PMID- 24970591
OWN - NLM
STAT- MEDLINE
DCOM- 20160923
LR  - 20170410
IS  - 2511-705X (Electronic)
IS  - 0026-1270 (Linking)
VI  - 53
IP  - 4
DP  - 2014
TI  - Point-process nonlinear autonomic assessment of depressive states in bipolar 
      patients.
PG  - 296-302
LID - 10.3414/ME13-02-0036 [doi]
AB  - 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.
FAU - Valenza, G
AU  - Valenza G
AD  - Gaetano Valenza, Ph.D., Department of Information Engineering, Research Centre 
      "E. Piaggio", Faculty of Engineering, University of Pisa, Via G. Caruso 16, 56122 
      Pisa, Italy.
FAU - Citi, L
AU  - Citi L
FAU - Gentili, C
AU  - Gentili C
FAU - Lanata, A
AU  - Lanata A
FAU - Scilingo, E P
AU  - Scilingo EP
FAU - Barbieri, R
AU  - Barbieri R
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20140627
PL  - Germany
TA  - Methods Inf Med
JT  - Methods of information in medicine
JID - 0210453
SB  - IM
MH  - Adolescent
MH  - Adult
MH  - *Affect
MH  - Autonomic Nervous System/*physiopathology
MH  - Bipolar Disorder/*diagnosis/physiopathology
MH  - Diagnosis, Computer-Assisted/*methods
MH  - Female
MH  - Heart Rate/*physiology
MH  - Humans
MH  - Male
MH  - Middle Aged
MH  - *Monitoring, Physiologic/statistics & numerical data
MH  - *Nonlinear Dynamics
MH  - Psychological Tests/statistics & numerical data
MH  - Young Adult
OTO - NOTNLM
OT  - Bipolar Disorder
OT  - Bispectrum
OT  - Heart Rate Variability (HRV)
OT  - High Order Statistics
OT  - International Affective Picture System (IAPS)
OT  - Nonlinear Analysis
OT  - Point Process
OT  - Thematic Apperception Test (TAT)
OT  - Wiener-Volterra Series
EDAT- 2014/06/28 06:00
MHDA- 2016/09/24 06:00
CRDT- 2014/06/28 06:00
PHST- 2013/10/14 00:00 [received]
PHST- 2014/05/14 00:00 [accepted]
PHST- 2014/06/28 06:00 [entrez]
PHST- 2014/06/28 06:00 [pubmed]
PHST- 2016/09/24 06:00 [medline]
AID - 13-02-0036 [pii]
AID - 10.3414/ME13-02-0036 [doi]
PST - ppublish
SO  - Methods Inf Med. 2014;53(4):296-302. doi: 10.3414/ME13-02-0036. Epub 2014 Jun 27.