Abstract
AbstractBased on sensory conflict theory, motion sickness is strongly related to the information processing capacity or resources of the brain to cope with the multi-sensory stimuli experienced by watching virtual reality (VR) content. The purpose of this research was to develop a method of measuring motion sickness using the heart-evoked potential (HEP) phenomenon and propose new indicators for evaluating motion sickness. Twenty-eight undergraduate volunteers of both genders (14 females) participated in this study by watching VR content on both 2D and head-mounted devices (HMD) for 15 min. The responses of HEP measures such as alpha power, latency, and amplitude of first and second HEP components were compared using paired t-tests and ANCOVA. This study confirmed that motion sickness leads to a decline in cognitive processing, as demonstrated by increasing in alpha power of HEP. Also, the proposed indicators such as latency and amplitude of the HEP waveform showed significant differences during the experience of motion sickness and exhibited high correlations with alpha power measures. Latencies of the first HEP component, in particular, are recommended as better quantitative evaluators of motion sickness than other measures, following the multitrait-multimethod matrix. The proposed model for motion sickness was implemented in a support vector machine with a radial basis function kernel, and validated on twenty new participants. The accuracy, F1 score, precision, recall, and area under the curve (AUC) of the motion-sickness classification results were 0.875, 0.865, 0.941, 0.8, and 0.962, respectively.
Funder
Institute of Information & communications Technology Planning & Evaluation
Electronics and Telecommunications Research Institute
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Human-Computer Interaction,Software
Cited by
12 articles.
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