Biomedical Signal Processing: From a Conceptual Framework to Clinical Applications [Scanning the Issue]

This special issue covers relevant contemporary challenges in the field of biomedical signal processing and possibilities for future technological development.

[1]  Laura Astolfi,et al.  Time-Variant Modeling of Brain Processes , 2016, Proceedings of the IEEE.

[2]  Shamim Nemati,et al.  Machine Learning and Decision Support in Critical Care , 2016, Proceedings of the IEEE.

[3]  Aneta Stefanovska,et al.  Reconstructing Time-Dependent Dynamics , 2016, Proceedings of the IEEE.

[4]  Wei Wu,et al.  Multimodal BCIs: Target Detection, Multidimensional Control, and Awareness Evaluation in Patients With Disorder of Consciousness , 2016, Proceedings of the IEEE.

[5]  Kenji Sunagawa,et al.  Closed-Loop Neuromodulation Technology for Baroreflex Blood Pressure Control , 2016, Proceedings of the IEEE.

[6]  Toru Nakamura,et al.  Multiscale Analysis of Intensive Longitudinal Biomedical Signals and Its Clinical Applications , 2016, Proceedings of the IEEE.

[7]  Pablo Laguna,et al.  Techniques for Ventricular Repolarization Instability Assessment From the ECG , 2016, Proceedings of the IEEE.

[8]  David J. Warren,et al.  Recording and Decoding for Neural Prostheses , 2016, Proceedings of the IEEE.

[9]  Dario Farina,et al.  Characterization of Human Motor Units From Surface EMG Decomposition , 2016, Proceedings of the IEEE.

[10]  Luca Faes,et al.  Wiener–Granger Causality in Network Physiology With Applications to Cardiovascular Control and Neuroscience , 2016, Proceedings of the IEEE.

[11]  Andrzej Cichocki,et al.  Linked Component Analysis From Matrices to High-Order Tensors: Applications to Biomedical Data , 2015, Proceedings of the IEEE.

[12]  Mathias Baumert,et al.  Quantitative-Electrogram-Based Methods for Guiding Catheter Ablation in Atrial Fibrillation , 2016, Proceedings of the IEEE.