1;Preface;6 2;Organization;7 3;Table of Contents;12 4;Biosignal Processing;12 4.1;Quantitative Analysis of Two-Dimensional Catch-Up Saccades Executed to the Target Jumps in the Time-Continuous Trajectory;30 4.1.1;INTRODUCTION;30 4.1.2;AIM AND TASKS OF THE WORK;31 4.1.3;METHOD;31 4.1.4;EXPERIMENTAL RESULTS;31 4.1.5;CONCLUSIONS;33 4.1.6;REFERENCES;33 4.2;Spike Sorting based on Dominant-Sets clustering;34 4.2.1;INTRODUCTION;34 4.2.2;METHOD;35 4.2.3;RESULTS;36 4.2.4;CONCLUSIONS;37 4.2.5;REFERENCES;37 4.3;Differentiation of human bone marrow stromal cells onto gelatin cryogel scaffolds;38 4.3.1;INTRODUCTION;38 4.3.2;MATERIALS ANDMETHODS;38 4.3.3;RESULTS;40 4.3.4;DISCUSSION;40 4.3.5;REFERENCES;41 4.4;Simples Coherence vs. Multiple Coherence: A Somatosensory Evoked Response Detection Investigation;42 4.4.1;INTRODUCTION;42 4.4.2;MATERIAL AND METHODS;42 4.4.3;RESULTS;43 4.4.4;DISCUSSION AND CONCLUSIONS;45 4.4.5;REFERENCES;45 4.5;Measure of Similarity of ECG Cycles;46 4.5.1;INTRODUCTION;46 4.5.2;MATERILAS AND METHODS;46 4.5.3;DISCUSSION;48 4.5.4;CONCLUSION;49 4.5.5;REFERENCES;49 4.6;Wavelet phase synchronization between EHGs at different uterine sites: comparison of pregnancy and labor contractions;50 4.6.1;INTRODUCTION;50 4.6.2;MATERIALS AND METHODS;50 4.6.3;DISCUSSION;53 4.6.4;CONCLUSION;53 4.6.5;REFERENCES;53 4.7;Dynamic Generation of Physiological Model Systems;54 4.7.1;INTRODUCTION;54 4.7.2;METHODS;54 4.7.3;RESULTS;56 4.7.4;CONCLUSIONS;57 4.7.5;REFERENCES;57 4.8;Random Forest-Based Classification of Heart Rate Variability Signals by Using Combinations of Linear and Nonlinear Features;58 4.8.1;INTRODUCTION;58 4.8.2;METHODS AND MATERIAL;58 4.8.3;RESULTS;60 4.8.4;DISCUSSION;61 4.8.5;CONCLUSION;61 4.8.6;REFERENCES;61 4.9;Validation of MRS metabolic markers in the classification of brain gliomas and their correlation to energy metabolism;62 4.9.1;INTRODUCTION;62 4.9.2;MATERIALS AND METHODS;63 4.9.3;RESULTS;63 4.9.4;DISCUSSION;64 4.9.5;CONCLUSIONS;65 4.9.6;REFERENCES;65 4.10;Event-Related Synchronization/Desynchronization for Evaluating Cortical Response Detection Induced by Dynamic Visual Stimuli;66 4.10.1;INTRODUCTION;66 4.10.2;MATERIALS AND METHODS;66 4.10.3;RESULTS;68 4.10.4;DISCUSSION AND CONCLUSION;69 4.10.5;REFERENCES;69 4.11;Investigating the EEG Alpha Band during Kinesthetic and Visual Motor Imagery of the Spike Volleyball Movement;70 4.11.1;INTRODUCTION;70 4.11.2;MATERIAL AND MEHOTDS;70 4.11.3;RESULTS;72 4.11.4;DISCUSSION;72 4.11.5;CONCLUSIONS;73 4.11.6;REFERENCES;73 4.12;Principal Components Clustering through a Variance-Defined Metric;74 4.12.1;INTRODUCTION;74 4.12.2;BACKGROUND;74 4.12.3;MATERIALS AND METHODS;75 4.12.4;RESULTS;76 4.12.5;DISCUSSION;77 4.12.6;REFERENCES;77 4.13;A Kurtosis-Based Automatic System Using Naïve Bayesian Classifier to Identify ICA Components Contaminated by EOG or ECG Artifacts;78 4.13.1;INTRODUCTION;78 4.13.2;MATERIALS AND METHODS;79 4.13.3;RESULTS;80 4.13.4;CONCLUSSIONS AND DISCUSSION;81 4.13.5;REFERENCES;81 4.14;Correlation between Fractal Behavior of HRV and Neurohormonal and Functional Indexes in Chronic Heart Failure;82 4.14.1;INTRODUCTION;82 4.14.2;MATERIALS AND METHODS;83 4.14.3;RESULTS;84 4.14.4;CONCLUSIONS;84 4.14.5;REFERENCES;85 4.15;On the Selection of Time Interval and Frequency Range of EEG Signal Preprocessing for P300 Brain-Computer Interfacing;86 4.15.1;INTRODUCTION;86 4.15.2;METHODS;86 4.15.3;RESULTS;88 4.15.4;CONCLUSION;89 4.15.5;REFERENCES;89 4.16;Development of a Simple and Cheap Device for Movement Analysis;90 4.16.1;INTRODUCTION;90 4.16.2;SYSTEM DESCRIPTION;91 4.16.3;RESULTS;92 4.16.4;DISCUSSION;93 4.16.5;REFERENCES;93 4.17;Signal Peptide Prediction in Single Transmembrane Proteins Using the Continuous Wavelet Transform;94 4.17.1;INTRODUCTION;94 4.17.2;MATERIALS AND METHODS;94 4.17.3;RESULTS;96 4.17.4;DISCUSSION;96 4.17.5;CONCLUSIONS;97 4.17.6;REFERENCES;97 4.18;Comparison of AM-FM Features with Standard Features for the Classification of Surface Electromyographic Signals;98 4.