Determining natural arm configuration along a reaching trajectory

Owing to the flexibility and redundancy of neuromuscular and skeletal systems, humans can trace the same hand trajectory in space with various arm configurations. However, the joint trajectories of typical unrestrained movements tend to be consistent both within and across subjects. In this paper we...

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Bibliographic Details
Published in:Experimental brain research 2005-12, Vol.167 (3), p.352-361
Main Authors: TAO KANG, JIPING HE, TILLERY, Stephen I. Helms
Format: Article
Language:English
Subjects:
Algorithms
Arm - innervation
Arm - physiology
Biological and medical sciences
Biomechanical Phenomena
Elbow
Fundamental and applied biological sciences. Psychology
Human subjects
Humans
Joints - physiology
Kinematics
Medical sciences
Models, Statistical
Motor control and motor pathways. Reflexes. Control centers of vegetative functions. Vestibular system and equilibration
Movement - physiology
Ophthalmology
Psychomotor Performance - physiology
Reproducibility of Results
Vertebrates: nervous system and sense organs
Vision disorders
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Summary:Owing to the flexibility and redundancy of neuromuscular and skeletal systems, humans can trace the same hand trajectory in space with various arm configurations. However, the joint trajectories of typical unrestrained movements tend to be consistent both within and across subjects. In this paper we propose a method to solve the 3-D inverse kinematics problem based on minimizing the magnitude of total work done by joint torques. We examined the fit of the joint-space trajectories against those observed from human performance in a variety of movement paths in 3-D workspace. The results showed that the joint-space trajectories produced by the method are in good agreement with the subjects' arm movements (r2>0.98), with the exception of shoulder adduction/abduction (where, in the worst case, r2 approximately 0.8). Comparison of humeral rotation predicted by our algorithm with other models showed that the correlation coefficient r2) between actual data and our predictions is extremely high (mostly >0.98, 11 out of 15 cases, with a few exceptions, 4 of 15, in the range of 0.8-0.9) and the slope of linear regression is much closer to one (0.15). However, the discrepancy in shoulder adduction/abduction indicated that when only the hand path is known, additional constraint(s) may be required to generate a complete match with human performance.
ISSN:0014-4819
1432-1106
DOI:10.1007/s00221-005-0039-5