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Experimental Brain Research

, Volume 188, Issue 2, pp 223–236 | Cite as

The statistics of natural hand movements

  • James N. Ingram
  • Konrad P. Körding
  • Ian S. Howard
  • Daniel M. Wolpert
Research Article
First Online:
Received:
Accepted:

Abstract

Humans constantly use their hands to interact with the environment and they engage spontaneously in a wide variety of manual activities during everyday life. In contrast, laboratory-based studies of hand function have used a limited range of predefined tasks. The natural movements made by the hand during everyday life have thus received little attention. Here, we developed a portable recording device that can be worn by subjects to track movements of their right hand as they go about their daily routine outside of a laboratory setting. We analyse the kinematic data using various statistical methods. Principal component analysis of the joint angular velocities showed that the first two components were highly conserved across subjects, explained 60% of the variance and were qualitatively similar to those reported in previous studies of reach-to-grasp movements. To examine the independence of the digits, we developed a measure based on the degree to which the movements of each digit could be linearly predicted from the movements of the other four digits. Our independence measure was highly correlated with results from previous studies of the hand, including the estimated size of the digit representations in primary motor cortex and other laboratory measures of digit individuation. Specifically, the thumb was found to be the most independent of the digits and the index finger was the most independent of the fingers. These results support and extend laboratory-based studies of the human hand.

Keywords

Human hand Digit independence Dimensionality of hand movements Movement statistics 
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Notes

Acknowledgments

We thank Roger Lemon for useful comments on an early version of the manuscript. GRANTS: This work was supported by the Wellcome Trust and the Human Frontiers Science Program.

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • James N. Ingram
    • 1
  • Konrad P. Körding
    • 2
  • Ian S. Howard
    • 1
  • Daniel M. Wolpert
    • 1
  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUK
  2. 2.Rehabilitation Institute of Chicago, Departments of Physiology, Physical Medicine and Rehabilitation and Applied MathematicsNorthwestern UniversityChicagoUSA

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