The goal of this work is to develop a computa- tional methodology able to characterize mood states in bipolar patients by analysis of heartbeat dynam- ics. A novel Point-Process-based Nonlinear Autore- gressive Integrative (NARI) model is applied to ana- lyze data collected from bipolar patients undergoing a dedicated affective elicitation protocol designed within the European project PSYCHE (Personalised monitoring SYstems for Care in mental HEalth) plat- form. Results demonstrate that inclusion of instan- taneous higher order spectral (HOS) features esti- mated from the NARI nonlinear assessment signif- icantly improve the accuracy in successfully recog- nizing specific mood states such as euthymia and depression
A point-process nonlinear model approach for autonomic assessment of depressive states in bipolar patients / G. Valenza; L. Citi; C. Gentili; A. Lanatà; M. Mauri; Scilingo E.P.; R. Barbieri. - ELETTRONICO. - (2012), pp. 1-4. (Intervento presentato al convegno 7th International Workshop on Biosignal Interpretation (BSI2012) tenutosi a Come (ITALY) nel 02/06/2012-04/06/2012).
A point-process nonlinear model approach for autonomic assessment of depressive states in bipolar patients
A. Lanatà;
2012
Abstract
The goal of this work is to develop a computa- tional methodology able to characterize mood states in bipolar patients by analysis of heartbeat dynam- ics. A novel Point-Process-based Nonlinear Autore- gressive Integrative (NARI) model is applied to ana- lyze data collected from bipolar patients undergoing a dedicated affective elicitation protocol designed within the European project PSYCHE (Personalised monitoring SYstems for Care in mental HEalth) plat- form. Results demonstrate that inclusion of instan- taneous higher order spectral (HOS) features esti- mated from the NARI nonlinear assessment signif- icantly improve the accuracy in successfully recog- nizing specific mood states such as euthymia and depression
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