Selecting differentially expressed genes with respect to some phenotype of interest is a difficult task, especially in the presence of confounding factors. We propose to use a spatiotemporal independent component analysis to model those factors, and to combine information from different spatiotemporal parameter values to improve the set of selected genes. We show on real datasets that the propo...

Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern of activation, which leads to the instantaneous mixing model. To allow modeling patterns of spatiotemporal dynamics, in particular, the flow of oxygenated blood, we have developed a convolutive ICA...

Abstract— After summarizing typical approaches for solving independent component analysis (ICA) problems, advances on the ICA studies that consider hybrid sources of both subGaussians and superGaussians and the ICA extensions that consider noise and temporal dependence among observations have been overviewed from the perspective of Bayesian Ying-Yang independence learning. Not only new insights...

PURPOSE In light of the increasing elderly population and the growing demand for home care, the potential of robot support is given increasing attention. In this paper, an inventory of activities was made that threaten independent living of elderly when becoming problematic. Results will guide the further development of an existing service robot, the Care-O-bot®. METHOD A systematic literatur...

In this paper we study the dependencies of features found by independent component analysis (ICA) in image data by examining how the activation of one feature changes certain statistics of the data. We look at how the PCA components are affected when we know a certain ICA feature is highly active, and also study the ICA components in this situation. This can be thought of as a simple form of tw...

A new instrument, the Satisfaction with Performance Scaled Questionnaire (SPSQ), was developed to measure individuals' satisfaction with their performance of independent living skills. The SPSQ was designed to be used for clinical assessment and research with community-based persons with disabilities. Split-half reliability coefficients were .97 and .93 for the two scales, Home Management and S...

Data sets acquired from functional magnetic resonance imaging (fMRI) contain both spatial and temporal structures. In order to blindly extract underlying activities, the common approach however only uses either spatial or temporal independence. More convincing results can be achieved by requiring the transformed data to be as independent as possible in both domains. First introduced by Stone, s...

Regional myocardial motion analysis is used in clinical routine to inspect cardiac contraction in myocardial diseases such as infarction or hypertrophy. Physicians/radiologists can recognize abnormal cardiac motion because they have knowledge about normal heart contraction. This paper explores the potential of Independent Component Analysis (ICA) to extract local myocardial contractility patter...

The analysis and characterization of atrial fibrillation requires the previous extraction of the atrial activity from the electrocardiogram, where the independent atrial and ventricular activities are combined in addition to noise. An independent component analysis method is proposed where additional knowledge about the time and statistical structure of the sources is incorporated. Finally, a c...

In this paper we examine how the activation of one independent component analysis (ICA) feature changes first and second order statistics of other independent components in image patches. Essential for observing these dependencies is normalizing patch statistics, and selecting patches according to activation. We then estimate a model predicting the conditional statistics of a component using th...