Pupillometric Study of the Dysregulation of the Autonomous Nervous System by SVM Networks

  • Luca Mesin
  • Ruggero Cattaneo
  • Annalisa Monaco
  • Eros Pasero
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 26)


Pupil is controlled by the autonomous nervous system. Patients with temporomandibular disorders (TMD) and with obstructive sleep apnea syndrome (OSAS) are affected by a dysregulation of the autonomous system. Pupillometry is here used to investigate the state of the autonomous system in 3 groups: control, TMD and OSAS. Different indexes are extracted from the pupillogram to characterize pupil dynamics investigated in rest and under stationary stimulations. All possible sets of 3 and 4 indexes are used as features to train support vector machines (SVM) to identify the correct groups. The indexes providing optimal classification are identified.


Support vector machine (SVM) Temporomandibular disorders (TMD) obstructive sleep apnea syndrome (OSAS) Pupillometry 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Murillo, R., Crucilla, C., Schmittner, J., Hotchkiss, E., Pickworth, W.B.: Pupillometry in the detection of concomitant drug use in opioid-maintained Patients. Methods Find Exp. Clin. Pharmacol. 26, 271–275 (2004)Google Scholar
  2. 2.
    Br, K.J., Schulz, S., Koschke, M., Harzendorf, C., Gayde, S., Berg, W., Voss, A., Yeragani, V.K., Boettger, M.K.: Correlations between the autonomic modulation of heart rate, blood pressure and the pupillary light reflex in healthy subjects. J. Neurol. Sci. 279(1-2), 9–13 (2009)CrossRefGoogle Scholar
  3. 3.
    Keivanidou, A., Fotiou, D., Arnaoutoglou, C., Arnaoutoglou, M., Fotiou, F., Karlovasitou, A.: Evaluation of autonomic imbalance in patients with heart failure: a preliminary study of pupillomotor function. Cardiol. J. 17(1), 65–72 (2010)Google Scholar
  4. 4.
    Censi, F., Calcagnini, G., Cerutti, S.: Coupling patterns between spontaneous rhythms and respiration in cardiovascular variability signals. Comput. Methods Programs Biomed. 68(1), 37–47 (2002)CrossRefGoogle Scholar
  5. 5.
    Borgdorff, P.: Respiratory fluctuations in pupil size. Am. J. Physiol. 228(4), 1094–1102 (1975)Google Scholar
  6. 6.
    Wilhelm, B., Giedke, H., Ludtke, H., Bittner, E., Hofmann, A., Wilhelm, H.: Daytime variations in central nervous system activation measured by a pupillographic sleepiness test. J. Sleep Res. 10(1), 1–7 (2001)CrossRefGoogle Scholar
  7. 7.
    Eze-Nliam, C.M., Quartana, P.J., Quain, A.M., Smith, M.T.: Nocturnal heart rate variability is lower in temporomandibular disorder patients than in healthy, pain-free individuals. J. Orofac. Pain 25(3), 232–239 (2011)Google Scholar
  8. 8.
    Diatchenko, L., Slade, G.D., Nackley, A.G., Bhalang, K., Sigurdsson, A., Belfer, A., Goldman, D., Xu, K., Shabalina, S.A., Shagin, D., Max, M.B., Makarov, S.S., Maixner, W.: Genetic basis for individual variations in pain perception and the development of a chronic pain condition. Hum. Mol. Genet. 14, 135–143 (2005)CrossRefGoogle Scholar
  9. 9.
    Light, K.C., Bragdon, E.E., Grewen, K.M., Brownley, K.A., Girdler, S.S., Maixner, W.: Adrenergic dysregulation and pain with and without acute beta-blockade in women with fibromyalgia and temporomandibular disorder. J. Pain 10(5), 542–552 (2009)CrossRefGoogle Scholar
  10. 10.
