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Related Concept Videos

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:
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The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
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Kinematic Equations - II01:17

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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.
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In mechanics, when one observes a rigid body in rotational motion with constant angular acceleration, it is possible to establish equations for its rotational kinematics. This process resembles how linear kinematics are dealt with in simpler motion studies.
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Related Experiment Video

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A Repetitive Concussive Head Injury Model in Mice
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A Fast-Running, End-to-End Concussion Risk Model for Assessment of Complex Human Head Kinematics.

Pi Phohomsiri1, Melissa Gibbons1, Vladislav Volman1

  • 1L-3 Applied Technology, 10180 Barnes Canyon Road Suite 100, San Diego, CA 92121.

Military Medicine
|April 11, 2018
PubMed
Summary
This summary is machine-generated.

A new algorithm simplifies a complex concussion risk model, accurately predicting injury from head motion. This innovation enables real-time concussion assessment using head-worn sensors.

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Area of Science:

  • Biomechanics
  • Neuroscience
  • Sports Medicine

Background:

  • Concussion risk models are crucial for injury assessment.
  • Current models often rely on external correlates like peak head acceleration.
  • There's a need for real-time, accurate concussion prediction from head-worn sensors.

Purpose of the Study:

  • To develop a simplified, fast-running algorithm for concussion risk assessment.
  • To enable embedding a concussion model onto head-worn sensor microprocessors.
  • To achieve comparable accuracy to a complex, computationally expensive end-to-end model.

Main Methods:

  • Mathematical modeling of dynamic axonal response using a lumped parameter system.
  • Fitting the lumped parameter model to finite element model responses for various head motions.
  • Simplifying other component models of the full end-to-end model.

Main Results:

  • The simplified algorithm demonstrates comparable results to the full end-to-end model.
  • Probabilities of concussion from both models align for identical head kinematic scenarios.
  • The developed algorithm is computationally efficient and suitable for sensor integration.

Conclusions:

  • A simplified, fast-running algorithm can effectively predict concussion risk.
  • This algorithm bridges the gap between research-level models and practical, real-time sensor applications.
  • The approach allows for more accessible and immediate concussion assessment in various settings.