Protocolo de procesamiento de electrooculogramas para la evaluación y el seguimiento de pacientes con Ataxia Espinocerebelosa tipo 2

  • Roberto A. Becerra García
  • Gonzalo Joya Caparros
  • Luis Velázquez Pérez


The analysis of eye movements is an useful tool to evaluate various neurological disfunctions, among them is the Spinocerebellar Ataxia Type 2 (SCA2). This work is about the process of design a protocol for the the processing of eye movement records carried out at the Centre of Research and Rehabilitation of Hereditary Ataxias (CIRAH, spanish accronym) of Holguin city, Cuba. To accomplish this task, the process of processing was separated in four stages: filtering, differentiation, annotation and calculation of features; choosing at every stage the fundamentals methods and tools used frequently to solve each of yielded problems.
El análisis de los movimientos oculares constituye una herramienta útil para el estudio de una gran variedad de disfunciones neurológicas entre las que se encuentra la Ataxia Espinocerebelosa Tipo 2 (SCA2, en inglés Spinocerebellar Ataxia Type 2 ). Este trabajo aborda el proceso de diseño de un protocolo para el procesamiento de los registros de movimientos oculares que se realizan en el Centro de Investigación y Rehabilitación de Ataxias Hereditarias (CIRAH) de la ciudad de Holguín. Para lograr esta tarea se separa el proceso de procesamiento en cuatro etapas fundamentales: filtrado, diferenciación, etiquetado y cálculo de características; seleccionándose para cada una de las etapas los principales métodos y herramientas empleados comúnmente en éstas.




[1] L. Velázquez, R. García, N. Santos, M. Paneque, E. Medina, R. Hechavarría, Las ataxias hereditarias en cuba. aspectos históricos, epidemiológicos, clínicos, electrofisiológicos y de neurología cuantitativa, Revista de Neurología 32 (1) (2001) 71–76.

[2] L. Velázquez-Pérez, G. Sánchez-Cruz, N. Santos-Falcón, L. E. Almaguer-Mederos, K. Escalona-Batallan, R. Rodríguez-Labrada, M. Paneque-Herrera, J. M. Laffita-Mesa, J. C. Rodríguez-Díaz, R. Aguilera-Rodríguez, Y. González-Zaldivar, D. Coello-Almarales, D. Almaguer-Gotay, H. Jorge-Cedeno, Molecular epidemiology of spinocerebellar taxias in cuba: Insights into sca2 founder effect in holguin, Neuroscience Letters 454 (2) (2009) 157–160.

[3] R. J. Leigh, D. S. Zee, The neurology of eye movements, Vol. 90, Oxford University Press, USA, 2015.

[4] L. Velázquez Pérez, Ataxia espinocerebelosa tipo 2. Diagnóstico, pronóstico y evolución, 3rd Edition,E ditorial Ciencias Médicas, La Habana, 2012.

[5] R. Krupinski, P. Mazurek, Electrooculography signal estimation by using evolution-based technique for computer animation applications, Vol. 6374 LNCS, 2010.

[6] R. V. García Bermúdez, Procesamiento de registros oculares sacádicos en pacientes de ataxia SCA2. aplicación del análisis de componentes independientes., Ph.D. thesis, Universidad de Granada, Granada, España (Noviembre 2010).

[7] M. Martínez, E. Soria, R. Magdalena, A. J. Serrano, J. D. Martín, J. Vila, Comparative study of several fir median hybrid filters for blink noise removal in electrooculograms, WSEAS Trans. Sig. Proc. 4 (3) (2008) 53–59.

[8] M. Juhola, The effect of digital lowpass filters on the maximum velocity of saccadic eye movements, Computers in Biology and Medicine 16 (5) (1986) 361–370.

[9] M. Juhola, Median filtering is appropriate to signals of saccadic eye movements, Computers in Biology and Medicine 21 (1-2) (1991) 43–49.

[10] M. Reddy, B. Narasimha, E. Suresh, K. Rao, Analysis of EOG signals using wavelet transform for detecting eye blinks, 2010, pp. 1 –4.

