Luo Haizhen, Wang Xiaoyun, Fan Mengying, Deng Lingyun, Jian Chuyao, Wei Miaoluan, Luo Jie
Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Engineering, Sun Yat-sen University, Guangzhou, China.
Guangdong Work Injury Rehabilitation Center, Guangzhou, China.
Front Neurol. 2018 Feb 8;9:48. doi: 10.3389/fneur.2018.00048. eCollection 2018.
Visual input could benefit balance control or increase postural sway, and it is far from fully understanding the effect of visual stimuli on postural stability and its underlying mechanism. In this study, the effect of different visual inputs on stability and complexity of postural control was examined by analyzing the mean velocity (MV), SD, and fuzzy approximate entropy (fApEn) of the center of pressure (COP) signal during quiet upright standing. We designed five visual exposure conditions: eyes-closed, eyes-open (EO), and three virtual reality (VR) scenes (VR1-VR3). The VR scenes were a limited field view of an optokinetic drum rotating around yaw (VR1), pitch (VR2), and roll (VR3) axes, respectively. Sixteen healthy subjects were involved in the experiment, and their COP trajectories were assessed from the force plate data. MV, SD, and fApEn of the COP in anterior-posterior (AP), medial-lateral (ML) directions were calculated. Two-way analysis of variance with repeated measures was conducted to test the statistical significance. We found that all the three parameters obtained the lowest values in the EO condition, and highest in the VR3 condition. We also found that the active neuromuscular intervention, indicated by fApEn, in response to changing the visual exposure conditions were more adaptive in AP direction, and the stability, indicated by SD, in ML direction reflected the changes of visual scenes. MV was found to capture both instability and active neuromuscular control dynamics. It seemed that the three parameters provided compensatory information about the postural control in the immersive virtual environment.
视觉输入可能有益于平衡控制或增加姿势晃动,而目前对于视觉刺激对姿势稳定性的影响及其潜在机制的理解还远远不够全面。在本研究中,通过分析安静直立站立期间压力中心(COP)信号的平均速度(MV)、标准差(SD)和模糊近似熵(fApEn),研究了不同视觉输入对姿势控制稳定性和复杂性的影响。我们设计了五种视觉暴露条件:闭眼、睁眼(EO)以及三个虚拟现实(VR)场景(VR1 - VR3)。VR场景分别是围绕偏航轴(VR1)、俯仰轴(VR2)和滚动轴(VR3)旋转的视动鼓的有限视野。16名健康受试者参与了实验,并根据测力台数据评估他们的COP轨迹。计算了COP在前后(AP)、内外侧(ML)方向上的MV、SD和fApEn。采用重复测量的双向方差分析来检验统计学意义。我们发现,这三个参数在EO条件下的值最低,在VR3条件下的值最高。我们还发现,由fApEn表示的主动神经肌肉干预,在响应视觉暴露条件变化时,在AP方向上更具适应性,而由SD表示的ML方向上的稳定性反映了视觉场景的变化。发现MV捕捉到了不稳定性和主动神经肌肉控制动态。似乎这三个参数提供了关于沉浸式虚拟环境中姿势控制的补偿信息。