Title :
Electrodermal Activity in Bipolar Patients during Affective Elicitation
Author :
Greco, Alberto ; Valenza, Gaetano ; Lanata, Antonio ; Rota, Giuseppina ; Scilingo, Enzo Pasquale
Author_Institution :
Dept. of Inf. Eng. & Res. Center “E. Piaggio”, Univ. of Pisa, Pisa, Italy
Abstract :
Bipolar patients are characterized by a pathological unpredictable behavior, resulting in fluctuations between states of depression and episodes of mania or hypomania. In the current clinical practice, the psychiatric diagnosis is made through clinician-administered rating scales and questionnaires, disregarding the potential contribution provided by physiological signs. The aim of this paper is to investigate how changes in the autonomic nervous system activity can be correlated with clinical mood swings. More specifically, a group of ten bipolar patients underwent an emotional elicitation protocol to investigate the autonomic nervous system dynamics, through the electrodermal activity (EDA), among different mood states. In addition, a control group of ten healthy subjects were recruited and underwent the same protocol. Physiological signals were analyzed by applying the deconvolutive method to reconstruct EDA tonic and phasic components, from which several significant features were extracted to quantify the sympathetic activation. Experimental results performed on both the healthy subjects and the bipolar patients supported the hypothesis of a relationship between autonomic dysfunctions and pathological mood states.
Keywords :
bioelectric potentials; deconvolution; feature extraction; medical disorders; medical signal processing; neurophysiology; psychology; signal reconstruction; skin; EDA phasic component reconstruction; EDA tonic component reconstruction; autonomic nervous system dynamics; bipolar patients; clinical mood swings; deconvolutive method; depression states; electrodermal activity; emotional elicitation protocol; episode states; feature extraction; hypomania; pathological mood states; pathological unpredictable behavior; physiological signal analysis; psychiatric diagnosis; Feature extraction; Mental disorders; Mood; Patient monitoring; Physiology; Protocols; Statistical analysis; Bipolar disorder; deconvolutive analysis; electrodermal activity (EDA); mood recognition;
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
DOI :
10.1109/JBHI.2014.2300940