A Simple and Accurate onset Detection Method for a Measured Bell-shaped Speed Profile

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 detec...

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Bibliographic Details
Published in:Frontiers in neuroscience 2009-01, Vol.3, p.61-61
Main Authors: Botzer, Lior, Karniel, Amir
Format: Article
Language:English
Subjects:
Algorithms
feedforward control
Methods
minimum jerk
Motor task performance
movement onset
Neuroscience
Noise
onset detection
Reaction Time
Velocity
velocity threshold
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Summary: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.
ISSN:1662-453X
1662-4548
1662-453X
DOI:10.3389/neuro.20.002.2009