The statistics of natural hand movements

James N. Ingram, Konrad P. Körding, Ian S. Howard, Daniel M. Wolpert

Research output: Contribution to journalArticlepeer-review

168 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)223-236
Number of pages14
JournalExperimental Brain Research
Volume188
Issue number2
DOIs
StatePublished - Jun 2008

Keywords

  • Digit independence
  • Dimensionality of hand movements
  • Human hand
  • Movement statistics

ASJC Scopus subject areas

  • Neuroscience(all)

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