Human hand motion data collected by commercial motion capture system and custom-made data glove

This dataset presents diverse human hand motions in various forms including:Forward kinematic hand model implemented in 3d computer graphics software tool (/Joint angles/HandModel.blend);Bone lengths of 13 subjects (9 males, 4 females);Motion-captured rotations of the finger bones in Euler angles;Joint angles of the finger joints that were calculated by post-processing the motion-captured rotations.Also, with the aim of real-time tracking of these hand motions using the custom-made data glove, we provide:Sensor signals measured by the data glove during the hand motions;Regression model that relates the bone lengths and the sensor signals measured at the zero pose for instantaneous estimation of the bone lengths of the wearer;Filtering process for further refinement of the bone lengths estimation using the subsequent sensor signals;Filtering process for estimation of the joint angles using the subsequent sensor signals.ReadmeThe dataset is composed of three folders (/Initial bone lengths, /Refined bone lengths, and /Joint angles) and in each folder there exists Matlab or Python script that infers the collected motion-capture data and sensor signals in the /Data folder.How to use:Initial bone lengths: Run InitialBoneLengthsEstimation.mRefined bone lengths: Run RefinedBoneLengthsEstimation.mJoint angles1. Run Calibration.py to output the linear model (already included in ./Data/230703_1440/model)2. Open HandModel.blend, Open Text editor, and Press Run script (Alt+P)3. Run JointAngleEstimation.pyDetailed results, experimental procedures, post-processing methods of the data, and the filtering algorithms are described in Stretchable glove for accurate and robust hand pose reconstruction based on comprehensive motion data, Nature Communications, 2024 (https://doi.org/10.1038/s41467-024-50101-w).