title: Human arm movements described by a low-dimensional superposition of principal components.
abstract: A new method for analyzing kinematic patterns during smooth movements is proposed. Subjects are asked to move the end of a two-joint manipulandum to copy a smooth initial target path. On subsequent trials the target path is the subject's actual movement from the preceding trial. Using Principal Components Analysis, it is shown that the trajectories have very low dimension and that they converge toward a linear superposition of the first few principal components. We show similar results for handwriting on an electronic pen tablet. We hypothesize that the low dimensionality and convergence are attributable to combined properties of the internal controller and the musculoskeletal system. The low dimensionality may allow for efficient descriptions of a large class of arm movements.
authors.affiliation: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. tds@ai.mit.edu
authors.forename: T D
authors.initials: TD
authors.lastname: Sanger
mesh_terms: D001132:Arm / Q000502:physiology*; D001696:Biomechanical Phenomena; D006236:Handwriting; D006801:Humans; D016014:Linear Models; D009068:Movement / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology