目的 针对虚拟运动机制所带来的晕动症状，提出基于眼动的评估方法。方法 选用视线追踪回溯式有声思维的方式，在受试者体验常见虚拟运动时，实时采集眼动数据并在实验前、后完成两次量表评价，采集的11项参数指标用于数据分析。采用熵权法改进EFA进行综合评价，首先提取因子以简化变量数目，再在熵值赋权法下校正成分因子权重。结果 提取后再赋权的成分变量具有现实意义，得到的虚拟现实晕动症因子评估模型，其预测值与实际值配对t检验结果大于0.05，具有有效性。结论 模型优势在于基于眼动追踪技术，以客观可采集的眼动数据描述主观晕动，提出眼动技术结合VR，采集数据作为反馈信息，实时改进虚拟现实运动机制的思路，以缓解受试者的晕动症状。

This paper aims to propose an evaluation method based on eye movement for motion sickness caused by virtual reality movement mechanism. When subjects experienced in the experiment, eye-movement data were collected in real time under the usability testing method called eye-tracking retrospective think-aloud. Subjects need to complete evaluation scales twice before and after the experiment and then 11 parameters were collected. To describe more clearly, the entropy weight method was used to improve the exploratory factor analysis to comprehensive evaluate. This method firstly extracted factors to simplify the number of variables and then corrected the weight of component factors by entropy evaluation. This new component variables had highly practical significance, and we obtained the virtual reality motion sickness evaluation model. The paired t-test results were greater than 0.05, which is effective. Based on the eye-movement tracking technology, the subjective motion can be described by objective eye movement data. Combined with VR, eye-tracking technology can collect data as feedback information to improve virtual reality motion mechanism. Also, it can further alleviate virtual motion sickness symptoms of subjects.