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Characterization of depressive states in bipolar patients using wearable textile technology and instantaneous heart rate variability assessment

Valenza, G and Citi, L and Gentili, C and Lanatá, A and Scilingo, EP and Barbieri, R (2015) 'Characterization of depressive states in bipolar patients using wearable textile technology and instantaneous heart rate variability assessment.' IEEE Journal of Biomedical and Health Informatics, 19 (1). 263 - 274. ISSN 2168-2194

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Abstract

© 2014 IEEE. The analysis of cognitive and autonomic responses to emotionally relevant stimuli could provide a viable solution for the automatic recognition of different mood states, both in normal and pathological conditions. In this study, we present a methodological application describing a novel system based on wearable textile technology and instantaneous nonlinear heart rate variability assessment, able to characterize the autonomic status of bipolar patients by considering only electrocardiogram recordings. As a proof of this concept, our study presents results obtained from eight bipolar patients during their normal daily activities and being elicited according to a specific emotional protocol through the presentation of emotionally relevant pictures. Linear and nonlinear features were computed using a novel point-process-based nonlinear autoregressive integrative model and compared with traditional algorithmic methods. The estimated indices were used as the input of a multilayer perceptron to discriminate the depressive from the euthymic status. Results show that our system achieves much higher accuracy than the traditional techniques. Moreover, the inclusion of instantaneous higher order spectra features significantly improves the accuracy in successfully recognizing depression from euthymia.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 09 Jul 2015 09:45
Last Modified: 17 Aug 2017 17:36
URI: http://repository.essex.ac.uk/id/eprint/14095

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