    Donadio, V., Liguori, R., Vetrugno, R., Contin, M., Elam, M., Wallin, B.G., Karlsson, T., Bugiardini, E., Baruzzi, A., Montagna, P.: Daytime sympathetic hyperactivity in OSAS is related to excessive daytime sleepiness. J. Sleep Res. 16(3), 327–332 (2007)CrossRefGoogle Scholar
  11. 11.
    Montesano, M., Miano, S., Paolino, M.C., Massolo, A.C., Ianniello, F., Forlani, M., Villa, M.P.: Autonomic cardiovascular tests in children with obstructive sleep apnea syndrome. Sleep 33(10), 1349–1355 (2010)Google Scholar
  12. 12.
    Yun, A.J., Lee, P.Y., Bazar, K.A.: Autonomic dysregulation as a basis of cardiovascular, endocrine, and inflammatory disturbances associated with obstructive sleep apnea and other conditions of chronic hypoxia, hypercapnia, and acidosis. Med. Hypotheses 62(6), 852–856 (2004)CrossRefGoogle Scholar
  13. 13.
    Guilleminault, C., Poyares, D., Rosa, A., Huang, Y.S.: Heart rate variability, sympathetic and vagal balance and EEG arousals in upper airway resistance and mild obstructive sleep apnea syndromes. Sleep Med. 6(5), 451–457 (2005)CrossRefGoogle Scholar
  14. 14.
    Marwan, N., Romano, M.C., Thiel, M., Kurths, J.: Recurrence Plots for the Analysis of Complex Systems. Physics Reports 438, 237–329 (2007)CrossRefMathSciNetGoogle Scholar
  15. 15.
    Chaudhuri, B.B., Kundu, P.: Optimum circular fit to weighted data in multidimensional space. Pattern Recogn. Lett. 14, 1–6 (1993)CrossRefGoogle Scholar
  16. 16.
    Kantz, H., Schreiber, T.: Nonlinear Time-series Analysis. Cambridge Univ. Press (1997)Google Scholar
  17. 17.
    Cao, L.Y.: Practical method for determining the minimum embedding dimension of a scalar time series. Physical D 110, 43–50 (1997)CrossRefMATHGoogle Scholar
  18. 18.
    Mesin, L., Monaco, A., Cattaneo, R.: Investigation of Nonlinear Pupil Dynamics by Recurrence Quantification Analysis. BioMed. Research International (in press, 2013)Google Scholar
  19. 19.
    Zou, Y., Donner, R.V., Donges, J.F., Marwan, N., Kurths, J.: Identifying complex periodic windows in continuous-time dynamical systems using recurrence-based methods. Chaos 20(4), 043130 (2010)Google Scholar
  20. 20.
    Cortes, C., Vapnik, V.N.: Support-Vector Networks. Machine Learning, 20 (1995)Google Scholar
  21. 21.
    Monaco, A., Cattaneo, R., Mesin, L., Ciarrocchi, I., Sgolastra, F., Pietropaoli, D.: Dysregulation of the Autonomous Nervous System in Patients with Temporomandibular Disorder: A Pupillometric Study. PLoS One 7(9), e45424 (2012)Google Scholar
  22. 22.
    Javorka, M., Turianikova, Z., Tonhajzerova, I., Javorka, K., Baumert, M.: The effect of orthostasis on recurrence quantification analysis of heart rate and blood pressure dynamics. Physiol. Meas. 30(1), 29–41 (2009)CrossRefGoogle Scholar
  23. 23.
    Hayashi, N., Someya, N., Fukuba, Y.: Effect of intensity of dynamic exercise on pupil diameter in humans. J. Physiol. Anthropol. 29(3), 119–122 (2010)CrossRefGoogle Scholar
  24. 24.
    Eckberg, D.L.: Sympathovagal Balance: A Critical Appraisal. Circulation 96, 3224–3232 (1997)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Luca Mesin
    • 1
  • Ruggero Cattaneo
    • 2
  • Annalisa Monaco
    • 2
  • Eros Pasero
    • 1
  1. 1.Dipartimento di Elettronica e TelecomunicazioniPolitecnico di TorinoTurinItaly
  2. 2.Department of Life, Health and Environmental Sciences, Dental UnitUniversitá di L’AquilaL’AquilaItaly

Personalised recommendations