Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Cover of the book

2016 | OriginalPaper | Chapter

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

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

Published in: Innovation in Medicine and Healthcare 2016

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

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.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Erratum to: Hygehos Ontology for Electronic Health Records
next chapter Emotional Induction Through Films: A Model for the Regulation of Emotions
Literature
1.
Lutz, W., Sanderson, W., Scherbov, S.: The coming acceleration of global population ageing. Nature 451(7179), 716–719 (2008)CrossRef
2.
United Nations Department of Economic, World Population Ageing 2009, vol. 295. United Nations Publications (2010)
3.
Carone, G., Costello, D., Diez Guardia, N., Mourre, G., Przywara, B., Salomäki, A.: The economic impact of ageing populations in the eu25 member states. Directorate General for Economic and Financial Affairs (236)
4.
World Health Organization, et al.: Global Health and Ageing
5.
Castillo, J.C., Castro-González, A., Fernández-Caballero, A., Latorre, J.M., Pastor, J.M., Fernández-Sotos, A., Salichs, M.A.: Software architecture for smart emotion recognition and regulation of the ageing adult. Cognitive Computation. In Press
6.
Fernández-Caballero, A., Latorre, J.M., Pastor, J.M., Fernández-Sotos, A.: Improvement of the elderly quality of life and care through smart emotion regulation. In: Ambient Assisted Living and Daily Activities, pp. 348–355. Springer (2014)
7.
Martínez-Rodrigo, A., Zangróniz, R., Pastor, J.M., Fernández-Caballero, A.: Arousal level classification in the ageing adult by measuring electrodermal skin conductivity. In: Ambient Intelligence for Health, pp. 213–223. Springer (2015)
8.
Costa, Â., Castillo, J.C., Novais, P., Fernández-Caballero, A., Simoes, R.: Sensor-driven agenda for intelligent home care of the elderly. Expert Syst. Appl. 39(15), 12192–12204 (2012)CrossRef
9.
García-Rodríguez, C., Martínez-Tomás, R., Cuadra-Troncoso, J.M., Rincón, M., Fernández-Caballero, A.: A simulation tool for monitoring elderly who suffer from disorientation in a smart home. Expert Syst. 32(6), 676–687 (2015)CrossRef
10.
German, W.J.: The hypothalamus and central levels of autonomic function. Yale J. Biol. Med. 12(5), 602–603 (1940)
11.
Schacter, D.L.: Psychology, 2nd edn. (2011)
12.
Nasoz, F., Lisetti, C.L., Alvarez, K., Finkelstein, N.: Emotion recognition from physiological signals for user modeling of affect. In: Proceedings of the 3rd Workshop on Affective and Attitude User Modelling, pp. 1–8 (2003)
13.
Russell, J.A.: A circumplex model of affect. J. Pers. Soc. Psychol. 39(6), 1161 (1980)CrossRef
14.
Kim, J.: Bimodal emotion recognition using speech and physiological changes. In: Robust Speech Recognition and Understanding, INTECH Open, pp. 265–280 (2007)
15.
Valenza, G., Lanata, A., Scilingo, E.P.: The role of nonlinear dynamics in affective valence and arousal recognition. IEEE Trans. Affect. Comput. 3(2), 237–249 (2012)CrossRef
16.
Hatamikia, S., Nasrabadi, A.: Recognition of emotional states induced by music videos based on nonlinear feature extraction and som classification. In: 21th Iranian Conference on Biomedical Engineering, pp. 333–337. IEEE (2014)
17.
Akar, S.A., Kara, S., Agambayev, S., Bilgic, V.: Nonlinear analysis of eeg in major depression with fractal dimensions. In: 37th Annual International Conference of the IEEE on Engineering in Medicine and Biology Society), pp. 7410–7413. IEEE (2015)
18.
Koelstra, S., Mühl, C., Soleymani, M., Lee, J.-S., Yazdani, A., Ebrahimi, T., Pun, T., Nijholt, A., Patras, I.: Deap: a database for emotion analysis; using physiological signals. IEEE Trans. Affect. Comput. 3(1), 18–31 (2012)CrossRef
19.
Philippot, P.: Inducing and assessing differentiated emotion-feeling states in the laboratory. Cogn. Emot. 7(2), 171–193 (1993)CrossRef
20.
Richman, J.S., Moorman, J.R.: Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol. Heart Circulatory Physiol. 278(6), 2039–2049 (2000)
21.
22.
Lake, D.E., Moorman, J.R.: Accurate estimation of entropy in very short physiological time series: the problem of atrial fibrillation detection in implanted ventricular devices. Am. J. Physiol. Heart Circulatory Physiol. 300(1), 319–325 (2011)CrossRef
23.
Alcaraz, R., Abásolo, D., Hornero, R., Rieta, J.J.: Optimal parameters study for sample entropy-based atrial fibrillation organization analysis. Comput. Methods Prog. Biomed. 99(1), 124–132 (2010)CrossRef
24.
Breiman, L., Friedman, J., Stone, C.J., Olshen, R.A.: Classification and Regression Trees. CRC Press (1984)
25.
Hosseini, S.A., Naghibi-Sistani, M.B.: Classification of emotional stress using brain activity. In: Applied Biomedical Engineering, INTECH Open, pp. 313–336 (2011)
26.
Dolcos, F., Cabeza, R.: Event-related potentials of emotional memory: encoding pleasant, unpleasant, and neutral pictures. Cogn. Affect. Behav. Neurosci. 2(3), 252–263 (2002)CrossRef
Metadata
Title
Non-lineal EEG Modelling by Using Quadratic Entropy for Arousal Level Classification
Authors
Arturo Martínez-Rodrigo
Raúl Alcaraz
Beatriz García-Martínez
Roberto Zangróniz
Antonio Fernández-Caballero
Copyright Year
2016
Book
Innovation in Medicine and Healthcare 2016

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

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

Copyright Year: 2016

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

Premium Partner

    Image Credits