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Related Experiment Video

Updated: Nov 19, 2025

Movement Retraining using Real-time Feedback of Performance
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Forward Inverse Relaxation Model Incorporating Movement Duration Optimization.

Misaki Takeda1, Isao Nambu1, Yasuhiro Wada1

  • 1Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata 940-2188, Japan.

Brain Sciences
|January 27, 2021
PubMed
Summary
This summary is machine-generated.

This study enhances the Forward Inverse Relaxation Model (FIRM) for human arm movement by optimizing movement duration. The updated model accurately predicts movement time and trajectory features, improving computational modeling of human motion.

Keywords:
arm dynamicsforward inverse relaxation modelhuman arm movementmovement durationoptimization modelreaching movementsignal-dependent noisespeed-accuracy trade-off

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Area of Science:

  • Robotics
  • Biomechanics
  • Computational Neuroscience

Background:

  • The Forward Inverse Relaxation Model (FIRM) effectively models human arm movements.
  • Existing FIRM versions treat movement duration as a fixed parameter, not an optimized variable.
  • Empirical data shows movement duration is influenced by task factors like accuracy and distance.

Purpose of the Study:

  • To develop an enhanced FIRM incorporating a movement duration optimization module.
  • To investigate the optimization criteria for movement duration in human arm movements.
  • To validate the model's ability to reproduce empirical movement characteristics.

Main Methods:

  • Introduced a movement duration optimization module into the FIRM.
  • The module minimizes a weighted sum of trajectory cost (torque change) and time cost (tolerance).
  • Conducted behavioral experiments to compare model predictions with actual human arm movements.

Main Results:

  • The optimized movement duration from the model closely matched observed movement durations.
  • Trajectories generated by the enhanced FIRM accurately reproduced features of actual human arm trajectories.
  • The model's predictions align well with empirical observations of human arm movement.

Conclusions:

  • The proposed FIRM with an integrated movement duration optimization module accurately captures human arm movement dynamics.
  • This enhanced computational model shows promise for precise measurement and analysis of human motor behavior.
  • The findings support the use of this optimized FIRM in understanding and replicating human movement patterns.