Search results for "Algorithms"

showing 10 items of 1716 documents

The RFID technology for neurosciences: feasibility of limbs' monitoring in sleep diseases.

2009

This contribution investigates the feasibility of the passive UHF RF identification technology for the wireless monitoring of human body movements in some common sleep disorders by means of passive tags equipped with inertial switches. Electromagnetic and mechanical models as well as preliminary experimentations are introduced to analyze all the significant issues concerning the required power, the tag antenna design, the read distance, and the expected biosignals collected by the interrogation device.

Computer scienceRemote patient monitoringRadio WavesPolysomnographytag antennaRFID sensor Human health monitoringAccelerometerRF identification (RFID)MotionRestless Legs SyndromemedicineWirelessHumansTelemetryaccelerometer; RF identification (RFID); sensor network; sleep disorder; tag antennaElectrical and Electronic Engineeringsensor networksleep disorderSleep disorderbusiness.industrySettore ING-INF/02 - Campi ElettromagneticiExtremitiesGeneral MedicineModels Theoreticalmedicine.diseaseComputer Science ApplicationsNocturnal Myoclonus SyndromeaccelerometerRadio frequencySleep (system call)TelecommunicationsbusinessWireless sensor networkComputer hardwareAlgorithmsBiotechnologyIEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society
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Atrial activity extraction for atrial fibrillation analysis using blind source separation.

2004

This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA …

Computer scienceSpeech recognitionHeart VentriclesBiomedical EngineeringSignalBlind signal separationSensitivity and SpecificityElectrocardiographyRobustness (computer science)Heart Conduction SystemAtrial FibrillationmedicineHumansDiagnosis Computer-AssistedHeart AtriaPrincipal Component Analysismedicine.diagnostic_testBody Surface Potential MappingContrast (statistics)Reproducibility of ResultsAtrial fibrillationmedicine.diseaseIndependent component analysisKurtosisElectrocardiographyAlgorithmsIEEE transactions on bio-medical engineering
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Testing for goodness rather than lack of fit of continuous probability distributions.

2021

The vast majority of testing procedures presented in the literature as goodness-of-fit tests fail to accomplish what the term is promising. Actually, a significant result of such a test indicates that the true distribution underlying the data differs substantially from the assumed model, whereas the true objective is usually to establish that the model fits the data sufficiently well. Meeting that objective requires to carry out a testing procedure for a problem in which the statement that the deviations between model and true distribution are small, plays the role of the alternative hypothesis. Testing procedures of this kind, for which the term tests for equivalence has been coined in sta…

Computer scienceStatement (logic)Alternative hypothesisScienceTest StatisticsResearch and Analysis MethodsStatistical InferenceMathematical and Statistical TechniquesStatistical inferenceEconometricsHumansLack-of-fit sum of squaresStatistical MethodsEquivalence (measure theory)Statistical hypothesis testingStatistical DataProbabilityMultidisciplinaryModels StatisticalApplied MathematicsSimulation and ModelingStatisticsQRProbability TheoryProbability DistributionTerm (time)Monte Carlo methodStatistical TheoriesPhysical SciencesProbability distributionMedicineMathematicsAlgorithmsResearch ArticleStatistical DistributionsPLoS ONE
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Toward morphological thoracic EIT: major signal sources correspond to respective organ locations in CT.

2012

Lung and cardiovascular monitoring applications of electrical impedance tomography (EIT) require localization of relevant functional structures or organs of interest within the reconstructed images. We describe an algorithm for automatic detection of heart and lung regions in a time series of EIT images. Using EIT reconstruction based on anatomical models, candidate regions are identified in the frequency domain and image-based classification techniques applied. The algorithm was validated on a set of simultaneously recorded EIT and CT data in pigs. In all cases, identified regions in EIT images corresponded to those manually segmented in the matched CT image. Results demonstrate the abilit…

Computer scienceSwine0206 medical engineeringBiomedical Engineering02 engineering and technologyIterative reconstructionSignal030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineElectric ImpedanceImage Processing Computer-AssistedAnimalsComputer visionElectrical impedance tomographyLungTomographyContextual image classificationbusiness.industryReproducibility of ResultsHeartSignal Processing Computer-AssistedImage segmentation020601 biomedical engineeringFrequency domainRadiography ThoracicArtificial intelligencebusinessTomography X-Ray ComputedAlgorithmsIEEE transactions on bio-medical engineering
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Automatic segmentation of the spine by means of a probabilistic atlas with a special focus on ribs suppression

2017

[EN] Purpose: The development of automatic and reliable algorithms for the detection and segmentation of the vertebrae are of great importance prior to any diagnostic task. However, an important problem found to accurately segment the vertebrae is the presence of the ribs in the thoracic region. To overcome this problem, a probabilistic atlas of the spine has been developed dealing with the proximity of other structures, with a special focus on ribs suppression. Methods: The data sets used consist of Computed Tomography images corresponding to 21 patients suffering from spinal metastases. Two methods have been combined to obtain the final result: firstly, an initial segmentation is performe…

