This paper reports on a multiclass arousal recognition system based on autonomic nervous system linear and nonlinear dynamics during affective visual elicitation. We propose a new hybrid method based on Lagged Poincaré Plot (LPP) and symbolic analysis, hereinafter called LPPsymb. This tool uses symbolic analysis to evaluate the irregularity of the trends of Lagged Poincaré Plot (LPP) quantifiers over the lags, and is here applied to investigate complex Heart Rate Variability (HRV) changes during emotion stimuli. In the experimental protocol 22 healthy subjects were elicited through a passive visualization of affective images gathered from the international affective picture system. LPPsymb and standard HRV analysis (defined in time and frequency domains) were applied to HRV series of one minute length. Then, an ad-hoc pattern recognition algorithm based on quadratic discriminant classifier was implemented and validated through a leave-onesubject-out procedure. The best performance of the proposed classification algorithm for recognizing the four classes of arousal was obtained using nine features comprising heartbeat complex dynamics, achieving an accuracy of 71.59%.

A Multiclass Arousal Recognition using HRV Nonlinear Analysis and Affective Images / Nardelli, M.; Greco, A.; Valenza, G.; Lanata, A.; Bailon, R.; Scilingo, E. P.. - 2018-:(2018), pp. 392-395. (Intervento presentato al convegno 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 tenutosi a Hawaii Convention Center, usa nel 2018) [10.1109/EMBC.2018.8512426].

A Multiclass Arousal Recognition using HRV Nonlinear Analysis and Affective Images

Lanata, A.;
2018

Abstract

This paper reports on a multiclass arousal recognition system based on autonomic nervous system linear and nonlinear dynamics during affective visual elicitation. We propose a new hybrid method based on Lagged Poincaré Plot (LPP) and symbolic analysis, hereinafter called LPPsymb. This tool uses symbolic analysis to evaluate the irregularity of the trends of Lagged Poincaré Plot (LPP) quantifiers over the lags, and is here applied to investigate complex Heart Rate Variability (HRV) changes during emotion stimuli. In the experimental protocol 22 healthy subjects were elicited through a passive visualization of affective images gathered from the international affective picture system. LPPsymb and standard HRV analysis (defined in time and frequency domains) were applied to HRV series of one minute length. Then, an ad-hoc pattern recognition algorithm based on quadratic discriminant classifier was implemented and validated through a leave-onesubject-out procedure. The best performance of the proposed classification algorithm for recognizing the four classes of arousal was obtained using nine features comprising heartbeat complex dynamics, achieving an accuracy of 71.59%.
2018
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Hawaii Convention Center, usa
2018
Nardelli, M.; Greco, A.; Valenza, G.; Lanata, A.; Bailon, R.; Scilingo, E. P.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1192185
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