NDLI: An inverse kinematics algorithm for upper-limb joint reconstruction during robot-aided motor therapy

Content Provider	IEEE Xplore Digital Library
Author	Papaleo, E. Zollo, L. Sterzi, S. Guglielmelli, E.
Copyright Year	2012
Description	Author affiliation: Laboratory of Biomedical Robotics and Biomicrosystems, Università Campus Bio-Medico di Roma, via Àlvaro del Portillo 21, 00128 Roma, Italy (Papaleo, E.; Zollo, L.; Guglielmelli, E.) \|\| Department of Physical Medicine and Rehabilitation, Università Campus Bio-Medico di Roma, via Àlvaro del Portillo 21, 00128 Roma, Italy (Sterzi, S.)
Abstract	The paper presents an analytical procedure, based on inverse kinematics with an Augmented Jacobian matrix, for reconstructing human arm joint motion during robot-aided motor therapy with an end-effector machine. The presented method can be exploited for investigating arm motion in the joint space and, accordingly, determining objective indicators of patient kinematic performance in order to plan and adapt the therapy to his/her capabilities. The proposed technique exploits hand pose data, provided by the robot, and a constraint on the elbow trajectories to solve redundancy. In order to compute elbow trajectories, two additional magneto-inertial sensors located on the upper arm are used. Theoretical formulation and experimental validation of the method are presented in the paper; finally, a comparative analysis with an optoelectronic motion capture system is carried out to assess the level of accuracy and reliability of the proposed algorithm.
Starting Page	1983
Ending Page	1988
File Size	3214098
Page Count	6
File Format	PDF
ISBN	9781457711992
ISSN	21551774
e-ISBN	9781457712005
DOI	10.1109/BioRob.2012.6290861
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-24
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kinematics Robot sensing systems Vectors Trajectory Joints Elbow
Content Type	Text
Resource Type	Article

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