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A Review on Applications of Soft Computing Techniques in Neuroergonomics During the Last Decade

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Advances in Neuroergonomics and Cognitive Engineering (AHFE 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1201))

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Abstract

Soft computing (SC) methods play an important role in addressing the different types of problems and offering potential alternatives at the present time. Such methods have also been implemented in the context of neuroergonomics, because of the success of SC strategies, to reliably evaluate the mental workload and achieve better results than traditional approaches. Nevertheless, these applications are still limited. This paper surveys SC techniques using classification and literature review of articles for the last decade (2009–2019) to explore how various SC methodologies have been developed during this period. The purpose of this paper is to summarize the results through a systemic review of current research papers on the use of SC methodologies in neuroergonomics. Throughout the course of this study, it has been observed that SC techniques have been applied to most traditional areas of neuroergonomics research, and research in neuroergonomics has grown in recent years.

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Gazi University, Ankara, Turkey

    Erman Çakıt

  2. Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL, 32816-2993, USA

    Waldemar Karwowski

Authors
  1. Erman Çakıt
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  2. Waldemar Karwowski
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Correspondence to Erman Çakıt .

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Editors and Affiliations

  1. Drexel University, Philadelphia, PA, USA

    Hasan Ayaz

  2. National University of Sciences and Tech (NUST), School of Mech and Manufacturing Eng (SMME), Islamabad, Pakistan

    Umer Asgher

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Çakıt, E., Karwowski, W. (2021). A Review on Applications of Soft Computing Techniques in Neuroergonomics During the Last Decade. In: Ayaz, H., Asgher, U. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1201. Springer, Cham. https://doi.org/10.1007/978-3-030-51041-1_6

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