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A novel method for the evaluation of fashion product design based on data mining

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Abstract

It is difficult to qualitatively evaluate the design effects of product appearance. Electroencephalograph (EEG) and eye-tracking data can serve as reflection of the subconscious activities of human beings. The application of advanced neuroscience technology in industrial operation management has become a new research hot spot. This study uses EEG equipment and an eye-tracking device to record a subject’s brain activity and eye-gaze data, and then uses data mining methods to analyze the correlation between the two types of signals. The fuzzy theory is then applied to create a fuzzy comprehensive evaluation model. The neural attributes are used to quantify the factors affected by product appearance and evaluation indicators. We use women’s shirts as research subjects for a case study. The EEG Emotiv device and Tobii mobile eye-tracking glasses are used to record a subject’s brain activity and eye-gaze data in order to quantify the evaluation factors related to product appearance. This method not only scientifically evaluates the uniqueness of product appearance but also provides an objective reference for improving product appearance design.

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Authors and Affiliations

  1. Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200072, People’s Republic of China

    Bao-Rui Li

  2. School of Business, Plymouth University, Plymouth, UK

    Yi Wang

  3. Knowledge Discovery Laboratory, Norwegian University of Science and Technology, Trondheim, Norway

    Ke-Sheng Wang

Authors
  1. Bao-Rui Li
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  2. Yi Wang
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  3. Ke-Sheng Wang
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Correspondence to Yi Wang.

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Li, BR., Wang, Y. & Wang, KS. A novel method for the evaluation of fashion product design based on data mining. Adv. Manuf. 5, 370–376 (2017). https://doi.org/10.1007/s40436-017-0201-x

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  • DOI: https://doi.org/10.1007/s40436-017-0201-x

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