Nobuyuki Nishiuchi – Abstract

Title:

Machine Learning-based User Experience Evaluation using Biological Data

 

Presenter:

Professor Nobuyuki Nishiuchi,

Department of Computer Science, Faculty of Systems Design,

Tokyo Metropolitan University, Tokyo, Japan.

 

Abstract:

User experience (UX) have been important factors in the design for products, systems, and services. The evaluation methods used to assess the current UX factors are interviews and questionnaires. These traditional methods are based on the subjective approach; therefore, certain limitations are encountered – they are time-consuming, burdensome for users, and require significant human effort for interpretation. It has been challenging to gather data on UX for a long duration to understand user feedback.

 

To address these challenges, our research team has been studying objective and machine learning (ML)-based UX evaluation methods using biological dada, such as eye movement, facial expression, or body movement during the operations of the target products or services, including virtual reality applications. By leveraging ML, we aim to predict the user’s state, providing valuable insights for the evaluation and improvement of products or services. During this lecture, I will present the basic idea and specific experiments conducted using the proposed method.