Motor styles in action: Developing a computational framework for operationalization of motor distances.

Abstract

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.