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Sensors 2016, 16(11), 1828; doi:10.3390/s16111828

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results

1
Institute of Life Science, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
2
Research Center “E. Piaggio”, University of Pisa, 56122 Pisa, Italy
3
Fondazione Toscana Gabriele Monasterio, National Research Council, 56124 Pisa, Italy
4
Dipartimento di Ingegneria dell’Informazione, University of Pisa, 56124 Pisa, Italy
*
Author to whom correspondence should be addressed.
Academic Editors: Steffen Leonhardt and Daniel Teichmann
Received: 25 August 2016 / Revised: 21 October 2016 / Accepted: 27 October 2016 / Published: 31 October 2016
(This article belongs to the Special Issue Noninvasive Biomedical Sensors)
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Abstract

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings. View Full-Text
Keywords: EEG; missing data segments; cross correlation function; control of breathing EEG; missing data segments; cross correlation function; control of breathing
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MDPI and ACS Style

Morelli, M.S.; Giannoni, A.; Passino, C.; Landini, L.; Emdin, M.; Vanello, N. A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results. Sensors 2016, 16, 1828.

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