Computer scienceVertebral segmentationComputed tomographyRibscomputer.software_genre030218 nuclear medicine & medical imagingTECNOLOGIA ELECTRONICA03 medical and health sciences0302 clinical medicineVoxelAtlas (anatomy)medicineHumansSegmentationProbabilistic atlasComputed tomographyProbabilityRib cagemedicine.diagnostic_testbusiness.industryPattern recognitionGeneral MedicineProbabilistic atlasSpineHausdorff distancemedicine.anatomical_structureRibs suppressionArtificial intelligencebusinessTomography X-Ray Computedcomputer030217 neurology & neurosurgeryAlgorithms
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Predicting perceived visual complexity of abstract patterns using computational measures: The influence of mirror symmetry on complexity perception

2017

Visual complexity is relevant for many areas ranging from improving usability of technical displays or websites up to understanding aesthetic experiences. Therefore, many attempts have been made to relate objective properties of images to perceived complexity in artworks and other images. It has been argued that visual complexity is a multidimensional construct mainly consisting of two dimensions: A quantitative dimension that increases complexity through number of elements, and a structural dimension representing order negatively related to complexity. The objective of this work is to study human perception of visual complexity utilizing two large independent sets of abstract patterns. A w…

Computer scienceVisionSocial Scienceslcsh:MedicineSensory perceptioncomputer.software_genreSymmetry0302 clinical medicineMathematical and Statistical TechniquesAttitudes (psychology)Psychologylcsh:Sciencemedia_commonMultidisciplinaryApplied MathematicsSimulation and Modeling05 social sciencesPattern Recognition VisualEllipsesPhysical SciencesVisual PerceptionMirror symmetryStatistics (Mathematics)AlgorithmsResearch ArticleComputer and Information Sciencesmedia_common.quotation_subjectGeometryMachine learning algorithmsMachine learningEllipseResearch and Analysis Methods050105 experimental psychologyVisual complexity03 medical and health sciencesArtificial IntelligencePerceptionMachine learningHumans0501 psychology and cognitive sciencesStatistical Methodsbusiness.industrylcsh:RBiology and Life SciencesComputational BiologyUsabilitylcsh:QArtificial intelligencebusinesscomputer030217 neurology & neurosurgeryMathematicsNeuroscienceForecasting
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Feature selection with Ant Colony Optimization and its applications for pattern recognition in space imagery

2016

This paper presents a feature selection (FS) algorithm using Ant Colony Optimization (ACO). It is inspired by the particular behavior of real ants, namely by the fact that they are capable of finding the shortest path between a food source and the nest. There are considered two ACO-FS model applications for pattern recognition in remote sensing imagery: ACO Band Selection (ACO-BS) and ACO Training Label Purification (ACO-TLP). The ACO-BS reduces dimensionality of an input multispectral image data by selecting the “best” subset of bands to accomplish the classification task. The ACO-TLP selects the most informative training samples from a given set of labeled vectors in order to optimize the…

Computer sciencebusiness.industryAnt colony optimization algorithmsMultispectral imageFeature selectionPattern recognition02 engineering and technologyStatistical classification020204 information systemsPrincipal component analysisShortest path problem0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)Curse of dimensionality2016 International Conference on Communications (COMM)
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An evolutionary restricted neighborhood search clustering approach for PPI networks

2014

Protein-protein interaction networks have been broadly studied in the last few years, in order to understand the behavior of proteins inside the cell. Proteins interacting with each other often share common biological functions or they participate in the same biological process. Thus, discovering protein complexes made of a group of proteins strictly related can be useful to predict protein functions. Clustering techniques have been widely employed to detect significant biological complexes. In this paper, we integrate one of the most popular network clustering techniques, namely the Restricted Neighborhood Search Clustering (RNSC), with evolutionary computation. The two cost functions intr…

Computer sciencebusiness.industryCognitive NeuroscienceNeighborhood searchComputational biologyPPI networks clusteringGenetic algorithmsMachine learningcomputer.software_genreBudding yeastEvolutionary computationComputer Science ApplicationsOrder (biology)Artificial IntelligenceGenetic algorithmArtificial intelligenceEvolutionary approachesbusinessCluster analysiscomputerProtein-protein interaction networks clustering
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Fingerprint Registration Using Specialized Genetic Algorithms

2005

One of the most common problem to realize a robust matching algorithm in an Automated Fingerprint Identification System (AFIS) is the images registration. In this paper a fingerprints registration method based on a specialized genetic algorithm (GA) is proposed. A global transformation between two fingerprint images is performed using genetic data evolutions based on specialized mutation rate and solution refining. An AFIS including the above method has been developed and tested on two different fingerprint databases: NIST 4 ink-on-paper and self optical scanned. The obtained experimental results show that the proposed approach is comparable with literature systems working on medium quality…

Computer sciencebusiness.industryGenetic dataImage registrationPattern recognitionBiometricsfingerprint orientationFingerprintGenetic algorithmNISTGlobal transformationArtificial intelligencebusinessAutomated fingerprint identificationAlgorithmsBlossom algorithmEUROCON 2005 - The International Conference on "Computer as a Tool"
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A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …

2013

Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…

Computer sciencecomputer.software_genreBiochemistrysymbols.namesakeDiscriminative modelStructural BiologyCluster AnalysisRelevance (information retrieval)Cluster analysisMolecular BiologyOligonucleotide Array Sequence AnalysisClustering discriminative ability of a distance function external validation indicesSettore INF/01 - InformaticaResearchApplied MathematicsMutual informationPearson product-moment correlation coefficientComputer Science ApplicationsHierarchical clusteringEuclidean distanceRange (mathematics)Metric (mathematics)symbolsData miningTranscriptomecomputerAlgorithmsBMC Bioinformatics
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