Dataset A dataset of human manipulation actions recorded with a motion capture system. A Qualisys motion capture system was used to record the data. We tracked individual finger movements as well as the position and orientation of the right hand. Some recordings contain additional markers at the back, shoulder, and elbow. The motion capture setup is explained here. The dataset contains the original recordings of manipulation actions as well as metadata with annotations of relevant parts of the recordings (labels, start, end). Recordings are exported from the Qualisys Track Manager (QTM) as tab-separated value (TSV) files. Metadata is provided in JSON format. Related software is available at github.com/dfki-ric/hand_embodiment, which also contains code to load and use the dataset. Publication This dataset was introduced in the following paper: Alexander Fabisch, Manuela Uliano, Dennis Marschner, Melvin Laux, Johannes Brust, Marco Controzzi: "A Modular Approach to the Embodiment of Hand Motions from Human Demonstrations", Proceedings of IEEE-RAS International Conference on Humanoid Robots 2022. It is available from arxiv.org as a preprint or from IEEE. If you use the dataset, please cite the paper as: @INPROCEEDINGS{Fabisch2022, author={Fabisch, Alexander and Uliano, Manuela and Marschner, Dennis and Laux, Melvin and Brust, Johannes and Controzzi, Marco}, booktitle={2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)}, title={A Modular Approach to the Embodiment of Hand Motions from Human Demonstrations}, year={2022}, pages={801--808}, doi={10.1109/Humanoids53995.2022.10000165}} Ethics Approval Experimental protocols were approved by the ethics committee of the University of Bremen. Written informed consent was obtained from all participants for participation in the study and to publish this dataset. Origin and Funding This dataset is provided by the Robotics Innovation Center, DFKI GmbH. This work was supported by the European Commission under the Horizon 2020 framework program for Research and Innovation (project acronym: APRIL, project number: 870142).