Jackson Kyle, Duric Zoran, Engdahl Susannah, Gerber Lynn
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:3166-3169. doi: 10.1109/EMBC44109.2020.9176492.
Haptic virtual environments have been used to assess cognitive and fine motor function. For tasks performed in physical environments, upper extremity movement is usually separated into reaching and object manipulation phases using fixed velocity thresholds. However, these thresholds can result in premature segmentation due to additional trajectory adjustments common in virtual environments. In this work, we address the issues of premature segmentation and the lack of a measure to characterize the spatial distribution of a trajectory while targeting an object. We propose a combined relative distance and velocity segmentation procedure and use principal component analysis (PCA) to capture the spatial distribution of the participant's targeting phase. Synthetic data and 3D motion data from twenty healthy adults were used to evaluate the methods with positive results. We found that these methods quantify motor skill improvement of healthy participants performing repeated trials of a haptic virtual environment task.
触觉虚拟环境已被用于评估认知和精细运动功能。对于在物理环境中执行的任务，通常使用固定速度阈值将上肢运动分为伸手和物体操作阶段。然而，由于虚拟环境中常见的额外轨迹调整，这些阈值可能导致过早分割。在这项工作中，我们解决了过早分割的问题以及在瞄准物体时缺乏表征轨迹空间分布的度量的问题。我们提出了一种结合相对距离和速度的分割程序，并使用主成分分析（PCA）来捕捉参与者瞄准阶段的空间分布。使用来自20名健康成年人的合成数据和3D运动数据对这些方法进行评估，结果是积极的。我们发现这些方法量化了健康参与者在执行触觉虚拟环境任务的重复试验时运动技能的提高。
