A simple and accurate onset detection method for a measured bell-shaped speed profile

Lior Botzer, Amir Karnie

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Motor control neuroscientists measure limb trajectories and extract the onset of the movement for a variety of purposes. Such trajectories are often aligned relative to the onset of individual movement before the features of that movement are extracted and their properties are inspected. Onset detection is performed either manually or automatically, typically by selecting a velocity threshold. Here, we present a simple onset detection algorithm that is more accurate than the conventional velocity threshold technique. The proposed method is based on a simple regression and follows the minimum acceleration with constraints model, in which the initial phase of the bell-shaped movement is modeled by a cubic power of the time. We demonstrate the performance of the suggested method and compare it to the velocity threshold technique and to manual onset detection by a group of motor control experts. The database for this comparison consists of simulated minimum jerk trajectories and recorded reaching movements. Copyright:.

Original languageEnglish
Article numberArticle 61
JournalFrontiers in Neuroscience
Volume3
Issue numberJUN
DOIs
StatePublished - 1 Dec 2009

Keywords

  • Feedforward control
  • Minimum jerk
  • Movement onset
  • Onset detection
  • Reaction time
  • Velocity threshold

ASJC Scopus subject areas

  • Neuroscience (all)

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