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Predictions of Age and Mood Based on Changes in Saccades Parameters

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Man-Machine Interactions 6 (ICMMI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1061 ))

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Abstract

We have measured saccades of 12 subjects in age below 30 (younger adults) and over 60 (older adults) during musical sessions with energetic and relaxing music. We wanted to check if saccade parameters are sensitive to emotions caused by music and if so, check if there ability to distinguish and classify those parameters to one of defined group of Age (young/old) or group of Mood (energetic/relaxed) induced by the music. We used combination of different types of filters and classifiers from WEKA [5] in search of possible correlations between saccade parameters and characteristics of respondents. Results showed statistical changes between age groups in the latency (23.6% of difference) and in the pupils size (16,6% of difference), both found significant (P < 0.0001). In case of Mood, results showed changes in the group of younger adults in the latency (P = 0.4532), the amplitude (P = 0.0001) and for the average velocity (P = 0.0048). Prediction of age group showed the accuracy of 91.4%, in case of Mood groups 97%. For both types of groups, best predictions were obtained by the Random Forest and the Multilayer Perceptron.

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Acknowledgements

This work was partly supported by projects Dec-2011/03/B/ST6/03816 from the Polish National Science Centre.

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Authors and Affiliations

  1. Polish-Japanese Academy of Information Technology, 02-008, Warsaw, Poland

    Albert Sledzianowski

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  1. Albert Sledzianowski
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Correspondence to Albert Sledzianowski .

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Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland

    Tadeusz Czachórski

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Sebastian Deorowicz

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Katarzyna Harężlak

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Piotrowska

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Sledzianowski, A. (2020). Predictions of Age and Mood Based on Changes in Saccades Parameters. In: Gruca, A., Czachórski, T., Deorowicz, S., Harężlak, K., Piotrowska, A. (eds) Man-Machine Interactions 6. ICMMI 2019. Advances in Intelligent Systems and Computing, vol 1061 . Springer, Cham. https://doi.org/10.1007/978-3-030-31964-9_19

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