms for all series were subjected to a principal components analysis/analysis of variance. Two subject variables were also considered: sex and absolute pitch. All four stimulus types elicited identifiable responses. The waveform peaks for the four stimulus types are clearly differentiated by principal component analysis scores to two components: one with a maximum value at 273 ms and one with a maximum value at 471 ms. Taking the closed endings as the expected "standard," the waveforms for the two types of musical deviant endings were significantly below the standard at 273 ms and above the standard at 471 ms. The amount of negativity was proportional to the amount of deviance of the ending. The positive peak in the closed condition and the reduced peak in the open/diatonic condition are contrary to the normal inverse relationship between peak size and stimulus probability; the former agrees with peaks found in response to syntactic closure in language. Significant, though isolated, interactions involving both sex and absolute pitch also emerged.


2020 ◽  
Vol 6 (4) ◽  
Author(s):  
Thatcher RW ◽  
Palmero-Soler E ◽  
North DM ◽  
Otte G

EEG artifact is defined as any electrical potential that is not produced by the brain, e.g., eye movement or head movement or muscle, 50 Hz-60 Hz line noise, etc. The most commonly used method of artifact elimination from an EEG recording is to delete the parts of the EEG recording that contain artifact and thereby leave the artifact free parts of the recording unchanged. Recently, Independent Components Analysis (ICA) has been used to decompose the original EEG into a set of components and then subjectively identify components that statistically load on one or more Independent Components (ICs) and using a smaller set of ICs then replace the original EEG recording with a different time series referred to as the ICA replacement or ICA-R. The purpose of this study is to mathematically and empirically test the distortion of the artifact free parts of the EEG when using ICA-R to replace the entire EEG digital record. The results of Joint-Time-Frequency-Analysis (JTFA) and the FFT spectral analyses demonstrated that ICA-Replacement of the original EEG produced phase distortions at each and every time point of the recording between all channel pairs. In contrast, the standard method of deleting the segments of an EEG recording that contain artifact did not distort the artifact free segments of the EEG recording. Conclusions are that ICA Replacement (ICA-R) is a severe distortion of the phase differences and time differences of the electrophysiology of the human scalp recorded Electroencephalogram (EEG) and invalidates all subsequent analyses that rely upon the imaginary part of the crossspectrum including scalp coherence, phase and network analyses that are dependent on the physics of electrical and magnetic fields.


2017 ◽  
Vol 14 (27) ◽  
pp. 30-38
Author(s):  
Filipe ALBANO ◽  
Carla ten CATEN ◽  
Michel ANZANELLO

Proficiency Tests (PT) based on interlaboratory comparisons are activities aimed at assessing the technical competence of laboratories in carrying out specific measurements. The analyses of homogeneity and stability of prepared samples are an important step in ensuring the reliability of the comparison rounds, since improper selection of the parameter to carry out this evaluation can influence the promoted comparison. This paper proposes a method for selecting the most relevant variables aimed at improving homogeneity and stability tests in PT. For that matter, the approach relies on a variable importance index derived from Principal Components Analysis (PCA) parameters. The proposed method was applied to three different PT schemes (beverage, water and coal) in Brazil. Results indicate that the use of PCA was adequate to help the variable selection of homogeneity and stability tests in PT schemes. The selected subset of variables was corroborated by experts in the PT schemes analyzed.


Author(s):  
Carla Barbosa ◽  
M. Rui Alves ◽  
Beatriz Oliveira

Principal components analysis (PCA) is probably the most important multivariate statistical technique, being used to model complex problems or just for data mining, in almost all areas of science. Although being well known by researchers and available in most statistical packages, it is often misunderstood and poses problems when applied by inexperienced users. A biplot is a way of concentrating all information related to sample units and variables in a single display, in an attempt to help interpretations and avoid overestimations. This chapter covers the main mathematical aspects of PCA, as well as the form and covariance biplots developed by Gabriel and the predictive and interpolative biplots devised by Gower and coworkers. New developments are also presented, involving techniques to automate the production of biplots, with a controlled output in terms of axes predictivities and interpolative accuracies, supported by the AutoBiplot.PCA function developed in R. A practical case is used for illustrations and discussions.


2006 ◽  
Vol 3 (3) ◽  
pp. 208-216 ◽  
Author(s):  
M Naeem ◽  
C Brunner ◽  
R Leeb ◽  
B Graimann ◽  
G Pfurtscheller

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