Deng Linchuan, Luo Jie, Lyu Yueling, Song Rong
Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Sun Yat-Sen University, Guangzhou 510006, China.
Shenzhen Research Institute, Sun Yat-Sen University, Shenzhen 518057, China.
Entropy (Basel). 2021 Jan 15;23(1):111. doi: 10.3390/e23010111.
Visual-motor tracking movement is a common and essential behavior in daily life. However, the contribution of future information to visual-motor tracking performance is not well understood in current research. In this study, the visual-motor tracking performance with and without future-trajectories was compared. Meanwhile, three task demands were designed to investigate their impact. Eighteen healthy young participants were recruited and instructed to track a target on a screen by stretching/flexing their elbow joint. The kinematic signals (elbow joint angle) and surface electromyographic (EMG) signals of biceps and triceps were recorded. The normalized integrated jerk (NIJ) and fuzzy approximate entropy (fApEn) of the joint trajectories, as well as the multiscale fuzzy approximate entropy (MSfApEn) values of the EMG signals, were calculated. Accordingly, the NIJ values with the future-trajectory were significantly lower than those without future-trajectory (-value < 0.01). The smoother movement with future-trajectories might be related to the increasing reliance of feedforward control. When the task demands increased, the fApEn values of joint trajectories increased significantly, as well as the MSfApEn of EMG signals (-value < 0.05). These findings enrich our understanding about visual-motor control with future information.
视觉运动跟踪是日常生活中一种常见且重要的行为。然而，目前的研究对未来信息对视觉运动跟踪性能的贡献了解不足。在本研究中，比较了有和没有未来轨迹时的视觉运动跟踪性能。同时，设计了三种任务需求来研究它们的影响。招募了18名健康的年轻参与者，并指导他们通过伸展/弯曲肘关节在屏幕上跟踪目标。记录了肱二头肌和肱三头肌的运动学信号（肘关节角度）和表面肌电图（EMG）信号。计算了关节轨迹的归一化积分急动度（NIJ）和模糊近似熵（fApEn），以及EMG信号的多尺度模糊近似熵（MSfApEn）值。因此，有未来轨迹时的NIJ值显著低于没有未来轨迹时的NIJ值（p值<0.01）。有未来轨迹时更平滑的运动可能与前馈控制的依赖增加有关。当任务需求增加时，关节轨迹的fApEn值显著增加，EMG信号的MSfApEn也显著增加（p值<0.05）。这些发现丰富了我们对带有未来信息的视觉运动控制的理解。
