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Erschienen in:
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2016 | OriginalPaper | Buchkapitel

Non-lineal EEG Modelling by Using Quadratic Entropy for Arousal Level Classification

verfasst von : Arturo Martínez-Rodrigo, Raúl Alcaraz, Beatriz García-Martínez, Roberto Zangróniz, Antonio Fernández-Caballero

Erschienen in: Innovation in Medicine and Healthcare 2016

Verlag: Springer International Publishing

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Abstract

Nowadays, assistive technologies together with ubiquitous and pervasive computing are emerging as main alternative to help ageing population. In this respect, an important number of works have been carried out to improve the quality of life in elderly from a physical point of view. However, less efforts have been made in monitoring the mental and emotional states of the elderly. This work presents a non-linear model for discriminating different arousal levels through quadratic entropy and a decision tree-based algorithm. Two hundred and seventy eight EEG recordings lasting one minute each were used to train the proposed model. The recordings belong to the Dataset for Emotion Analysis using Physiological signals (DEAP). In agreement with the complexity and variability observed in other works, our results report a low quadratic entropy when subjects face high arousal stimuli. Finally, the model achieves a global performance around 70 % when discriminating between calm and excitement events.

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Vorheriges Kapitel Erratum to: Hygehos Ontology for Electronic Health Records
Nächstes Kapitel Emotional Induction Through Films: A Model for the Regulation of Emotions
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Metadaten
Titel
Non-lineal EEG Modelling by Using Quadratic Entropy for Arousal Level Classification
verfasst von
Arturo Martínez-Rodrigo
Raúl Alcaraz
Beatriz García-Martínez
Roberto Zangróniz
Antonio Fernández-Caballero
Copyright-Jahr
2016
Buch
Innovation in Medicine and Healthcare 2016

Print ISBN: 978-3-319-39686-6

Electronic ISBN: 978-3-319-39687-3

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-39687-3_1