Dataset Name: Haptic Exploration of Real Objects (September 2015)
Research Group: UNIPI
Hand Type: Human Hand
Data Type: Human Motion Data
Data Structure: Joint Angles (rad)
Data Format: .mat
Sampling Rate: >100 Hz (480 Hz)
Action Type: Haptic Exploration
Objects Type: Real Objects
Kin. Model #DOFs: >20 (26)
Equipment: Motion Capture System -> Phase Space
# of Actions: >20
# of Subjects: 1
The subject was blindfolded and asked to identify some common objects. Before each trial, the subject placed the dominant hand on a table and one of the objects was placed in random order about 30 cm in front of the hand. On a go signal, the subject reached out, explored and identified the object. In addition, the subject was asked to explore the surface curvature, edges and textures of each object in order to prolong the exploration time, because a simple object identification task is trivial and takes a very short time.
How to Cite:
 M. Gabiccini, G. Stillfried, H. Marino, M. Bianchi. A data-driven kinematic model of the human hand with soft-tissue artifact compensation mechanism for grasp synergy analysis. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2013. Tokyo, Japan.
 Pramodsingh H. Thakur, Amy J. Bastian, and Steven S. Hsiao, “Multidigit movement synergies of the human hand in an unconstrained haptic exploration task”, In: The Journal of neuroscience 28.6 (2008), pp. 1271–1281.