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Related Concept Videos

Functional Classification of Joints01:09

Functional Classification of Joints

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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
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Development of the Limb Synovial Joints01:07

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Joints form during embryonic development in conjunction with the formation and growth of the associated bones. The embryonic tissue that gives rise to all bones, cartilage, and connective tissues of the body is called mesenchyme.
The mesenchymal stem cells differentiate into chondrocytes that form the hyaline cartilage, and later the cartilaginous model of the bone. This model further transforms into a bone. This process is known as endochondral ossification.
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Structural Classification of Joints01:20

Structural Classification of Joints

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Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
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Introduction to Joints00:58

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The adult human body usually has 206 bones, and except for the hyoid bone in the neck, each bone is connected to at least one other bone. Joints are the location where bones come together. Many joints allow for movement between the bones. At these joints, the articulating surfaces of the adjacent bones can move smoothly against each other. However, the bones of other joints may be joined by connective tissue or cartilage. These joints are designed for stability and provide little or no...
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Movement Joints in Buildings01:27

Movement Joints in Buildings

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Movement joints in buildings are essential design elements that accommodate inevitable motions caused by various factors such as temperature changes, moisture content variations, and structural deflections. These motions, if not considered in design and construction, can lead to unsightly or dangerous damage. Movement joints are incorporated in different forms to manage these stresses and allow materials to move without causing distress.
The simplest type of movement joints, working joints, are...
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Method of Joints: Problem Solving II01:30

Method of Joints: Problem Solving II

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Consider a truss structure with frictionless joints fixed to a wall and roller support. If a force of 150 N is applied to joint A, the forces in each member of the truss can be determined using the method of joints.
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Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
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Research on Discrete Semantics in Continuous Hand Joint Movement Based on Perception and Expression.

Lesong Jia1, Xiaozhou Zhou1, Hao Qin1

  • 1School of Mechanical Engineering, Southeast University, Nanjing 211189, China.

Sensors (Basel, Switzerland)
|June 2, 2021
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Summary

This study quantifies semantic states in hand gestures, defining typical movement angles for each state. This research provides a discrete gesture semantic expression space for advancing gesture recognition and design.

Keywords:
Leap Motiondiscreteness of cognitionhand gesturehuman mirroring mechanismsemantic cognition

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Area of Science:

  • Human-Computer Interaction
  • Robotics
  • Computer Vision

Background:

  • Continuous hand movements convey discrete semantic gestures.
  • Existing research lacks quantification of semantic states within hand motion primitives, including their intervals and representative angles.

Purpose of the Study:

  • To determine the number of semantic states for each hand motion primitive.
  • To define the interval and typical motion angle for each semantic state.
  • To establish a quantitative semantic expression space for hand gestures.

Main Methods:

  • Conducted perception and expression experiments to analyze semantic levels and boundaries of motion primitives.
  • Verified and optimized segmentation results to determine typical motion values for each semantic state.
  • Empirically applied semantic state segmentation using Leap Motion data.

Main Results:

  • Defined a discrete gesture semantic expression space for both real-world and digital environments.
  • Clearly identified the number of semantic states, boundaries, and typical motion angles for each hand motion primitive.
  • Demonstrated the application of semantic state segmentation with Leap Motion.

Conclusions:

  • The developed quantitative semantic expression space aids in understanding and segmenting hand gestures.
  • This framework will guide and advance research in gesture coding, recognition, and design.
  • Provides a foundation for more sophisticated human-computer interaction through precise gesture interpretation.