Correlations between SSQ Scores and ECG Data during Virtual Reality Walking by Display Type

Author:

Choi Mi-Hyun12ORCID,Kang Kyu-Young1,Lee Tae-Hoon1,Choi Jin-Seung12

Affiliation:

1. Department of Biomedical Engineering, School of ICT Convergence Engineering, College of Science & Technology, Konkuk University, Chungju 27478, Republic of Korea

2. Research Institute of Biomedical Engineering, Konkuk University, Chungju 27478, Republic of Korea

Abstract

To encourage the application of virtual reality (VR) in physical rehabilitation, this study analyzed the occurrence of motion sickness when walking on a treadmill in virtual straight paths presented on two types of displays (screen and head-mounted displays (HMDs)) at a constant speed of 3.6 km/h. The simulator sickness questionnaire (SSQ) scores, which indicate motion sickness, were collected from the participants. In addition, the heart rate (HR) and heart rate variability (HRV; RMSSD and LF/HF ratio) were measured from electrocardiogram data. The correlations between the SSQ scores and HR and HRV were examined to identify a reliable variable for evaluating motion sickness. The SSQ scores were used to classify the data into the motion-sickness and no-motion-sickness groups. The data were classified into the motion-sickness group if a minimum difference of 15 points existed between the walking and baseline phases when using the screen and HMD; otherwise, the data were classified into the no-motion-sickness group. The HR and LF/HF ratio were higher, whereas the RMSSD was lower in the motion-sickness group. Moreover, within the motion-sickness group, the reduction in RMSSD and increase in HR and LF/HF ratio were greater with the HMD than with the screen. Regression analysis was performed on the HR, HRV, and SSQ scores to differentiate between the motion-sickness and no-motion-sickness groups. The regression analysis results showed a high negative correlation between the SSQ score and RMSSD. The results of this study can assist in controlling the occurrence of motion sickness in VR-based applications.

Funder

Konkuk University

Publisher

MDPI AG

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