Dataset Name: NTUA Dataset (May 2010)
Research Group: NTUA
Hand Type: Human Hand
Data Type: Human Motion Data, Human Postures
Data Structure: Joint Angles (deg)
Data Format: .txt
Sampling Rate: >=100 Hz (100 Hz)
Action Type: Reach and Grasp, Static Grasps
Objects Type: Real Objects
Kin. Model #DOFs: >15 & <=20 (20)
Equipment: Motion Capture System -> Cyberglove II
# of Actions: <20 (19) (4 objects: a mug x5 trials, a rectangle x5 trials, a ball x5 trials, a small ball x4 trials)
# of Subjects: 1
The role of synergies during reach to grasp movements was identiﬁed by the following experiment; a subject is seated on a chair, while his trunk is holded to the chair by means of elastic straps, so as to restrain body movements. His hand was placed at the top of the table with the palm facing downwards. Objects of varying shape and size were placed on the surface of a table at a higher point than the starting hand position. The user was instructed to move his arm in order to reach and grasp the object. For each trial the starting position of the hand and the position of the object were kept the same.
How to Cite:
 Pantelis Katsiaris, Panagiotis Artemiadis and Kostas Kyriakopoulos, “Relating Postural Synergies to Low-D Muscular Activations: Towards Bio-inspired Control of Robotic Hands,” IEEE International Conference on BioInformatics and BioEngineering, Larnaca, Cyprus, 2012.
 Ioannis Filippidis, Kostas Kyriakopoulos and Panagiotis Artemiadis, “Navigation Functions Learning from Experiments: Application to Anthropomorphic Grasping,” IEEE International Conference on Robotics and Automation (ICRA), pp. 570-575, 2012.
 Minas V. Liarokapis, Panagiotis K. Artemiadis and Kostas J. Kyriakopoulos, “Telemanipulation with the DLR/HIT II Robot Hand Using a Dataglove and a Low Cost Force Feedback Device”, IEEE Mediterranean Conference on Control and Automation (MED), Chania (Greece), 2013.