Preliminary Study On Visually Induced Motion Sickness Evaluation In Virtual Reality

In recent years,virtual reality(VR)technology has developed rapidly and has been applied in many fields.VR technology creates the virtual environment through a head-mounted display(HMD)or large projection screen.VR can provide users with rich three-dimensional information,which brings people a strong sense of stereo and immersion.However,visually induced motion sickness(VIMS,also called VR motion sickness)may occur when a person immerses into the VR environment created by these devices.VIMS is a motion-sickness-like disorder,which is often induced when a person is exposed to visual and proprioceptive motions that are decoupled.A person with VIMS always suffers from headaches,stomach awareness,nausea,vomiting,sweating,fatigue,and even disorientation,which may cause safety and health issues for current VR platforms.Therefore,VIMS has been one of the major hurdles to overcome for virtual reality(VR)applications.It is of great significance to carry out this research.The purpose of this dissertation is to analyse the relationship between the physiological data,including blood pressure(BP),pulse rate(PR),blink rate(BR)and jaw clench rate(JCR)and subjective visually induced motion sickness level(VIMSL),to find the candidate markers for VIMS evaluation,through the VR-based vehicle driving simulator(VDS)experiment.In this dissertation,VR-based vehicle driving simulator was used to induce VIMS symptoms,and the subjective and objective data of subjects were collected throughout the experiment.The subjective and objective methods were combined to evaluate the VIMS.Firstly,the physiological data were preprocessed.Then they were divided into non-VIMS and VIMS state according to the VIMSL.Finally,the preprocessed physiological data were comparatively analyzed based on different states,including(1)marker analysis for single physiological data(BP and PR)in the time domain and frequency domain;(2)marker analysis for multiple physiological data.The markers include the characteristic parameters of "BP+PR",correlation of BP and PR in the time domain and coherence of BP and PR in the frequency domain;(3)marker analysis of BR and JCR.Our studies suggest that:?For single physiological data,there were significant differences in the following markers between non-VIMS state and VIMS state(P < 0.05): standard deviation of PSD of systolic pressure and standard deviation of PSD of pulse rate.?For multiple physiological data,there were significant differences in the following markers between non-VIMS state and VIMS state(P < 0.05):1)maximum cross-correlation coefficient between systolic pressure and pulse rate2)maximum cross-correlation coefficient between diastolic pressure and pulse rate3)mean value of maximum cross-correlation coefficient between systolic pressure and pulse rate4)mean value of maximum cross-correlation coefficient between diastolic pressure and pulse rate5)coherence coefficient between systolic pressure and pulse rate6)mean value of coherence coefficient between systolic pressure and pulse rate7)standard deviations of coherence coefficient between systolic pressure and pulse rate?There were significant differences in BR between non-VIMS state and VIMS state(P < 0.05).?There were individual differences in physiological data of VIMS for different subjects.For the same subject,there were also individual differences in repeated experiments;with the increase of the number of experiments,VIMS tolerance of some subjects might increase.The results above indicate that blood pressure,pulse rate,and blink rate are associated with VIMS,and the markers mentioned above may be used as the candidate markers for VIMS evaluation.The results of this dissertation can provide the basis for evaluation and reduction of VIMS in virtual reality;so as to promote the applications of VR technology.