SEARCH · PubMed Health

Results for “Principal component”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed1992

[Classification of congenital superior oblique palsy based on principal component analysis].

An attempt was to classify unilateral congenital superior oblique palsy principal component analysis. Each principal component was calculated by taking a linear combination of an eigenvector of the correlation matrix with a standardized original variable. The variables selected for the analysis were vertical deviation in the nine diagnostic positions of 51 cases measured by a synoptometer. The cumulative contributive percent of principal components showed that 88.5% of the variation were accounted for by the first three principal components. The first principal component accounted for 56.7% of the variation in samples indicating the extent of superior oblique palsy in which vertical deviation increases or decreases proportionately. The second principal component accounted for 20.6% of the variation of samples indicating the extent of the incomitance of vertical deviation with a vertical change of gaze. The third principal component accounted for 11.1% of the variation in the sample indicating the extent of the vertical deviation with a horizontal change of gaze.

Adolescent↗

PubMed1992

Measurement processes and spatial principal components analysis.

Spatial principal components analysis (SPCA) applied to the ongoing EEG yields factor loadings which, when mapped, consistently reveal symmetrical patterns resembling the spherical harmonics. In this paper, we consider the mechanisms responsible for these characteristic patterns. In doing so, we demonstrate that volume conduction is one of a family of processes capable of generating such patterns with SPCA. It is shown that any series of measurements on a sphere in which the covariance is only a function of measurement site angular separation (shift invariant processes) will yield the spherical harmonics as the eigenvectors or factor loadings of the covariance matrix. Simulations further indicate that this effect is robust and not determined by the geometry of the measurement sites. In situations where shift invariant signals coexist with those generated at specific sites (anatomically specific processes), such as evoked potentials and some artifacts, it is shown that the anatomically specific signals do not influence the eigenvectors of the covariance matrix in a uniform or random fashion. The factors most influenced are those whose symmetry is similar to that of the site specific signal.

Brain↗

PubMed1990

Multivariate data reduction by principal components, with application to neurological scoring instruments.

Principal components analysis is widely used as a practical tool for the analysis of multivariate data. The aim of this analysis is to reduce the dimensionality of a multivariate data set to the smallest number of meaningful and independent dimensions. The analysis can also provide interpretable linear functions of the original measured variables that may serve as valuable indices of variation. A brief introduction to principal components analysis is given herein, followed by an examination of a particular set of multivariate data accruing from a study of acute brain injuries in a pediatric population, in which severity of brain injury had been assessed with the Glasgow Coma Scale (CGS). Principal components analysis reveals that the GCS sum score is a particularly inefficient summarizer of information in this cohort. The determination of an objective weighting of measured variables, as provided through principal components analysis, is essential in the construction of meaningful neurological scoring instruments.

Coma↗

PubMed1992

Composite index of skeletal mass: principal components analysis of regional bone mineral densities.

Principal components analysis is a statistical method that is used to reduce and explore data to facilitate further analyses. This method was applied to bone mineral densities measured at seven sites in 109 black and 44 white women, ages 22-80, at an internal medicine clinic in urban Detroit. We excluded subjects with a history of diseases or drugs known to affect bone metabolism. Principal components analysis was used to summarize the interrelationship of the densities and yielded two major results. First, the seven site measurements were reduced to a single, composite index (PC1) of skeletal mass that accounted for 73% of the variation in density among subjects. PC1 had roughly equal weights among the sites. A second combination of the seven sites indicated that the contrast between axial and appendicular regional densities accounted for another 10% of the variation among subjects. In investigating the relationship of density to age, body mass index, and ethnic group, we found that the principal components composite index had a stronger correlation with age (r = -0.58) and with body mass index (r = 0.34) than almost all of the regional densities. Black-white differences were larger for the composite index than for any single site density. A multiple regression of the composite index on ethnicity, body mass index, and age yielded a larger R2 (0.46) than any of the individual site densities. The second principal component, although of theoretical interest, showed a minimal ability to discriminate among subjects using the three independent variables of this study.

Absorptiometry, Photon↗

PubMed1975

Selecting key parameters in pharmaceutical formulations by principal component analysis.