[11] R. L. Burden, J. D. Faires, Numerical Analysis, 9th Edition, Cengage Learning, Canada, 2011.

[12] A. Bahill, J. McDonald, Computing eye velocities with a two-point central difference algorithm., 1982, pp. 254–257.

[13] P. Niemenlehto, Constant false alarm rate detection of saccadic eye movements in electrooculography, Computer Methods and Programs in Biomedicine 96 (2) (2009) 158–171.

[14] A. T. Bahill, J. S. Kallman, J. E. Lieberman, Frequency limitations of the two-point central difference differentiation algorithm, Biological Cybernetics 45 (1) (1982) 1–4.

[15] P. Inchingolo, M. Spanio, On the identification and analysis of saccadic eye movements. a quantitative study of the processing procedures, IEEE Transactions on Biomedical Engineering 32 (9) (1985) 683–695.

[16] A. Savitzky, M. J. E. Golay, Smoothing and differentiation of data by simplified least squares procedures., Analytical Chemistry 36 (8) (1964) 1627–1639.

[17] F. Shic, B. Scassellati, K. Chawarska, The incomplete fixation measure, ACM, Savannah, Georgia, 2008, pp. 111–114.

[18] J. Anliker, Eye movements - on-line measurement, analysis, and control.

[19] D. D. Salvucci, J. H. Goldberg, Identifying fixations and saccades in eye-tracking protocols, ACM, Palm Beach Gardens, Florida, United States, 2000, pp. 71–78.

[20] R. W. Baloh, A. W. Sills, W. Kumley, V. Honrubia, Quantitative measurement of saccade amplitude, duration, and velocity, Neurology 25 (11) (1975) 1065.

[21] A. Bahill, A. Brockenbrough, B. Troost, Variability and development of a normative data base for saccadic eye movements, Investigative Ophthalmology and Visual Science 21 (1 II) (1981) 116–125.

[22] M. Juhola, V. Jántti, I. Pyykkö, M. Magnusson, L. Schalén, M. ̊Akesson, Detection of saccadic eye movements using a non-recursive adaptive digital filter, Computer Methods and Programs in Biomedicine 21 (2) (1985) 81–88.

[23] H. Wyatt, Detecting saccades with jerk, Vision Research 38 (14) (1998) 2147–2153.

[24] J. Keegan, E. Burke, J. Condron, An electrooculogram-based binary saccade sequence classification (bssc) technique for augmentative communication and control, Conference Proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 1 (2009) 2604–2607, PMID: 19965222.

[25] P.-H. Niemenlehto, M. Juhola, Application of the cell averaging constant false alarm rate technique to saccade detection in electro-oculography, 2007, pp. 586–589.

[26] M. Juhola, T. Grönfors, A scheme of inference of regular grammars for the syntactic pattern recognition of saccadic eye movements, Artificial Intelligence in Medicine 3 (2) (1991) 87–93.

[27] M. Juhola, A syntactic analysis method for eye movements of vestibulo-ocular reflex, Computer Methods and Programs in Biomedicine 46 (1) (1995) 59–65.

[28] P. Tigges, N. Kathmann, R. R. Engel, Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings, International Journal of Medical Informatics 45 (1997) 175–184.

[29] A. T. Bahill, M. R. Clark, L. Stark, The main sequence, a tool for studying human eye movements, Mathematical Biosciences 24 (3-4) (1975) 191–204.

[30] E. Irving, M. Steinbach, Development of the saccadic amplitude/velocity relationship, Investigative Ophthalmology and Visual Science 38 (4).

[31] S. Garbutt, M. R. Harwood, C. M. Harris, Comparison of the main sequence of reflexive saccades and the quick phases of optokinetic nystagmus, Br J Ophthalmol 85 (12) (2001) 1477–1483.

[32] J. B. J. Smeets, I. T. C. Hooge, Nature of variability in saccades, J Neurophysiol 90 (1) (2003) 12–20.