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Behavior Research Methods

, Volume 39, Issue 4, pp 748–754 | Cite as

Comparing derived and acquired acceleration profiles: 3-D optical electronic data analyses

  • Steve HansenEmail author
  • Digby Elliott
  • Michael A. Khan
Article

Abstract

Advances in technology in the last century have provided the opportunity to observe human behavior in one, two, and three dimensions with higher recording frequencies and greater spatial accuracy. Consequently, detailed analyses of individual trials and composite measures of multiple movement trajectories are possible. However, 3-D data have often been analyzed by performing independent analyses of the limb trajectory along each axis. Essentially, analyses of individual axes are often inappropriate as movement in each axis can contribute to the overall trajectory. Employing such methods can compound error throughout the analysis process. The purpose of this study was to determine appropriate post hoc and real-time 3-D optoelectronic data reduction procedures for manual aiming movements. Rapid goal-directed movements were recorded using an Optotrak and triaxial accelerometer. Data were separately subjected to second order Butterworth filters employing low-cut frequencies of 6–24 Hz in 2 Hz increments. Subsequently, acceleration profiles were derived by double differentiating the individual position profiles and then calculating the resultant acceleration profile. In addition, acceleration profiles were also calculated by finding the resultant position and the total distance traveled each frame prior to double differentiation. Root mean square error between the derived and acquired profiles was employed as our main dependent measure. Trajectories reduced with the total distance procedure produced the lowest root mean square error. The results are important for experimenters analyzing 3-D data post hoc and those implementing real-time manipulations.

Keywords

Root Mean Square Error Visual Condition Derivation Method Lower Root Mean Square Error Home Position 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Psychonomic Society, Inc. 2007

Authors and Affiliations

  1. 1.Department of KinesiologyMcMaster UniversityHamiltonCanada
  2. 2.University of WalesBangorWales

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