The role of principal component analysis in the selection of pharmaceutical formulations is presented. The objective and the procedure of the analysis are discussed in detail. The technique was successfully applied to a system consisting of 10 response variables (tablet properties). Analysis of the results showed that the first component (dissolution) and components one and two together (dissolution and disintegration) contributed 95.4 and 99.3%, respectively, to the overall information about the formulations and that eight of 10 response parameters contributed nothing further to the overall information. The results obtained from this method of analysis may be found useful for achieving economy in both cost and time of measuring response. Principal component analysis also provides a basis for understanding the underlying mechanism of the system under consideration.

Computers↗

PubMed1991

Evaluation of a principal-components tactile aid for the hearing-impaired.

Principal component analysis, a statistical data reduction technique which can be used to eliminate redundant information, has shown promising results as a speech coding strategy in auditory perceptual studies. The present study describes the development, modification, and evaluation of a principal components-based tactile aid for speech perception by the hearing-impaired. In this device, the first two principal components of an input speech signal were displayed on two-dimensional arrays of vibrators contacting either the fingertip or the forearm. Initial testing of the device with closed-set recorded speech tokens showed fair recognition performance, reaching 57% for three consonants and 56% for four vowels. Modifications to the processor algorithm designed to improve vowel recognizability resulted in higher levels of performance (66% for eight vowels). A real-time prototype was constructed implementing the revised algorithm. Live-voice testing was conducted with six normal-hearing subjects, three of whom had previous training with the Queen's University vocoder, a multichannel tactile vocoder that has shown promising results. Performance of these "trained" subjects for both single-item and connected speech tasks was excellent, equalling levels obtained with the Queen's vocoder. These results suggest that a principal components design may be a promising alternative to a vocoder strategy for a tactile aid. Results for the "naive" subjects did not reach the levels attained by the trained subjects, a finding partially attributed to the short training period available to the naive subjects. The higher level of performance for the trained subjects, together with the similarity of performance for the principal components aid and the Queen's vocoder for these subjects, suggests that they were able to transfer previous learning with the Queen's vocoder to the principal components device.

Adult↗

PubMed1992

Morphology of the normal visual field in a population-based random sample: principal components analysis.

I applied principal components analysis to Humphrey central 24-2 threshold values from both eyes of 304 clinically normal persons selected by simple random sample from Barbados, WI. The first component, accounting for 62 per cent of the variation, is equivalent to the average threshold value within persons. The first eigenvector, when represented by grey scale maps depicting a pair of eyes, reveals that, as average threshold increases, the visual field rises and flattens, like an umbrella that, initially closed, is simultaneously opened and thrust upwards. I verify three numerical predictions based upon this umbrella description. Much less important sources of variation involve disparity between fellow eyes, and hemimeridional and other symmetric differences within eyes. I discuss briefly possible physiologic explanatory mechanisms.

Barbados↗

PubMedDate not supplied

Chemometric differentiation of raw and commercial milk by trace elements using principal component analysis.

Nine trace elements (Cr, Mn, Fe, Ni, Cu, Zn, Mo, Cd, and Pb) were determined in the dissolved ash of 36 samples of raw milk. The distribution of the concentration of each element was first investigated by means of a test of normality. The matrix of the correlation between the concentrations of the elements was then used as a starting matrix for principal component analysis. Nine variables were reduced to four principal components, accounting for 75% of the total variance. The biophilic elements Mn-Fe and Cu-Mo were positively associated with the first two principal components, while Cr was correlated to the third and Ni and Cd with the fourth principal component. Pb and Zn are both negatively correlated to the first principal component. Comparison with 42 samples of a commercial milk, by using a two-dimensional plot of the principal component scores, rendered possible the differentiation between raw and commercial milk.

Animals↗

PubMed1979

Craniofacial morphology: a principal component analysis.

