Welcome to the InfoSci Platform
Reference Hub4
Evaluation of a Computer Vision-Based System to Analyse Behavioral Changes in High School Classrooms

Evaluation of a Computer Vision-Based System to Analyse Behavioral Changes in High School Classrooms

Hyungsook Kim, David O'Sullivan, Ksenia Kolykhalova, Antonio Camurri, Yonghyun Park
Copyright: © 2021 |Volume: 17 |Issue: 4 |Pages: 12
ISSN: 1550-1876|EISSN: 1550-1337|EISBN13: 9781799859390|DOI: 10.4018/IJICTE.20211001.oa12
Cite Article Cite Article

MLA

Kim, Hyungsook, et al. "Evaluation of a Computer Vision-Based System to Analyse Behavioral Changes in High School Classrooms." IJICTE vol.17, no.4 2021: pp.1-12. http://doi.org/10.4018/IJICTE.20211001.oa12

APA

Kim, H., O'Sullivan, D., Kolykhalova, K., Camurri, A., & Park, Y. (2021). Evaluation of a Computer Vision-Based System to Analyse Behavioral Changes in High School Classrooms. International Journal of Information and Communication Technology Education (IJICTE), 17(4), 1-12. http://doi.org/10.4018/IJICTE.20211001.oa12

Chicago

Kim, Hyungsook, et al. "Evaluation of a Computer Vision-Based System to Analyse Behavioral Changes in High School Classrooms," International Journal of Information and Communication Technology Education (IJICTE) 17, no.4: 1-12. http://doi.org/10.4018/IJICTE.20211001.oa12

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The objectives of this study were to investigate the feasibility of applying computer vision techniques and to analyse changes in behaviour and movement of high school students during class. The study is performed over two phases. Phase one focuses on developing a feasible method to use computer vision-based techniques in high school classes and phase two focuses on the testing of aromatherapy to affect student’s movement. All camera data was processed and analysed by OpenPose, Matlab and EyesWeb. Movement features such as velocity, acceleration, and kinetic energy and postural variables, spinal extension and neck flexion were calculated. Results of phase one, shows significant differences in the overall segment velocity, acceleration, energy, and neck flexion. Similarly, the second phase shows significant differences in velocity, acceleration and jerk for the left shoulder and elbow joints of the group exposed to aroma. In conclusion, the results show the feasibility of using computer vision techniques to apply in a classroom setting.