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A computational theory for movement pattern recognition based on optimal movement pattern generation

Y Wada1, Y Koike, E Vatikiotis-Bateson

  • 1ATR Human Information Processing Research Laboratories, Soraku-gun, Kyoto, Japan.

Biological Cybernetics
|June 1, 1995
PubMed
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This study introduces a computational theory for recognizing movement patterns, linking generation and perception. It demonstrates how motor control processes can be used for movement pattern recognition, particularly in handwriting and speech.

Area of Science:

  • Computational Neuroscience
  • Motor Control Theory
  • Pattern Recognition

Background:

  • Previous work proposed an optimal trajectory and control theory for continuous movements.
  • This theory is based on Marr's three-level description of brain function: computational theory (minimum torque-change model), intermediate representation (via-points), and algorithm/hardware (FIRM neural network).

Purpose of the Study:

  • To propose a computational theory for movement pattern recognition.
  • To demonstrate the coupling between pattern generation and recognition processes.
  • To validate the 'motor theory of movement pattern perception' computationally.

Main Methods:

  • Utilized a computational theory based on optimal movement pattern generation.
  • Treated recognition as an inverse flow of information within a single functional unit alongside generation.

Related Experiment Videos

  • Implemented error correction through repeated generation if input data deviates from the reconstructed optimal pattern.

    • Main Results:

    • Developed computational procedures for recognizing connected cursive handwritten characters.
    • Enabled estimation of phonemic timing in natural speech.
    • Demonstrated that movement pattern recognition can be achieved by actively recruiting the movement pattern formation process.

    Conclusions:

    • The recognition and generation of movement patterns are two directional flows within a unified functional system.
    • Movement pattern perception is computationally realizable through the recruitment of the motor pattern formation process.
    • A duality exists between movement pattern formation and movement pattern perception.