caa a22 4500 445353724 CHVBK 20180317142853.0 cr unu---uuuuu 170323e20110701xx s 000 0 eng 10.1007/s00221-011-2747-3 doi (NATIONALLICENCE)springer-10.1007/s00221-011-2747-3 Pointing with the wrist: a postural model for Donders' law [Elektronische Daten] [Domenico Campolo, Ferdinan Widjaja, Mohammad Esmaeili, Etienne Burdet] The central nervous system uses stereotypical combinations of the three wrist/forearm joint angles to point in a given (2D) direction in space. In this paper, we first confirm and analyze this Donders' law for the wrist as well as the distributions of the joint angles. We find that the quadratic surfaces fitting the experimental wrist configurations during pointing tasks are characterized by a subject-specific Koenderink shape index and by a bias due to the prono-supination angle distribution. We then introduce a simple postural model using only four parameters to explain these characteristics in a pointing task. The model specifies the redundancy of the pointing task by determining the one-dimensional task-equivalent manifold (TEM), parameterized via wrist torsion. For every pointing direction, the torsion is obtained by the concurrent minimization of an extrinsic cost, which guarantees minimal angle rotations (similar to Listing's law for eye movements) and of an intrinsic cost, which penalizes wrist configurations away from comfortable postures. This allows simulating the sequence of wrist orientations to point at eight peripheral targets, from a central one, passing through intermediate points. The simulation first shows that in contrast to eye movements, which can be predicted by only considering the extrinsic cost (i.e., Listing's law), both costs are necessary to account for the wrist/forearm experimental data. Second, fitting the synthetic Donders' law from the simulated task with a quadratic surface yields similar fitting errors compared to experimental data. Springer-Verlag, 2011 Human wrist nationallicence Kinematic redundancy nationallicence Donders' law nationallicence Hopf fibration nationallicence Multi-objective optimization nationallicence Campolo Domenico School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Nanyang Avenue, Singapore aut Widjaja Ferdinan School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Nanyang Avenue, Singapore aut Esmaeili Mohammad School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Nanyang Avenue, Singapore aut Burdet Etienne Department of Bioengineering, Imperial College London, SW7 2AZ, London, UK aut Experimental Brain Research Springer-Verlag 212/3(2011-07-01), 417-427 0014-4819 212:3<417 2011 212 221 https://doi.org/10.1007/s00221-011-2747-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00221-011-2747-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Campolo Domenico School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Nanyang Avenue, Singapore aut NATIONALLICENCE 700 1- Widjaja Ferdinan School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Nanyang Avenue, Singapore aut NATIONALLICENCE 700 1- Esmaeili Mohammad School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Nanyang Avenue, Singapore aut NATIONALLICENCE 700 1- Burdet Etienne Department of Bioengineering, Imperial College London, SW7 2AZ, London, UK aut NATIONALLICENCE 773 0- Experimental Brain Research Springer-Verlag 212/3(2011-07-01), 417-427 0014-4819 212:3<417 2011 212 221 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer