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
VALENZA, GAETANO;LANATA', ANTONIO;MAURI, MAURO;SCILINGO, ENZO PASQUALE;
2012-01-01
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 depressionI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
