title: Longitudinal monitoring of heartbeat dynamics predicts mood changes in bipolar patients: A pilot study.
abstract: Recent research indicates that Heart Rate Variability (HRV) is affected in Bipolar Disorders (BD) patients. To determine whether such alterations are a mere expression of the current mood state or rather contain longitudinal information on BD course, we examined the potential influence of states adjacent in time upon HRV features measured in a target mood state.
  
  
  
  Longitudinal evaluation of HRV was obtained in eight BD patients by using a wearable monitoring system developed within the PSYCHE project. We extracted time-domain, frequency-domain and non-linear HRV-features and trained a Support Vector Machine (SVM) to classify HRV-features according to mood state. To evaluate the influence of adjacent mood states, we trained SVM with different HRV-feature sets: 1) belonging to each mood state considered alone; 2) belonging to each mood state and normalized using information from the preceding mood state; 3) belonging to each mood state and normalized using information from the preceding and subsequent mood states; 4) belonging to each mood state and normalized using information from two randomly chosen states.
  
  
  
  SVM classification accuracy within a target state was significantly greater when HRV-features from the previous and subsequent mood states were considered.
  
  
  
  Although preliminary and in need of replications our results suggest for the first time that psychophysiological states in BD contain information related to the subsequent ones. Such characteristic may be used to improve clinical management and to develop algorithms to predict clinical course and mood switches in individual patients.
authors.affiliation: Department of General Psychology, University of Padua, Via Venezia 8, 35139 Padua, Italy. Electronic address: c.gentili@unipd.it.
authors.forename: Claudio
authors.initials: C
authors.lastname: Gentili
authors.affiliation: Department of Information Engineering & Research Centre "E. Piaggio", School of Engineering, University of Pisa, Italy.
authors.forename: Gaetano
authors.initials: G
authors.lastname: Valenza
authors.affiliation: Department of Information Engineering & Research Centre "E. Piaggio", School of Engineering, University of Pisa, Italy.
authors.forename: Mimma
authors.initials: M
authors.lastname: Nardelli
authors.affiliation: Department of Information Engineering & Research Centre "E. Piaggio", School of Engineering, University of Pisa, Italy.
authors.forename: Antonio
authors.initials: A
authors.lastname: Lanatà
authors.affiliation: INSERM U1114, Fédération de Médecine Translationnelle de Strasbourg, Université de Strasbourg, Pôle de Psychiatrie et Santé Mentale des Hôpitaux Universitaires de Strasbourg, France.
authors.forename: Gilles
authors.initials: G
authors.lastname: Bertschy
authors.affiliation: INSERM U1114, Fédération de Médecine Translationnelle de Strasbourg, Université de Strasbourg, Pôle de Psychiatrie et Santé Mentale des Hôpitaux Universitaires de Strasbourg, France.
authors.forename: Luisa
authors.initials: L
authors.lastname: Weiner
authors.affiliation: Section of Psychiatry, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
authors.forename: Mauro
authors.initials: M
authors.lastname: Mauri
authors.affiliation: Department of Information Engineering & Research Centre "E. Piaggio", School of Engineering, University of Pisa, Italy.
authors.forename: Enzo Pasquale
authors.initials: EP
authors.lastname: Scilingo
authors.affiliation: IMT School for Advanced Studies, Piazza San Ponziano, 6 - 55100 Lucca, Italy. Electronic address: pietro.pietrini@imtlucca.it.
authors.forename: Pietro
authors.initials: P
authors.lastname: Pietrini
mesh_terms: D000328:Adult; D000339:Affect; D001714:Bipolar Disorder / Q000503:physiopathology* / Q000523:psychology*; D004562:Electrocardiography; D005260:Female; D006339:Heart Rate; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D010865:Pilot Projects; D011569:Psychiatric Status Rating Scales; D060388:Support Vector Machine
keywords: Biological psychiatry; Bipolar disorders; Heart rate variability; Psychophysiology; Supported vector machine