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Revista ELECTRO

Vol. 40 – Año 2018

Artículo

TÍTULO

Reconocimiento de Estados Emocionales para Su Aplicación en Ergonomía

AUTORES

Rodríguez-Aguiñaga A., López-Ramírez A., Herrera-Arellano J.L., González-Gutiérrez R.

RESUMEN

Este trabajo presenta una propuesta de aplicación del reconocimiento de patrones enfocado en la identificación de emociones mediante los rasgos faciales e implementarlos en el análisis de un ambiente laboral en tiempo real. Se aborda un problema de la ergonomía cognitiva, utilizando un sistema de reconocimiento para solventar los problemas que se asocian a las limitaciones técnicas o fisiológicas de realizar inspecciones y/o controles de la ergonomía por largos periodos de tiempo y sin interrupciones. El modelo si bien se encuentra completamente desarrollado aún se encuentra en fase de implementación, por lo que en este trabajo se reporta la implementación del algoritmo y las especific aciones técnicas del sistema.

Palabras Clave: Cognitiva, emociones, reconocimiento, ergonomía

ABSTRACT

This paper presents a proposal of application of the recognition of patterns focused on the identification of emotions through facial features and implement them in the analysis of a work environment in real time. It addresses a problem of cognitive ergonomics, using a recognition system to solve problems that are associated with technical or physiological limitations of conducting inspections and / or ergonomics controls for long periods of time and without interruptions. Although the model is fully developed, it is still in the implementation phase, which is why this paper reports on the implementation of the algorithm and the technical specificatio ns of the system.

Keywords: Cognitive, emotions, recognition, ergonomics

REFERENCIAS

[1] E. Pakdamanian, N. Shiyamsunthar and D. Claudio, "Simulating the effect of workers' mood on the productivity of assembly lines," 2016 Winter Simulation Conference (WSC), Washington, DC, 2016, pp. 3440-3451. doi: 10.1109/WSC.2016.7822374.
[2] I. Tajri and A. Cherkaoui, "Modeling the complexity of the relationship (Lean, company, employee and cognitive ergonomics) case of Moroccan SMEs," 2015 International Conference on Industrial Engine ering and Systems Management (IESM), Seville, 2015, pp. 1286-1295. doi: 10.1109/IESM.2015.7380318
[3] Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, A. D., Jeffrey Dean, Matthieu Devin, Sanjay Ghemawa t, I. G., Andrew Harp, Geoffrey Irving, Michael Isard, Rafal Jozefowicz, Y. J., Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, M. S., Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, J. S., … Yuan Yu, and X. Z. TensorFlow: Large-Scale Mach ine Learning on Heterogeneous Systems, 2015. Congr. Int. en Ing. Electrónica. Mem. ELECTRO, Vol. 40, pp. 1 92-198, Oct 201 8, Chihuahua, Chih. México http://electro.itchihuahua.edu.mx/memorias_electro/MemoriaElectro201 8.zip ISSN 1405-2172 198
[4] Yan, W.-J., Li, X., Wang, S.-J., Zhao, G., Liu, Y.-J., Chen, Y.-H., & Fu, X. “CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation.” PLoS ONE, 9(1), e86041. (2014). https://doi.org/10.1371/journal.pone.0086041
[5] Bradski, G. (1971). The OpenCV Library. Dr. Dobb’s Journal of Software Tools, 4. [Online].
[6] Ekman, P., & Friesen, W. V. “Constants across cu ltures in the face and emotions”, Journal of Personality and Social Psychology, 17(2), pp. 124 –129, 1971.
[7] Shreve M, Godavarthy S, Goldgof D, Sarkar S (2011) Macro-and micro-expression spotting in long videos using spatio-temporal strain. 11th Proc Int Conf Autom Face Gesture Recognit (FG2011). Santa Barbara, California IEEE. pp. 51 –56.
[8] Polikovsky S, Kameda Y, Ohta Y (2009) Facial micro-expressions recognition using high speed camera and 3D-gradient descriptor. 3rd Int Conf on Crime Detection and Prevention (ICDP 2009): IET. pp. 1 –6.
[9] Li X, Pfister T, Huang X, Zhao G, Pietikäinen M (2013) A Spontaneous Micro-expression Database: Inducement, Collection and Baseline. 10th Proc Int Conf Autom Face Gesture Recognit (FG20 13). Shanghai, China. DOI: https://doi.org/10.1109/FG.2013.6553717.
[10] Wolf, K. (2015). Measuring facial expression of emotion. Dialogues in clinical Neuroscience, 17(4), 457 –462.
[11] Russell, J. A. “A circumplex model of affect”, Journal of Personality and Social Psychology (Vol. 39, pp. 1161 –1178), 1980. https://doi.org/http://dx.doi.org/10.1037/h0077714
[12] S. Koelstra and M. Pantic. In Automatic Face & Gesture Recognition, 2008. FG'08. 8th IEEE International Conference on, 2008.
[13] Ekman, P., Friesen, W. V, O’Sullivan, M., Chan, A., Diacoyanni-Tarlatzis, I., Heider, K., … Tzavaras, A. “Universals and cultural diffe rences in the judgments of facial expressions of emotion”. Journal of Personality and Social Psychology (Vol. 4, pp. 712 –717), 1987. https://doi.org/http://dx.doi.org/10.1037/0022-3514.53.4.712
[14] Antonio Damaso, self comes to mind.,imago mundi, ISBN: 978-84-233-4305-8,2010

CITAR COMO:

Rodríguez-Aguiñaga A., López-Ramírez A., Herrera-Arellano J.L., González-Gutiérrez R., "Reconocimiento de Estados Emocionales para Su Aplicación en Ergonomía", Revista ELECTRO, Vol. 40, 2018, pp. 192-1.

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