A series of 56 measurements was derived from lateral cephalometric radiographs of a large sample of subjects. These measurements were subjected to a principal-component analysis which resulted in a series of six components (factors). These factors, represented in general terms and in rank order of their percentage sample variability were as follows: Factor 1. Vertical facial characteristics Factor 2. Anteroposterior aspects of facial morphology Factor 3. Midfacial and dental protrusion Factor 4. Relationship of the mandible and dentition to the profile Factor 5. Horizontal base-line relationships (internal or deep) Factor 6. Maxillary incisor relationships These principal components and the variables contained within them were shown to have sex and age interactions. A longitudinal study of the principal component changes with age was then undertaken. Demonstrable age changes were verified for Factors 1, 2, and 3, and Factors 1 and 3 were observed to show patterns of change which were statistically different from each other and the remaining principal components. An orthodontically treated sample of patients was also assessed for factor changes. Factors 1 and 2 were found to show statistically reliable changes resulting from treatment and/or growth. The remaining four factors showed no statistically supportable alteration. The data-reduction method involving a principal-component analysis would seem to have potential research and clinical applications.

Adolescent↗

PubMed1992

Principal components and multidimensional scaling of auditory and visual event-related potential topography.

Principal components analysis and metric multidimensional scaling were used to assess auditory and visual event-related potential topography in healthy late-middle-aged and elderly adults (n = 20). Binaurally elicited auditory evoked potentials and full-field checkerboard pattern reversal visual event-related potentials were recorded from 28 scalp sites. The zero-lag, cross-correlations of all waveforms for 300 msec post-stimulus epochs were obtained and separate analyses of the auditory and visual data were performed. Ultimately, three of the four dimensions identified in the principal components and multidimensional scaling solutions were similar and represented electrode site differences in (1) the anterior-posterior plane; (2) laterality; and, (3) the proximal-distal relation to midline. The remaining multidimensional scaling axis appeared to reflect effects specific to the modality of stimulation. Under auditory stimulation, the temporal and central-parietal sites were distinct from other scalp regions, whereas under visual stimulation, the occipital and frontal sites were distinctive. Although the results of the principal component analyses were conceptually similar to the multidimensional scaling outcomes, there were consistent differences between them. The findings provide empirical support for the validity of these multivariate methods in topographic analysis.

Acoustic Stimulation↗

PubMed1990

[Multivariate analysis for the study of craniofacial structure. Selection of parameters on using the principal component analysis].

The present study was undertaken to discuss the effects of parameters on using the principal component analysis for the evaluation of the craniofacial structures. Materials consisted of lateral roentgenocephalograms of 100 adult Japanese females. They were divided into three groups by ANB angle. Linear and angular measurements were selected as parameters to apply the principal component analysis, and scattergrams made by the first and second principal component were compared. The results of the analysis were varied by the parameters. Especially there was a great difference between the real size and the value corrected by isometric method on scattergrams made by the first and second components. Results indicated the importance of using appropriate parameters for the research purpose.

Adult↗

PubMed1992

Observations on a principal components analysis of head-related transfer functions.

A recent principal components analysis (Kistler and Wightman, 1992) has shown that the transfer functions of the human external ear, for a wide range of source locations, can be expressed as weighted sums of a small number of basis vectors. Directional transfer functions obtained in this laboratory, using substantially different measurement techniques, yielded principal component basis vectors that are remarkably similar to those reported by Kistler and Wightman. When this subject population was divided in half according to the overall physical sizes of subjects, basis vectors computed for the subpopulation of smaller subjects were shifted systematically to higher frequencies relative to those computed for the subpopulation of larger subjects.

Ear, External↗

PubMed1978

Principal component analysis of neural population response of knee joint proprioceptors in cat.

(1) A means of describing the response of neural populations based on principal component analysis is presented. The analysis produces response descriptions that indicate whether two states are distinguishable and suggest how to best distinguish between states. (2) Analysis of slowly adapting joint receptor data from the cat knee joint indicates that the joint receptors are capable of signalling limb position in the range from 150 degrees to 180 degrees of extension during an extension movement. They also provide information which indicates whether the tibia is twisted inward or outward in this range of angles. (3) The first principal component in the response to a constant velocity extension of 8 simultaneously active units described 86% of the total mean square discharge displayed by all 8 units. The first principal component is qualitatively similar to the responses observed in slowly adapting thalamic joint units.

Animals↗

PubMed1990

Use of principal components analysis to develop a composite score as a primary outcome variable in a clinical trial. The VA Cooperative Study Group on Cochlear Implantation.

