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Selection of Classifiers for Hand Gesture Recognition Using Analytic Hierarchy Process: A Systematic Literature Review

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Advances and Applications in Computer Science, Electronics and Industrial Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1307))

Abstract

This article presents a systematic study for the selection of classifiers for hand gesture recognition by electromyography signals. The selection of a classifier can be determined using an arbitrary search criterion or employing an Analytic Hierarchy Process (AHP). The classifiers are determined as alternatives, which for the study are K-Nearest Neighbors (KNN), Naïve Bayes (NB), Support Vector Machines (SVM), and Linear Discriminant Analysis (LDA). Each of these alternatives is selected through search criteria, which are average training accuracy, average testing accuracy, sampling fee, average acceptance rating, and scrap rating average. These criteria and alternatives allow through a systematic study and the AHP model to select each search factor of the analysis of the systematic mapping (SMS) quantitatively. The results determine the KNN and SVM classifiers as the most used for research projects in electromyography signal recognition (EMG).

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Acknowledgements

The Corporación Ecuatoriana para el Desarrollo de la Investigación y la Academia (CEDIA) for the development of the research project CEPRA-2019-13-Reconocimiento de Gestos.

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Authors and Affiliations

  1. Facultad de Ingeniería en Sistemas Electrónica e Industrial, Universidad Técnica de Ambato, Ambato, Ecuador

    Ruben Nogales, Freddy Benalcazar, Jaime Guilcapi & Javier Vargas

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  1. Ruben Nogales
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  2. Freddy Benalcazar
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  3. Jaime Guilcapi
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Correspondence to Ruben Nogales .

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Editors and Affiliations

  1. Universidad del País Vasco, Bilbao, Spain

    Marcelo V. García

  2. Universidad Técnica de Ambato, FISEI, Ambato, Ecuador

    Félix Fernández-Peña

  3. Universidad Técnica de Ambato, FISEI, Ambato, Ecuador

    Carlos Gordón-Gallegos

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Nogales, R., Benalcazar, F., Guilcapi, J., Vargas, J. (2021). Selection of Classifiers for Hand Gesture Recognition Using Analytic Hierarchy Process: A Systematic Literature Review. In: García, M.V., Fernández-Peña, F., Gordón-Gallegos, C. (eds) Advances and Applications in Computer Science, Electronics and Industrial Engineering. Advances in Intelligent Systems and Computing, vol 1307. Springer, Singapore. https://doi.org/10.1007/978-981-33-4565-2_17

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  • DOI: https://doi.org/10.1007/978-981-33-4565-2_17

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