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Investigation of Psychological Evaluation and Estimation Method Using Skin Temperature of Lower Half of Face

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HCI International 2020 - Posters (HCII 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1224))

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Abstract

This study is aimed at establishing a mental workload (MWL) estimation method that can be used in work sites.

Advancements in information society have resulted in an increase in MWL mainly caused by using computers daily. Long-term excessive MWL can cause fatigue and lead to a drop in concentration and mental saturation. Therefore, it is important for workers to evaluate their MWL to prevent and reduce human errors and associated health hazards. We examine the correspondence between autonomic nervous activities and MWL using facial skin temperature with infrared thermography. Consequently, the ability to evaluate MWL according to the skin temperature of a face is shown.

In an actual environment, the forehead is often hidden by hair or wearing glasses. This hinders the measurement of the temperature of an entire face. This study focuses on the lower half of the face area. This is the area with less glass and hair effects. MWL was evaluated using the variance of the entire face, nose, and forehead in existing studies. However, detailed analysis of the temperature distribution information, such as the variance value of the nose only or the area other than the nose is scarce.

We examined the characteristics of the nose, cheeks, lips, and lower half of the face.

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Correspondence to Tota Mizuno .

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Mizuno, T., Mito, K., Itakura, N. (2020). Investigation of Psychological Evaluation and Estimation Method Using Skin Temperature of Lower Half of Face. In: Stephanidis, C., Antona, M. (eds) HCI International 2020 - Posters. HCII 2020. Communications in Computer and Information Science, vol 1224. Springer, Cham. https://doi.org/10.1007/978-3-030-50726-8_49

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  • DOI: https://doi.org/10.1007/978-3-030-50726-8_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50725-1

  • Online ISBN: 978-3-030-50726-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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