Evaluating Photoplethysmogram as a Real-Time Cognitive Load Assessment during Game Playing

ABSTRACT

Accurate evaluation for user experience during computer game playing is very important in optimizing game design to improve the gaming experience. When evaluating user experiences, the concept of cognitive load is crucial for dynamically responding to game players’ mental status. In our former studies, the photoplethysmogram (PPG)-based Stress-Induced Vascular Response Index (sVRI) shows better sensitivity and reliability in measuring cognitive loads compared with heart-rate variation, blood pressure, and galvanic skin response. In this study, we use memory matrixes and Pop Cap’s tower defense game Plants vs. Zombies as cognitive tasks and use sVRI to assess players’ cognitive load dynamically during the real-time computer games. Evaluations on cognitive tasks verified the usability of sVRI in comparison with other indexes derived from PPG, such as heartbeat interval, area under curve, digital pulse amplitude, reflection index, and inflection point area ratio. Our findings indicate the potential of sVRI for assessing game players’ mental workload in real time.

Acknowledgments

We thank all the volunteers for their participation in our experiment and our experimenter Jianwei Zhang of experiment. We thank all the anonymous reviewers for their insightful comments and helpful suggestions for improving the initial draft of this manuscript.

Additional information

Funding

This work was supported by the Chinese National Key Research and Development Program [Grant No. 2017YFB0403404] and China Scholarship Council.

Notes on contributors

Xiao Zhang

Xiao Zhang received her Bachelor degree from Xidian University in 2014. She is currently a Ph.D. candidate with Department of Aerospace, Tsinghua University. Her research interests include pervasive computing, human–computer interaction, and computer vision.

Yongqiang Lyu

Yongqiang Lyu is currently a research associate of Research Institute of Information Technology, Tsinghua University. His research interests are security and usability of software–hardware/human–computer fusion systems, including hardware/network security and psycho-physiological assessment in human–computer interaction.

Xin Hu

Xin Hu is a senior undergraduate student majoring in Automation Engineering in Beijing University of Posts and Telecommunications. In October 2016, she joined the Network and Big Data Technology R&D Center of Tsinghua University as an Intern research fellow under the guidance of Prof. Yongqiang Lyu.

Ziyue Hu

Ziyue Hu is a senior undergraduate student majoring in Computer Science in Beijing University of Posts and Telecommunications. In April 2015, she joined the Network and Big Data Technology R&D Center of Tsinghua University as an Intern research fellow under the guidance of Prof. Yongqiang Lyu.

Yuanchun Shi

Yuanchun Shi is a professor of Department of Computer Science, the director of HCI & Media Integration Institute, Tsinghua University, and the director of Pervasive Computing Division of Tsinghua National Lab of Information Science and Technology. Her research interests include pervasive computing, human–computer interaction, distributed multimedia processing, and e-learning.

Hao Yin

Hao Yin is currently a research fellow in the Department of Computer Science and Technology, Tsinghua University. He is serving as chief scientist of Beijing Blue I.T. Technologies Co., Ltd. (ChinaCache), and director of the Tsinghua-ChinaCache Content Delivery Network Research Institute.