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Related Concept Videos

Muscle Coordination and Action01:24

Muscle Coordination and Action

Muscle coordination is a complex and finely tuned process essential for smooth and purposeful movements like flexion, extension, adduction, abduction, and rotation. The human body orchestrates the actions of various muscles working in concert, each with a specific role. Four functional types describe how muscles work together: agonist, antagonist, synergist, and fixator.
Agonists
Agonist muscles, often called prime movers, are the primary muscles responsible for producing a specific movement.
Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
Kinematic Equations - III01:18

Kinematic Equations - III

The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
Using the kinematic equations,...
Kinematic Equations - II01:17

Kinematic Equations - II

The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
Suppose a car merges into freeway traffic on a 200 m long ramp. If its initial velocity is 10 m/s and it accelerates at 2 m/s2, then the...
Kinematic Equations - I01:26

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When an object moves with constant acceleration, the velocity of the object changes at a constant rate throughout the motion. The kinematic equations of motions are derived for such cases where the acceleration of the object is constant. The first kinematic equation gives an insight into the relationship between velocity, acceleration, and time. We can see, for example:
Movement Joints in Buildings01:27

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Corticospinal Excitability Modulation During Action Observation
12:33

Corticospinal Excitability Modulation During Action Observation

Published on: December 31, 2013

Modeling inter-human movement coordination: synchronization governs joint task dynamics.

Alexander Mörtl1, Tamara Lorenz, Björn N S Vlaskamp

  • 1Institute of Automatic Control Engineering, Technische Universität München, Munich, Germany, moertl@tum.de

Biological Cybernetics
|June 1, 2012
PubMed
Summary

Human partners synchronize arm movements during goal-directed tasks. A new model, inspired by coupled oscillators, accurately predicts these coordination dynamics, enhancing human-robot interaction.

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Area of Science:

  • Human-Computer Interaction
  • Robotics
  • Dynamical Systems Theory

Background:

  • Human interaction partners often synchronize movements during repetitive actions like walking.
  • Previous research focused on rhythmic tasks, showing synchronization dominates.
  • Human dyads synchronize arm movements even in goal-directed tasks.

Purpose of the Study:

  • To present a step-wise model for inter-human movement coordination.
  • To investigate phase synchronization in goal-directed arm movements.
  • To evaluate the model's ability to predict observed coordination patterns.

Main Methods:

  • Recorded hand trajectories of ten human dyads during a task.
  • Applied dynamical process of phase synchronization to analyze movement data.
  • Utilized coupled phase oscillators inspired by the Kuramoto model.
  • Investigated three methods for transforming motion trajectories into instantaneous phases.
  • Employed system identification to estimate model parameters (coupling strength, frequency detuning).

Main Results:

  • Participants established in-phase and anti-phase relations.
  • The model successfully reproduced emerging synchronization relations.
  • Model fit to experimental data was evaluated based on phase transformation methods.
  • Identified model parameters showed stability properties matching experimental observations.

Conclusions:

  • The developed model accurately predicts the dynamics of inter-human movement coordination.
  • The model can be directly implemented to enhance human-robot interaction.
  • Phase synchronization is a key mechanism in goal-directed human movement coordination.