  Digital human models of motion sickness have been actively developed, among
which models based on subjective vertical conflict (SVC) theory are the most
actively studied. These models facilitate the prediction of motion sickness in
various scenarios such as riding in a car. Most SVC theory models predict the
motion sickness incidence (MSI), which is defined as the percentage of people
who would vomit with the given specific motion stimulus. However, no model has
been developed to describe milder forms of discomfort or specific symptoms of
motion sickness, even though predicting milder symptoms is important for
applications in automobiles and daily use vehicles. Therefore, the purpose of
this study was to build a computational model of symptom progression of
vestibular motion sickness based on SVC theory. We focused on a model of
vestibular motion sickness with six degrees-of-freedom (6DoF) head motions. The
model was developed by updating the output part of the state-of-the-art SVC
model, termed the 6DoF-SVC (IN1) model, from MSI to the MIsery SCale (MISC),
which is a subjective rating scale for symptom progression. We conducted an
experiment to measure the progression of motion sickness during a straight
fore-aft motion. It was demonstrated that our proposed method, with the
parameters of the output parts optimized by the experimental results, fits well
with the observed MISC.
