Circle drawing and tracing dataset for evaluation of fine motor control

We introduce a motion dataset from healthy human subjects ( n = 125) performing two fine motor control tasks on a graphic tablet, namely circle drawing and circle tracing. The article reports the methods and materials used to capture the motion data. The method for data acquisition is the same as the one used to investigate some aspects of fine motor control in healthy subjects in the paper by Cohen et al. (2018) Precision in drawing and tracing tasks: Different measures for different aspects of fine motor control (https://doi.org/10.1016/j.humov.2018.08.004 ) [1] . The dataset shared here contains new raw files of the two-dimensional motion data, as well information on the participants (gender, age, laterality index). These data could be instrumental for assessing other aspects of fine motor control, such as speed-accuracy tradeoff, speed-curvature power law, etc., and/or test machine learning algorithms for e.g., task classification. (C) 2021 The Authors. Published by Elsevier Inc.

Automated summary

This article introduces a motion dataset from healthy human subjects performing fine motor control tasks on a graphic tablet, which could be used for assessing different aspects of fine motor control and testing machine learning algorithms.