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Related Concept Videos

Inertial Frames of Reference01:03

Inertial Frames of Reference

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Newton’s first law is usually considered to be a statement about reference frames. It provides a method for identifying a special type of reference frame: the inertial reference frame. In principle, we can make the net force on a body zero. If its velocity relative to a given frame is constant, then that frame is said to be inertial. So, by definition, an inertial reference frame is a reference frame where Newton's first law holds valid. Newton's first law applies to objects with...
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Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
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Non-inertial Frames of Reference01:27

Non-inertial Frames of Reference

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A reference frame accelerating or decelerating relative to an inertial frame is a non-inertial frame. To help understand this, consider what taking off in an airplane, turning a corner in a car, riding a merry-go-round, and the circular motion of a tropical cyclone all have in common. All these systems are accelerating, decelerating, or rotating relative to the Earth; hence, they all are non-inertial frames. All these systems exhibit inertial forces, which merely seem to arise from motion,...
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
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Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
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Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

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Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
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Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
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Drift-free position estimation for periodic movements using inertial units.

Nora Millor, Pablo Lecumberri, Marisol Gomez

    IEEE Journal of Biomedical and Health Informatics
    |July 12, 2014
    PubMed
    Summary

    A new PB-algorithm effectively cancels drift disturbances in human motion analysis using inertial units (IUs). This method improves position estimation accuracy for periodic movements, aiding clinical assessments like the chair stand test.

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    Area of Science:

    • Biomechanics
    • Signal Processing
    • Wearable Technology

    Background:

    • Microelectromechanical systems (MEMS) advance inertial units (IUs) for human motion analysis.
    • Challenges remain in processing IU output signals, particularly drift disturbances affecting position estimation.

    Purpose of the Study:

    • Develop a novel "PB-algorithm" to cancel drift disturbances in position estimation for periodic human movements.
    • Enhance the accuracy of motion analysis using IU data.

    Main Methods:

    • The PB-algorithm integrates polynomial data fitting, splines interpolation, and wavelet transform sequentially.
    • Validation employed high-accuracy optical system (Vicon Nexus 1.0) measurements.
    • Comparison with a modified-band limited Fourier linear combiner was conducted.

    Main Results:

    • The PB-algorithm achieved high accuracy, with Euclidean error < 54.62 × 10(-3) m and correlation coefficient > 0.968 against Vicon reference data.
    • A 68.74% reduction in root-mean-square error was observed compared to the Fourier linear combiner.
    • The algorithm was applied to the 30-second chair stand test data.

    Conclusions:

    • The PB-algorithm effectively cancels drift disturbances in IU-based motion analysis.
    • Accurate Z-position estimation enables detailed evaluation of sit-to-stand and stand-to-sit transitions.
    • This advancement supports clinical applications in assessing older adults' functional status.