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2022, Number 3

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RIC 2022; 101 (3)

Correction of horizontal and angular head displacement effects by MATLAB visual stimulation tests

Benítez-Fernández A, Vázquez-Seisdedos CR, Socarrás-Hernández BN
Full text How to cite this article

Language: Spanish
References: 13
Page: 1-13
PDF size: 589.89 Kb.


Key words:

electrooculography, head movement, correction, MATLAB.

ABSTRACT

Introduction: Eye movement disorders are an important indicator for the diagnosis of certain neurodegenerative diseases. Electrooculography is the most widespread technique for measuring such eye movements. During the performance of the eye test, patients may forge unwanted head movements that add disturbances to the electrooculographic signal, modifying its morphological characteristic and, therefore, changing certain diagnostic parameters.
Objective: To develop a method for the correction of the effect of the horizontal and angular head displacement by the electrooculographic signal.
Method: It is detailed the use of a mathematical model for the correction of two types of artificial electrooculographic signals with different horizontal head movements at the Universidad de Oriente, from March 2021 to December 2021.
Results: The behavior of the method used was evaluated qualitatively through its implementation in the signals generated artificially in MATLAB. Finally, the correction effects on the diagnostic parameters of the electrooculographic signal were characterized.
Conclusions: The implemented method proved its validity for specific cases, in which it is possible to eliminate the errors caused by head displacement in two types of signals. The correction minimizes the error introduced in the uncorrected electrooculographic signal amplitude and keeps unchanged the other diagnostic parameters in absence of further analyses.


REFERENCES

  1. Casamento-Moran A, Yacoubi B., Wilkes BJ, Hess CW, Foote KD, Okun MS, Christou, EA. Quantitative separation of tremor and ataxia in essential tremor. Ann Neurol. 2020; 88(2): 375-387. DOI: https://doi.org/10.1002/ana.257811.

  2. Agarwal S, Singh V, Rani A, Mittal AP. Hardware efficient denoising system for real EOG signal processing. J Intell Fuzzy Syst. 2017; 32(4):2857-62. DOI: http://dx.doi.org/10.3233/JIFS-1692282.

  3. Stern JA, Brown TB, Wang L, Russo MB. Eye and head movements in the acquisition of visual information. Psychologia. 2005; 48(2):133-45.

  4. Fuller JH. Head movement propensity. Exp Brain Res. 1992; 92(1):152-64. DOI: https://doi.org/10.1007/bf002303914.

  5. Khasnobish A, Chakravarty K, Chatterjee D, Sinha A. Wavelet based head movement artifact removal from electrooculography signals. 2017 Proc. En: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. IEEE; 2017. Disponible en: https://ieeexplore.ieee.org/document/7952303/5.

  6. Pérez Guzmán RE, Céspedes Pérez A, García Bermúdez RV, Pérez Céspedes A. Estimulador visual y auditivo para pruebas clínicas de electrooculografía basado en la plataforma Arduino. Rev Cubana Cienc Inform. 2017; 11(3):77-91.

  7. López A, Ferrero F, Villar JR, Postolache O. High-Performance Analog Front-End (AFE) for EOG Systems. Electronics. 2020; 9(6):970. DOI: https://doi.org/10.3390/electronics90609707.

  8. Rodríguez-Labrada R, Velázquez-Pérez L, Auburger G, Ziemann U, Canales-Ochoa N, Medrano-Montero J, et al. Spinocerebellar ataxia type 2: measures of saccade changes improve power for clinical trials. Mov Disorders. 2016; 31(4):570-8. DOI: https://doi.org/10.1002/mds.265328.

  9. Sánchez FH, Romaguera TV, Seisdedos CRV. Sistema de estimulación y registro del movimiento ocular con el empleo de la videoculografía infrarroja. MEDISAN [Internet]. 2020 [citado 23/02/2022]; 24(3):515-28. Disponible en: http://scielo.sld.cu/pdf/san/v24n3/1029-3019-san-24-03-515.pdf9.

  10. Benitez Fernández A, Dávila Galiana RB, Socarrás Hernández BN, Rodríguez JMH, Seisdedos CRV. Generador de estímulos visuales para el análisis de movimientos oculares usando el sistema de medición biomédica SMB-EV(r). En: XVIII Convención y Feria Informática 2020, VII Simposio Internacional de Electrónica: Diseño, Aplicaciones, Técnicas Avanzadas y Retos Actuales. La Habana; 2020. Cuba; 2020.

  11. Fadraga-Acosta Y, Vázquez-Seisdedos CR, Valdés-Pérez FE. Herramienta para el Análisis de Movimientos Oculares Sacádicos. En: V Latin American Congress on Biomedical Engineering CLAIB, La Habana; 2011 May 16-21. La Habana: CLAIB; 2011.

  12. Becerra-García RA, García-Bermúdez RV, Joya-Caparrós G, Fernández-Higuera A, Velázquez-Rodríguez C, Velázquez-Mariño M, et al. Data mining process for identification of non-spontaneous saccadic movements in clinical electrooculography. Neurocomputing [Internet]. 2017 [citado 23/02/2022]; 250:28-36. DOI: https://doi.org/10.1016/j.neucom.2016.10.07712.

  13. Vázquez-Seisdedos CR, Fadraga-Acosta Y, Valdés-Pérez FE. Delineación de Movimientos Oculares Sacádicos: Desempeño en Presencia de Ruido. En: V Latin American Congress on Biomedical Engineering CLAIB, Habana, 2011 May 16-21. La Habana: CLAIB; 2011.




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RIC. 2022;101