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An important and unresolved problem in the assessment of perceptual and cognitive deficits in neurological patients is how to choose from the many existing behavioral tests, a subset that is sufficient for an appropriate diagnosis. This problem has to be dealt with in clinical trials, as well as in rehabilitation settings and often even at bedside in acute care hospitals. The need for efficient, cost...
Iterative Closest Point (ICP) is a widely exploited method for point registration that is based on binary point-to-point assignments, whereas the Expectation Conditional Maximization (ECM) algorithm tries to solve the problem of point registration within the framework of maximum likelihood with point-to-cluster matching. In this paper, by fulfilling the implementation of both algorithms as well as...
Chemical descriptors are a way to define information concerning the physical, chemical and biological properties of a chemical compound. Machine learning methods such as the Artificial Neural Network (ANN) can be used to learn and predict such compounds by training on the compounds chemical descriptors. The motivation of our work is to predict odorant molecules for the development of an artificial...
ISAF (icosahedral symmetry-adapted functions) algorithm is the new high-resolution algorithm of icosahedral molecules. But its running speed is very slow because of the time-consuming operations of mapping sampling points into 3D space. In this paper, a fast mapping method is proposed to increase the running speed of this stage. First of all, the angle corresponding to one pixel arc in the maximum...
Motion and noise artifacts (MNA) have been a serious obstacle in realizing the potential of Photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a statistical approach based on the computation of kurtosis and Shannon Entropy (SE) for the accurate detection of MNA in PPG data. The MNA detection algorithm was verified on multi-site PPG data collected from both laboratory...
The automated tracing of the carotid layers on ultrasound images is complicated by noise, different morphology and pathology of the carotid artery. In this study we benchmarked four methods for feature selection on a set of variables extracted from ultrasound carotid images. The main goal was to select those parameters containing the highest amount of information useful to classify the pixels in the...
The detection of swallowing events by acoustic means represents an important tool to assess and diagnose swallowing disorders as well as to objectively monitor ingestive behavior of individuals. Acoustic sensors used to register swallowing sounds may also capture sound artifacts arising from intrinsic speech and external noise affecting the detection. In this paper we tested if subsonic frequencies...
This paper provides a comparison of several blind source separation (BSS) techniques as they are applied to EEG signals. Specifically, this work focuses on the P300 speller paradigm and assesses the classification accuracies for the identification of P300 trials. Previous work has shown that BSS methods such as independent component analysis (ICA) are useful in extracting the P300 source information...
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