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Heart Rate Variability Analysis Guided by Respiration in Major Depressive Disorder

Kontaxis, S; Orini, M; Gil, E; Posadas-de Miguel, M; Luisa Bernal, M; Aguilo, J; de la Camara, C; ... Bailon, R; + view all (2018) Heart Rate Variability Analysis Guided by Respiration in Major Depressive Disorder. In: (Proceedings) 45th Computing in Cardiology Conference (CinC). IEEE Green open access

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Abstract

In this study a Heart Rate Variability (HRV) analysis guided by respiration to evaluate different patterns of Autonomic Nervous System (ANS) in response to a cognitive stressor between Major Depressive Disorder (MDD) and control (CT) subjects is presented. Cardiorespiratory Time Frequency Coherence (TFC) reveals the local coupling of HRV and respiration signal which is essential and usually not included in estimation of ANS measures derived by HRV. Parasympathetic activity of ANS is measured as the power at the frequencies where TFC between HRV and respiration is significant, whereas sympathetic dominance is measured as the normalized power in the low frequency band [0.04,0.15] Hz of HRV excluding the power of those frequencies related to respiration. Results showed significantly lower (p <; 0.05) sympathetic dominance in MDD with respect to CT subjects during stress, suggesting that ANS reactivity as response to stress stimuli is lower in MDD patients. The study of ANS reactivity to a stressor may serve as a biomarker useful for the early diagnosis and monitoring of MDD patients.

Type: Proceedings paper
Title: Heart Rate Variability Analysis Guided by Respiration in Major Depressive Disorder
Event: 45th Computing in Cardiology Conference (CinC)
Location: Maastricht, NETHERLANDS
Dates: 23 September 2018 - 26 September 2018
Open access status: An open access version is available from UCL Discovery
DOI: 10.22489/CinC.2018.319
Language: English
Additional information: CinC has been an open-access publication, in which copyright in each article is held by its authors, who grant permission to copy and redistribute their work with attribution, under the terms of the Creative Commons Attribution License. (https://creativecommons.org/licenses/by/2.5/)
Keywords: Science & Technology, Technology, Computer Science, Interdisciplinary Applications, Engineering, Multidisciplinary, Engineering, Biomedical, Computer Science, Engineering, STRESS, TASK
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine > MRC Unit for Lifelong Hlth and Ageing
URI: https://discovery.ucl.ac.uk/id/eprint/10123845
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