This article describes the use of principal components analysis to derive a composite score from a battery of 24 audiologic tests. The composite score is being used as the primary outcome variable in a clinical trial comparing the efficacy of three cochlear implant devices for people with bilateral, profound hearing loss. The first principal component from the within-class pooled variance-covariance matrix over four time periods was chosen to establish the coefficients for the composite score. This component accounted for 61% of the total variance of the 24 audiologic tests. The first principal component had its largest coefficients associated with the most difficult audiologic tests. The mean composite score of all patients improved over time; some patients showed dramatic improvement. The changes in the composite score over time were also closely related to subjective impressions of implant performance by the patient, audiologist, and otolaryngologist.

Analysis of Variance↗

PubMed1991

Principal components analysis of regional bone density in black and white women: relationship to body size and composition.

Black and white women in the United States differ with respect to bone mass and the risk of developing osteoporosis. It has been suggested that greater body size among U.S. blacks may contribute to greater bone density in this group. It is not known whether the fat or lean component contributes more to this relationship. Bone density was measured at seven sites in 161 normal black and white women using single and dual photon absorptiometry. The first principal component accounted for 73% of the variance in the sample and constitutes an index of skeletal mass. The second principal component added another 10% and contrasts the axial and appendicular sites. Both the regional bone densities and the first principal component showed significantly greater bone densities for blacks; adjustment for body size reduced bone mass differences by approximately 50%. Body composition analysis done on a subset of these women indicated that the fat component of body mass may be the more important factor in its effect on bone mass.

Absorptiometry, Photon↗

PubMed1990

Application of principal component analysis for characterizing convergence patterns of inputs in interneurones of the cat forelimb segments.

We attempted to quantitatively describe a variety of convergence patterns of inputs from peripheral nerves and descending tracts (13 sources) onto interneurones of the cat forelimb segments (C6-C8). To this end we applied principal component analysis using the latency of firing as the parameter of each input. The first 3 principal components thus obtained explained 65% of the total variance of convergence patterns and characterized the input pattern of each cell. The first principal component correlated mainly with inputs from pads and the median nerve, the second with the cortico- and rubro-spinal tracts and the third with the superficial radial nerve.

Animals↗

PubMed1992

Principal component analysis and exploratory factor analysis.

In this paper we compare and contrast the objectives of principal component analysis and exploratory factor analysis. This is done through consideration of nine examples. Basic theory is presented in appendices. As well as covering the standard material, we also describe a number of recent developments. As an alternative to factor analysis, it is pointed out that in some cases it may be useful to rotate certain principal components if and when that is appropriate.

Animals↗

PubMed1991

Principal component analysis of various respiratory function tests: the relationship between factor score and severity of pulmonary circulatory disorder in chronic obstructive pulmonary disease.

The relationship between pulmonary haemodynamics and values of various respiratory function tests was studied in patients with mild chronic obstructive pulmonary disease (COPD) and the following results were obtained. (1) The value of mean pulmonary artery pressure (mPAP) at rest in COPD patients was slightly elevated to 19.4 mmHg on average compared with our control value of less than 18 mmHg. (2) Analysis of the data of 11 routine respiratory function tests in 88 COPD patients extracted two principal components: an index of the expiratory function and an index for overinflation of the lung. (3) In individual patients, mPAP expressed the severity of pulmonary circulatory disorder roughly inverse to the factor score of the first principal component (index of expiratory function) but not to that of the second principal component (overinflation of the lung). (4) Discriminant analysis was performed in all 88 COPD patients according to data from the 11 respiratory function tests. The probability of mPAP being above or below 18 mmHg was 18.2%. (5) The relationship between the predicted EPOI value and the factor score was similar to that between mPAP and the factor score. EPOI (exercise pulmonary artery pressure-oxygen consumption index) was calculated with the following equation: EPOI = (mPAPex#-mPAPrest)/[VO2ex-VO2rest)/BSA##). On the other hand, EPOIpred was calculated with the prediction equation obtained from multiple linear regression (dependent variable; EPOI, independent variable; respiratory function).

Adult↗