Usability Evaluation of Facial Emotion Recognition System


  • Kek Kai Ting Universiti Utara Malaysia
  • Noradila Nordin UUM


biometric, emotion recognition, identification


Face detection can identify and verify faces from images, videos, and other forms of face graphics. It tracks facial features, contours, and textures to analyze individuals’ unique biometrics and demographic details. Humans can express thousands of facial expressions, all of which vary in intensity, complexity, and meaning. Facial emotion recognition is a type of facial recognition system, and it is a technology that can detect human emotions through facial expressions. In the past few decades, real-time facial emotion recognition systems have been an active area of research. Due to the Covid-19 pandemic, most learning methods have changed from physical learning to online learning. Therefore, it is difficult for teachers to understand students' emotions in the teaching process, and some emotions constitute obstacles to students' classroom participation and test scores. Nowadays, as students, we also know that it is difficult for lecturers to capture the emotions of students through the online learning mode and change the learning mode according to the emotions of the students. As a result, most of the time students feel bored and cannot concentrate in class because they are not interested in the lecturer's learning mode. Therefore, the learning materials prepared by the lecturer will become invalid due to the inattention of students in class. In this project, we will use a facial landmark to detect real-time facial expressions via a webcam. The purpose of the project is to establish a facial emotion recognition system to recognize the emotions of students in class and view the report of the emotions of the students. The result of this project is to allow lecturers and students to better understand their emotions during class. By doing so, we can recognize emotions and classify learners’ participation and interest in topics that are mapped as feedback to the lecturer to improve the learner’s experience. In addition, after students use the system, there will be emotional results. For example, students can learn about their emotional changes during class hours.


Author Biographies

  • Kek Kai Ting, Universiti Utara Malaysia



  • Noradila Nordin, UUM






How to Cite

Ting, K. K. ., & Nordin, N. . (2023). Usability Evaluation of Facial Emotion Recognition System . Multidisciplinary Applied Research and Innovation, 4(1), 54-58.