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Estimation of Mental Fatigue During EEG Based Motor Imagery

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Intelligent Human Computer Interaction (IHCI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10127))

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Abstract

Mental Fatigue is a cognitive state which is an outcome of labour or protracted exercise finally leading to downgrading of mental performance. This leads to reduction in efficiency and disinclination of motor skills. Analysis of mental fatigue thus becomes momentous for assessing one’s capability. The aim here is to analyse whether motor imagery is fatiguing. There are many parameters to evaluate fatigue. This study analyses parietal alpha and frontal theta in motor imagery tasks. Decrement of arousal level, working memory and information encoding have been proven to be associated with increased theta power. Increase in alpha power indicates increase in mental effort to maintain vigilance level. When a person experiences fatigue, their concentration, attention, focus and vigilance level decreases for which they need to put more attention which leads to increase in alpha power. We exploit these EEG oscillatory rhythm fluctuations to model EEG-fatigue relationships. A statistical classifier is used to model EEG-fatigue relationship accurately. With Kernel Partial Least Square output we track the growth of mental fatigue with time.

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Notes

  1. 1.

    http://www.bbci.de/competition/iv/desc_2a.pdf.

  2. 2.

    The Matlab code for KPLS has been taken from Roman Rosipal’s homepage: http://aiolos.um.savba.sk/~roman/soft_data.html.

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Acknowledgement

Financial support from MHRD as Centre of Excellence on Machine Learning Research and Big Data Analysis is acknowledged. Many thanks to Dr. Roman Rosipal and Dr. Leonardo de Trezo for providing us with their much needed help. Assistance received under DST-UKEIRI Project: DST/INT/UK/P-91/2014 is gratefully acknowledged.

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Authors and Affiliations

  1. Biomimetic and Cognitive Robotics Lab, Tezpur University, Tezpur, India

    Upasana Talukdar & Shyamanta M. Hazarika

Authors
  1. Upasana Talukdar
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  2. Shyamanta M. Hazarika
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Corresponding author

Correspondence to Upasana Talukdar .

Editor information

Editors and Affiliations

  1. IIT Kharagpur , Kharagpur, India

    Anupam Basu

  2. IIT Madras , Chennai, India

    Sukhendu Das

  3. Telecom SudParis , Evry, France

    Patrick Horain

  4. IIT Guwahati , Guwahati, India

    Samit Bhattacharya

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Talukdar, U., Hazarika, S.M. (2017). Estimation of Mental Fatigue During EEG Based Motor Imagery. In: Basu, A., Das, S., Horain, P., Bhattacharya, S. (eds) Intelligent Human Computer Interaction. IHCI 2016. Lecture Notes in Computer Science(), vol 10127. Springer, Cham. https://doi.org/10.1007/978-3-319-52503-7_10

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  • DOI: https://doi.org/10.1007/978-3-319-52503-7_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52502-0

  • Online ISBN: 978-3-319-52503-7

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