论文标题
运动疾病的计算模型描述了学习外源运动动力学的影响
Computational Model of Motion Sickness Describing the Effects of Learning Exogenous Motion Dynamics
论文作者
论文摘要
用于估计运动疾病的现有计算模型无法描述运动模式的可预测性会影响运动病的事实。因此，本研究提出了一个计算模型，以描述动力学的可预测性或运动刺激模式对运动疾病的影响。在拟议的模型中，使用递归高斯过程回归的子模型代表在线学习的人类特征和运动动力学的未来预测，与基于观察者理论的传统运动疾病模型相结合。进行了一个模拟实验，其中提出的模型预测了由900 s的水平运动引起的运动疾病。该运动由9 m的来回运动模式组成，并停止。关于运动条件，运动的方向和时机如下：a）可预测的运动（M_P）：运动的方向和停顿的持续时间设置为8 s； b）运动方向（m_du）的运动：暂停持续时间如（p）中的固定，但运动方向是随机确定的； c）具有不可预测的时序（M_TU）的运动：运动方向如（M_P）固定，但暂停持续时间是从4到12 s随机选择的。使用所提出的模型获得的结果表明，（M_P）的预测运动疾病发生率小于（m_du）和（m_tu）的运动率。这种趋势与先前的实验研究中观察到的疾病模式一致，在该研究中，人类参与者受到与模拟中使用的运动条件相似的运动条件。此外，在使用常规模型时，在不同条件下的预测运动疾病发生中没有发现显着差异。
The existing computational models used to estimate motion sickness are incapable of describing the fact that the predictability of motion patterns affects motion sickness. Therefore, the present study proposes a computational model to describe the effect of the predictability of dynamics or the pattern of motion stimuli on motion sickness. In the proposed model, a submodel, in which a recursive Gaussian process regression is used to represent human features of online learning and future prediction of motion dynamics, is combined with a conventional model of motion sickness based on an observer theory. A simulation experiment was conducted in which the proposed model predicted motion sickness caused by a 900 s horizontal movement. The movement was composed of a 9 m repetitive back-and-forth movement pattern with a pause. Regarding the motion condition, the direction and timing of the motion were varied as follows: a) Predictable motion (M_P): the direction of the motion and duration of the pause were set to 8 s; b) Motion with unpredicted direction (M_dU): the pause duration was fixed as in (P), but the motion direction was randomly determined; c) Motion with unpredicted timing (M_tU): the motion direction was fixed as in (M_P), but the pause duration was randomly selected from 4 to 12 s. The results obtained using the proposed model demonstrated that the predicted motion sickness incidence for (M_P) was smaller than those for (M_dU) and (M_tU). This tendency agrees with the sickness patterns observed in a previous experimental study in which the human participants were subject to motion conditions similar to those used in our simulations. Moreover, no significant differences were found in the predicted motion sickness incidences at different conditions when the conventional model was used.
