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Luca Faes

Showing results (91-100 of 189) with videos related to

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IEEE Transactions on Bio-Medical Engineering|December 6, 2023
A Method to Assess Granger Causality, Isolation and Autonomy in the Time and Frequency Domains: Theory and Application to Cerebrovascular VariabilityLaura Sparacino, Yuri Antonacci, Chiara Bara, et al.
Medical & Biological Engineering & Computing|April 24, 2016
Causal analysis of short-term cardiovascular variability: state-dependent contribution of feedback and feedforward mechanismsMichal Javorka, Barbora Czippelova, Zuzana Turianikova, et al.
Journal of Neural Engineering|October 21, 2025
A method for the time-frequency analysis of high-order interactions in non-stationary physiological networksYuri Antonacci, Chiara Bará, Laura Sparacino, et al.
Physiological Measurement|June 19, 2026
Dissecting the integrated information of cardiovascular and cardiorespiratory systems at rest and during physiological stressIrene Franzone, Roberta Saputo, Yuri Antonacci, et al.
Autonomic Neuroscience : Basic & Clinical|April 17, 2013
Measuring postural-related changes of spontaneous baroreflex sensitivity after repeated long-duration diving: frequency domain approachesLuca Faes, Michela Masè, Giandomenico Nollo, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 25, 2017
Information transfer and information modification to identify the structure of cardiovascular and cardiorespiratory networksLuca Faes, Giandomenico Nollo, Jana Krohova, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
Statistical Approaches to Characterize Functional Connectivity in Brain and Physiologic Networks on a Single-Subject BasisLaura Sparacino, Martina Valentino, Yuri Antonacci, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
Investigating Dynamic High-Order Interactions in Physiological Networks through Predictive Information DecompositionLuca Faes, Gorana Mijatovic, Laura Sparacino, et al.
Frontiers in Network Physiology|April 19, 2024
A method to assess linear self-predictability of physiologic processes in the frequency domain: application to beat-to-beat variability of arterial complianceLaura Sparacino, Yuri Antonacci, Chiara Barà, et al.
Physical Review. E|April 18, 2025
Assessing high-order effects in feature importance via predictability decompositionMarlis Ontivero-Ortega, Luca Faes, Jesus M Cortes, et al.
Pageof 19

Showing results (91-100 of 189) with videos related to

Sort By:
Pageof 19
IEEE Transactions on Bio-Medical Engineering|December 6, 2023
A Method to Assess Granger Causality, Isolation and Autonomy in the Time and Frequency Domains: Theory and Application to Cerebrovascular VariabilityLaura Sparacino, Yuri Antonacci, Chiara Bara, et al.
Medical & Biological Engineering & Computing|April 24, 2016
Causal analysis of short-term cardiovascular variability: state-dependent contribution of feedback and feedforward mechanismsMichal Javorka, Barbora Czippelova, Zuzana Turianikova, et al.
Journal of Neural Engineering|October 21, 2025
A method for the time-frequency analysis of high-order interactions in non-stationary physiological networksYuri Antonacci, Chiara Bará, Laura Sparacino, et al.
Physiological Measurement|June 19, 2026
Dissecting the integrated information of cardiovascular and cardiorespiratory systems at rest and during physiological stressIrene Franzone, Roberta Saputo, Yuri Antonacci, et al.
Autonomic Neuroscience : Basic & Clinical|April 17, 2013
Measuring postural-related changes of spontaneous baroreflex sensitivity after repeated long-duration diving: frequency domain approachesLuca Faes, Michela Masè, Giandomenico Nollo, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 25, 2017
Information transfer and information modification to identify the structure of cardiovascular and cardiorespiratory networksLuca Faes, Giandomenico Nollo, Jana Krohova, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
Statistical Approaches to Characterize Functional Connectivity in Brain and Physiologic Networks on a Single-Subject BasisLaura Sparacino, Martina Valentino, Yuri Antonacci, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 12, 2023
Investigating Dynamic High-Order Interactions in Physiological Networks through Predictive Information DecompositionLuca Faes, Gorana Mijatovic, Laura Sparacino, et al.
Frontiers in Network Physiology|April 19, 2024
A method to assess linear self-predictability of physiologic processes in the frequency domain: application to beat-to-beat variability of arterial complianceLaura Sparacino, Yuri Antonacci, Chiara Barà, et al.
Physical Review. E|April 18, 2025
Assessing high-order effects in feature importance via predictability decompositionMarlis Ontivero-Ortega, Luca Faes, Jesus M Cortes, et al.
Pageof 19