Singular spectrum analysis of biomedical signals

Content: IntroductionPhysiological, Biological, and Biochemical ProcessesMajor Topics in Physiological and Biological Signal ProcessingBiological Signals and SystemsDecomposition of Signals and Extraction of the Sources of InterestQuantification of Evolution and Prediction of Future TrendsData and Trends
Rhythmic, Noisy, or Chaotic?Generation of Surrogate DataConcluding RemarksBibliographySingular Spectrum AnalysisIntroductionUnivariate SSAMultivariate SSAOptimal Values of L and r in MSSAExtensions of SSABibliographySSA Application to Sleep ScoringIntroductionStages of SleepThe Influence of Circadian RhythmsSleep DeprivationPsychological EffectsDetection and Monitoring of Brain Abnormalities during Sleep by EEG AnalysisSSA for Sleep ScoringConcluding RemarksBibliographyAdaptive SSA and Its Application to Biomedical Source SeparationIntroductionAdaptive Line EnhancementSSA-Based ALE and Its Application to Separation of ECG from Recorded EMGIncorporating Sparsity ConstraintComparing Basic ALE and SSA-Based ALEApplication of Sparsity ConstraintAn Adaptive SSA-Based System for Classification of Narrow Frequency Band SignalsConcluding RemarksBibliographyApplications to Biometric Identification and RecognitionIntroductionIntroduction to Gait RecognitionModel Free MethodsCombination of Gait with Other BiometricsGait AssessmentGait Analysis for Clinical RehabilitationAssessing Limb Function for Stroke PatientsSSA Application for Recognition and Characterisation of StrokeUse of Multivariate SSA for Joint Analysis of 3D TrajectoriesGait Analysis Using Ear-Worn Sensor DataConcluding RemarksBibliographyComplex-Valued SSA for Detection of Event Related Potentials from EEGBrief LiteratureComplex-Valued Matrix Variables Z and Z*Augmented Complex StatisticsAnalytic SignalsComplex-Valued DerivativesGeneralized Complex-Valued Matrix DerivativesAugmented Complex-Valued Matrix VariablesSingular Spectrum Analysis of P300 for ClassificationExperimental ResultsSome Concluding RemarksExtension to Hypercomplex DomainConclusionBibliographySSA Change Point Detection and Eye Fundus Image AnalysisOcular Fundus AbnormalitiesOcular Fundus ImagesDiabetic Retinopathy ImagesAnalysis of Fundus Images and Detection of Retinopathy FeaturesConcluding RemarksBibliographyPrediction of Medical and Physiological TrendsConventional Approaches for Time Series PredictionSSA Application for PredictionHow SSA Is Used in PredictionApplication of SSA-Based Prediction to Real Biomedical TrendsConcluding RemarksBibliographySSA Application on Genetic StudiesGenomic Signal ProcessingApplicationSingular Spectrum Analysis and Colonial TheorySignal Extraction and FilteringSSA Based on Minimum VarianceSSA Combined with AR ModelApplication of Two Dimensional SSAEigenvalues Identification in SSA Signal ExtractionConcluding RemarksBibliographyConclusions and Suggestions for Future Research