Manuello Jordi, Maronati Camilla, Rocca Matilde, Guidotti Riccardo, Costa Tommaso, Cavallo Andrea
Move'N'Brains Lab, Department of Psychology, University of Turin, Via Verdi, 10, 10124, Turin, Italy.
FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy.
Behav Res Methods. 2024 Dec 11;57(1):13. doi: 10.3758/s13428-024-02530-0.
Aside from some common movement regularities, significant inter-individual and inter-trial variation within the same individual exists in motor system output. However, there is still a lack of a robust and widely adopted solution for quantifying the degree of similarity between movements. We therefore developed an innovative approach based on the Procrustes transformation to compute 'motor distance' between pairs of kinematic data. As a proof of concept, we tested this on a dataset of reach-to-grasp movements performed by 16 participants while acting with the same confederate. Using the information of wrist velocity, acceleration, and jerk, the proposed technique was able to correctly estimate smaller distances between movements performed by the confederate compared with those of participants. Moreover, the reconstructed pattern of inter-subject distances was consistent when computed either on precision grip prehension or whole hand prehension, suggesting its suitability for the investigation of 'motor styles'. The definition of a solid approach to 'motor distance' computation, therefore, opens the way to new research lines in the field of movement kinematics.
除了一些常见的运动规律外，运动系统输出在个体间以及同一个体的不同试验之间存在显著差异。然而，目前仍缺乏一种强大且被广泛采用的方法来量化运动之间的相似程度。因此，我们开发了一种基于普罗克汝斯忒斯变换的创新方法，用于计算成对运动学数据之间的“运动距离”。作为概念验证，我们在16名参与者与同一实验助手共同完成的伸手抓握运动数据集上对其进行了测试。利用手腕速度、加速度和加加速度信息，与参与者的运动相比，该技术能够正确估计实验助手所执行运动之间更小的距离。此外，当在精确抓握或全手抓握时计算，受试者间距离的重建模式是一致的，这表明它适用于“运动风格”的研究。因此，一种可靠的“运动距离”计算方法的定义为运动运动学领域的新研究方向开辟了道路。
