Abstract
The quantification of interdependencies within autonomic nervous system has gained increasing importance to characterise healthy and psychiatric disordered subjects. The present work introduces a biosignal processing approach, suggesting a computational resource to estimate coherent or synchronised interactions as an eventual supportive aid in the diagnosis of primary insomnia and schizophrenia pathologies. By deploying linear, nonlinear and statistical methods upon 25 electroencephalographic and electrocardiographic overnight sleep recordings, the assessment of cross-correlation, wavelet coherence and \({\mathbf {n}}\):\({\mathbf {m}}\) phase synchronisation is focused on tracking discerning features amongst the clinical cohorts. Our results indicate that certain neuronal oscillations interact with cardiac power bands in distinctive ways responding to standardised sleep stages and patient groups, which promotes the hypothesis of subtle functional dynamics between neuronal assembles and (para)sympathetic activity subject to pathophysiological conditions.
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Acknowledgments
The authors would like to thank the Sleep Laboratory of the Central Institute of Mental Health for undertaking the recruitment and collection of polysomnographic recordings, which served as the main experimental source for the present research work. R. Chaparro-Vargas acknowledges the financial support of COLCIENCIAS-COLFUTURO of the Colombian Government, as main sponsor for his doctorate studies.
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Chaparro-Vargas, R., Schilling, C., Schredl, M. et al. Sleep electroencephalography and heart rate variability interdependence amongst healthy subjects and insomnia/schizophrenia patients. Med Biol Eng Comput 54, 77–91 (2016). https://doi.org/10.1007/s11517-015-1297-4
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DOI: https://doi.org/10.1007/s11517-015-1297-4