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Linear and nonlinear methods for analyses of cardiovascular variability in bipolar disorders


  • The authors of this paper do not have any commercial associations that might pose a conflict of interest in connection with this manuscript.

Corresponding author: Prof. Dr. Andreas Voss, Department of Medical Engineering, University of Applied Sciences Jena, Carl-Zeiss-Promenade 2, 07745 Jena, Germany. Fax: +49-(0)3641-205626; e-mail:


Objectives:  Heart rate variability (HRV), blood pressure variability (BPV), and the assessment of baroreflex sensitivity are widely accepted methods for analyzing and characterizing cardiovascular regulation and for an enhanced risk evaluation in different diseases. As a result of the complexity of the investigated regulatory systems, univariate analyses do not often provide a convenient description of pathological changes in the cardiovascular regulation. Therefore, the application of a multivariate approach is preferable.

Methods:  We present principal methods of time-domain, frequency-domain, and nonlinear analyses of HRV, BPV as well as methods for coupling and interaction analyses.

Results:  Changes in autonomic nervous system (ANS) tone are known to accompany various mental disorders. Depressive patients frequently complain of symptoms of ANS dysfunction, such as dry mouth, diarrhea, and insomnia. These clinical observations propose the assumption of altered autonomic dysfunction in these patients. In contrast to these clinical assumptions, inconsistent results have been found in studies of HRV in depressive patients. This work therefore covers a brief review of the literature in respect to bipolar disorder and the rationale to study autonomic changes in such a psychiatric disease.

Conclusions:  Prospective studies of cardiovascular changes in mania and depression are needed to evaluate a psychopathological state in connection with cardiovascular changes and cardiac morbidity and mortality. These studies should consider BPV, coupling and interaction analyses, the application of nonlinear methods, and a multivariate approach in addition to the traditional analysis of HRV.