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Methods Inf Med 2014; 53(04): 296-302
DOI: 10.3414/ME13-02-0036
Focus Theme – Original Articles
Schattauer GmbH

Point-process Nonlinear Autonomic Assessment of Depressive States in Bipolar Patients

G. Valenza
1   Neuroscience Statistics Research Laboratory, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA, and Massachusetts Institute of Technology, Cambridge, MA, USA
2   Research Center “E. Piaggio”, University of Pisa, Pisa, Italy
,
L. Citi
1   Neuroscience Statistics Research Laboratory, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA, and Massachusetts Institute of Technology, Cambridge, MA, USA
4   School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK
,
C. Gentili
3   Department of Psychiatry, Neurobiology, Pharmacology and Biotechnology, University of Pisa, Pisa, Italy
,
A. Lanatá
2   Research Center “E. Piaggio”, University of Pisa, Pisa, Italy
,
E. P. Scilingo
2   Research Center “E. Piaggio”, University of Pisa, Pisa, Italy
,
R. Barbieri
1   Neuroscience Statistics Research Laboratory, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA, and Massachusetts Institute of Technology, Cambridge, MA, USA
› Author Affiliations
Further Information

Publication History

received:14 October 2013

accepted:14 May 2014

Publication Date:
20 January 2018 (online)

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Summary

Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Biosignal Interpretation: Advanced Methods for Studying Cardiovascular and Respiratory Systems”.

Objectives: The goal of this work is to apply a computational methodology able to characterize mood states in bipolar patients through instantaneous analysis of heartbeat dynamics.

Methods: A Point-Process-based Nonlinear Autoregressive Integrative (NARI) model is applied to analyze data collected from five bipolar patients (two males and three females, age 42.4 ± 10.5 range 32−56) undergoing a dedicated affective elicitation protocol using images from the International Affective Picture System (IAPS) and Thematic Apperception Test (TAT). The study was designed within the European project PSYCHE (Personalised monitoring SYstems for Care in mental HEalth).

Results: Results demonstrate that the inclusion of instantaneous higher order spectral (HOS) features estimated from the NARI nonlinear assessment significantly improves the accuracy in successfully recognizing specific mood states such as euthymia and depression with respect to results using only linear indices. In particular, a specificity of 74.44% using the instantaneous linear features set, and 99.56% using also the nonlinear feature set were achieved. Moreover, IAPS emotional elicitation resulted in a more discriminant procedure with respect to the TAT elicitation protocol.

Conclusions: A significant pattern of instantaneous heartbeat features was found in depressive and euthymic states despite the inter-subject variability. The presented point-process Heart Rate Variability (HRV) nonlinear methodology provides a promising application in the field of mood assessment in bipolar patients.

Keywords

Bipolar Disorder - Heart Rate Variability (HRV) - Point Process - High Order Statistics - Bispectrum - Nonlinear Analysis - Wiener-Volterra Series - International Affective Picture System (IAPS) - Thematic Apperception Test (TAT)
 

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