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Related Concept Videos

Structural Joints: Synovial Joints01:16

Structural Joints: Synovial Joints

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Synovial joints are the most common type of joint in the body. A key structural characteristic for a synovial joint is the presence of a joint cavity. This fluid-filled space is where the articulating surfaces of the bones contact each other. Also, unlike fibrous or cartilaginous joints, the articulating bone surfaces at a synovial joint are not directly connected to each other with fibrous connective tissue or cartilage. This gives the bones of a synovial joint the ability to move smoothly...
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Structural Joints: Fibrous Joints01:03

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Fibrous joints are a type of joint where the bones are connected by fibrous connective tissue. These joints provide stability and minimal to no movement between the articulating bones. There are three types of fibrous joints.
Suture
All the bones of the skull, except for the mandible, are joined to each other by a fibrous joint called a suture. The fibrous connective tissue found at a suture strongly unites the adjacent skull bones and thus helps to protect the brain and form the face. In...
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Structural Joints: Cartilaginous Joints01:17

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As the name indicates, at a cartilaginous joint, the adjacent bones are united by cartilage, a tough but flexible type of connective tissue. Unlike synovial joints, these types of joints lack a joint cavity and involve bones joined together by either hyaline cartilage or fibrocartilage.
There are two types of cartilaginous joints:
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A synchondrosis ("joined by cartilage") is a cartilaginous joint where bones are connected by hyaline cartilage. Synchondrosis may be temporary...
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Joints01:26

Joints

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Joints, also called articulations or articular surfaces, are points at which ligaments or other tissues connect adjacent bones. Joints permit movement and stability, and can be classified based on their structure or function.
Structural joint classifications are based on the material that makes up the joint as well as whether or not the joint contains a space between the bones. Joints are structurally classified as fibrous, cartilaginous, or synovial.
Fibrous Joints Are Immovable
The bones of a...
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Contact Angle01:13

Contact Angle

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When a solid is dipped inside a liquid, the liquid surface becomes curved near the contact. For some solid–liquid interfaces, the liquid is pulled up along the solid, while for others, the liquid surface is convex or depressed near the solid surface. This phenomenon can be explained using the concept of cohesive and adhesive forces.
The adhesive force is the molecular force between molecules of different materials, that is, between the molecules of the solid and the liquid. The cohesive...
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What are Estimates?01:06

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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
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Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
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Elbow Joint Angle Estimation with Surface Electromyography Using Autoregressive Models.

L F Sommer, C Barreira, C Noriega

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |November 17, 2018
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    Summary
    This summary is machine-generated.

    This study estimates elbow joint angles using surface electromyography (sEMG) from arm muscles. The developed method accurately predicts joint angles, crucial for human-robot interfaces and biomechanical modeling.

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    Area of Science:

    • Biomedical Engineering
    • Robotics
    • Biomechanics

    Background:

    • Surface electromyography (sEMG) is vital for human-robot interfaces.
    • Interpreting sEMG signals is challenging due to signal complexities.

    Purpose of the Study:

    • To develop and validate a method for estimating elbow joint angles from sEMG.
    • To improve sEMG-based human-robot interaction and biomechanical modeling.

    Main Methods:

    • Experiments with six subjects performing elbow movements under varying loads.
    • Recorded sEMG from biceps, triceps, and brachioradialis, alongside joint angles.
    • Evaluated four modeling techniques: State Space, ARX, ARMAX, and ARIMAX.

    Main Results:

    • A robust procedure for estimating the EMG-to-angle relationship was established.
    • High correlation and low root-mean-square errors were achieved between estimated and measured angles.
    • The chosen model demonstrated effective validation in a separate experiment.

    Conclusions:

    • The proposed sEMG-based method accurately estimates elbow joint angles.
    • This technique has significant implications for designing advanced human-robot interfaces.
    • The findings contribute to more precise muscular system modeling and biomimetic mechanism design.